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EPA Global Climate Research Program
NOAA/NGDC Global Change Database Program
DOCUMENTATI
EPA/600/R-92/194b
NGDC Key to Geophysical Records Documentation No. 27
Incorporated in: Global Change Database - Volume 1
£% ^ Environmental Protection Agency
Environmental Research Laboratory
Corvallis, Oregon
U.S. Department of Commerce
National Oceanic and Atmospheric Administration
National Geophysical Data Center and
World Data Center A for Solid Earth Geophysics
Boulder, Colorado
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GLOBAIL ECOSYSTEMS DATABASE
EPA Global Climate Research Program
NOAA/NGDC Global Change Database Program
DOCUMENTATION MANUAL
EPA/600/R-92/194b
NGDC Key to Geophysical Records Documentation No. 27
Incorporated in: Global Change Database, Volume 1
John J. Kineman
and
Mark A. Ohrenschall
(with contributions as noted)
June, 1992
(with corrections through September, 1992)
Produced in cooperation with the US EPA under Interagency Agreement
(Contract No. DW13934786-01-0) titled "Co-developing data, tools, and methods
for characterization and analysis of environmental system patterns to support
EPA Global Climate Change Research and Modeling."
V
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Disclaimer
The information in this document has been funded in part by the U.S. Environmental
Protection Agency (EPA) under Interagency Agreement (DW13934786-01-0) to the National
Geophysical Data Center (NOAA). It has been subjected to the agency's peer review, and it
has been approved for publication as an EPA and NOAA document While every effort has
been made to ensure that the data accompanying this documentation, as well as the
documentation itself, are properly represented given the limitations of the original data and
the current state of the art in data integration, The U.S. Government cannot assume liability
for any damages caused by inaccuracies in the data or documentation, or as a result of the
failure of the data or software to fulfill a particular purpose. The U.5. Government makes no
warranty, expressed or implied, nor does the fact of distribution constitute a warranty.
Copyright Notice
While all data, the User's Guide, and NGDC Documentation are in the public domain,
portions of the accompanying on-line documentation and software on CD-ROM and floppy
disk contain copyrighted material that may not be reproduced (or placed on public access
electronic bulletin boards) without specific authorization. The materials provided have been
assembled as an integrated set to facilitate their appropriate use. Because of this integration,
the complete materials cannot be reproduced without permission from each copyright holder.
For scientific reasons, these materials should be distributed only as an integrated set.
Trademarks
Mention of a commercial company or product in this document does not imply endorsement by the
U.S. Government, any of its agencies, or any sponsor or participant of the project for which this
document was produced. All brand or product names are trademarks or registered trademarks of
their respective companies.
GED1.0 Documentation Manual Notices
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TABLE OF CONTENTS - DISC A
GED Materials Checklist iv
Citing These Materials iv
System Requirements v
Technical Support v
Preface vi
INTRODUCTION 1
DOCUMENTATION TEMPLATE DEFINITIONS 3
DEFINITION OF TERMS 10
ABBREVIATIONS AND ACRONYMS 15
GLOBAL GEOGRAPHIC (lat/long) RASTER DATA-SETS (NESTED GED GRID)
A01 NGDC Monthly Generalized Global Vegetation Index from NOAA-9
(APR 1985 - DEC 1988) A01-1
AQ2 EDC-NESDIS Monthly Experimental Calibrated Global Vegetation Index
from NOAA-9 and 11 (APR 1985 - DEC 1990) A02-1
A03 Leemans and Cramer 1IASA Mean Monthly Values of Temperature,
Precipitation, and Cloudiness on a Global Grid A03-1
A04 Legates and Willmott Average Monthly Surface Air Temperature and
Precipitation (re-gridded) A04-1
A05 Olson World Ecosystems A05-1
A06 Leemans Holdridge Life Zone Classifications A06-1
A07 Matthews Vegetation, Land Use, and Seasonal Albedo A07-1
A08 Lerner, Matthews, and Fung Methane Emissions from Animals A08-1
A09 Matthews and Fung Global Distribution, Characteristics and
Methane Emissions of Natural Wetlands A09-1
A10 Wilson and Henderson-Sellers Global Land Cover and Soils Data for GCMs .. A10-1
All Staub and Rosensweig Zobler Soil Type, Soil Texture, Surface Slope,
and Other properties All-1
A12 Webb, Rosenzweig, and Levine Global Soil Particle Size Properties A12-1
A13 FNOC Elevation, Terrain, and Surface Characteristics — A13-1
GLOBAL GEOGRAPHIC (lat/long) VECTOR DATA-SETS (GED FORMAT)
A14 Pospeschil Micro World Data Bank 27 A14-1
EXPERIMENTAL SOURCE DATA (NON-NESTED RASTER GRID)
A15X Edwards Global Gridded Elevation and Bathymetry A15X-1
A16X UNEP/GRID Gridded FAO/UNESCO Soil Units . A16X-1
REPRINTS (scanned images on CD-ROM)
GED 1.0 Documentation Manual Table of Contents - Disc A iii
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GED Materials Checklist
Please confirm that you have a complete set of materials that comprise the Global Ecosystems
Database. These are:
1. User's Guide Qune 1992)
2. GED Version 1.0, CD-ROM Disc A (June, 1992)
3. Disc-A Documentation Manual (June, 1992)
4. DOS Access and Exploration Software (floppy disk). Version 1.0
5. IDRISI-Explorer Technical Reference Manual, Version 1.0
Also available on request:
1. IDRISI 3.0 Headers (supplemental floppy disk)
2. GRASS 4.0 Headers (supplemental floppy disk)
3. Project 3-ring binder
As of this printing, Disc B of GED Version 1.0 was in preparation for pre-release review, and
scheduled for public availability December, 1992. Please contact NGDC for information on the
content and availability of Disc B or subsequent additions.
Technical memoranda about die database may be issued on occasion. In addition there is an
electronic bulletin board for communications about the Global Ecosystems Database Project
and peer-review. Contact NGDC for information about electronic bulletin-board and on-line
data services.
Citing These Materials
This database and documentation may be cited as a complete set as follows:
NOAA-EPA Global Ecosystems Database Project. 1992. Global Ecosystems Database
Version IX). User's Guide, Documentation, Reprints, and Digital Data on CD-
ROM. USDOC/NOAA National Geophysical Data Center, Boulder, CO.
The manuals may be cited individually, as follows:
Kineman, J.J. 1992. Global Ecosystems Database Version 1.0, User's Guide. Key to
Geophysical Records Documentation No. 26. USDOC/NOAA National
Geophysical Data Center, Boulder, CO. 121p.
Kineman, J.J., MA. Ohrenschall, et al. 1992. Global Ecosystems Database Version 1j0: Disc
A, Documentation Manual. Key to Geophysical Records Documentation No. 27.
USDOC/NOAA National Geophysical Data Center, Boulder, CO. 240p.
You may also cite die individual data-sets themselves. The recommended citation for each
data-set is given in the DATA-SET DESCRIPTION section of each chapter in the appropriate
Documentation Manual for a given CD-ROM disc. Literature citations are also provided in that
section.
GED 1.0 Documentation Manual GED Materials
iv
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System Requirements
The Global Ecosystems Database was designed for maximum platform independence using a
standard ISO 9660 CD-ROM format and relatively generic file formats. All data files use
common data types that are accessible at the operating system level. Nevertheless, there is no
universal standard for all systems.
Version 1.0 of die database is structured for compatibility with the IBM-PC/DOS environment.
DOS executable software is provided with the CD-ROM on an accompanying floppy disk (but
is not required to access the data files). The software provides many convenient exploration
functions for DOS users, plus export capabilities for UNIX systems. Direct access from other
operating systems is possible, but may require conversion of data storage types for correct
numerical interpretation.
The software provided on floppy disk requires an IBM-PC compatible computer running IBM-
DOS, MS-DOS, or DR-DOS, with at least 256K of memory and EGA, VGA, or 8514A graphics
(IBM 8514A compatible graphics is required for 256 color display). For optimal performance,
an Intel 80286, 80386,80486 or compatible processor with 640K of memory and a graphics
accelerator card is recommended. A CD-ROM reader is required to access the disc. Since
data access is slow from CD-ROM readers, adequate disk space to download portions of the
database to desirable. Various printers are supported.
Technical Support
NGDC staff are available to assist with inquiries about data and software availability, and
with any technical problems concerning data obtained directly from NGDC. While project
resources do not allow extensive user support for die implementation and use of this database
or software systems, NGDC staff are always willing to share their knowledge. Where more
extensive services are needed, NGDC staff may be able to refer your inquiry to an appropriate
source. Please use the following address for contact regarding this project and if s products:
Global Ecosystems Database Project
National Geophysical Data Center
325 Broadway E/GC1
Boulder, Colorado 80303
Phone: (303)497-6125
Fay: (303) 497-6513
EMAIL: infoQmail.ngdc.noaa.gov
GED 1.0 Documentation Manual System Requirements and Support
v
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Preface
The US Environmental Protection Agency (EPA), Environmental Research
Laboratory - Corvallis, Oregon (ERL-C), established an Interagency
Agreement with the US National Oceanic and Atmospheric Administration
(NOAA), National Geophysical Data Center (NGDC) in September 1990.
This agreement began a five year cooperative effort to develop a
geographic database for modeling terrestrial climate-biosphere interactions
in support of EPA's Global Climate Research Program. Although
performing specific tasks under contract to the US EPA, NGDC
independently operates a Global Change Database Program (GCDP) as part
of its NOAA mission. Considerable synergism therefore exists between the
tasks performed for the EPA under the "Global Ecosystems Database
Project," and other activities supporting NOAA Climate and Global Change
Program.
Within this contract the following cooperative goals have been established:
• Assemble and distribute periodic updates of the database in answer
to EPA needs assessments, incorporating existing data and priority
data developments, compiling appropriate and complete
documentation, providing quality assurance and quality control, and
ensuring adequate scientific review.
• Assess the data needs for global change modeling and research, and
determine future directions for database and software systems
developments.
• Pursue cooperative linkages and exchanges with parallel national
and international global change database activities.
Because this database was constructed from many pre-existing data sources
of varying quality; errors and omissions can be expected. All data are
provided for experimental use, and to initiate a process of evaluation and
improvement. Caution is advised when applying these data and computer
programs. Users should make special note of limitations mentioned in the
Documentation Manual and peer-reviews published in the User's Guide. For
example, problems are endemic in the use of uncorrected Normalized
Difference Vegetation Index (NDVI), such as the NOAA Global Vegetation
Index (GVI), for time-series analysis, and suitable corrections are still being
researched. This and similar issues associated with the various data-sets
should be the focus of initial study, along with consideration of potential
methods for inter comparison (referring here to comparisons between
different data-sets), validation, and empirical calibration using Geographic
Information System (GIS) tools and multi-thematic analysis.
GED 1.0 Documentation Manual Preface
vi
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INTRODUCTION
This Documentation Manual contains descriptive information about each data-set and exact
file descriptions for each element in the data-set. The data-set descriptions are structured
according to a precise template that is described in detail below (DOCUMENTATION
TEMPLATE DEFINITIONS). The Data-Set Description provides an in-depth
identification and tracking of the data-set and its technical properties, and gives key
references for the data-set. At the end of this description is a summary of any Data
Integration and Quality work associated with the project. Such work may range from
simple format conversion to complicated re-structuring, interpolation, and testing.
A User's Guide is provided as a separate document, giving a complete description of the
overall project, including management, research, development, and review procedures
that support the integration and improvement of this database, details of the Database
Structure. Organization of the CD-ROM, information on use with Geographic
Information Systems (GIS), as well as information on links between the database and
global change characterization and modeling.
In addition to their printed versions, the User's Guide and Documentation Manuals are
provided in computer-readable form (bit-mapped image format) on the CD-ROMs.
Reprints of the Primary References, including published journal articles, if applicable, are
provided separately from the Documentation Manual as scanned image files on the CD-
ROM. Reprints are assembled from available reports and publications, with permission
from the authors and publishers. Only materials that are directly relevant to
documenting the data-sets are reproduced, (see User's Guide).
The user should be aware that documentation provided with the source data (i.e., the
data-set received for use in this project), and reproduced in the Reprints, may contain
references to other formats and media, such as tape formats, which are not relevant to
this version of the data-set. In all cases, the user should refer to the formatted Data-set
Description and Data File Description sections for each data-set of the Documentation
Manual (at the beginning of each data-set chapter), and the Database Structure section of
the User's Guide, for information on data structure and format.
The quality of reproduction of the scanned articles cannot match that of the rest of the
manual. The on-line (digital) scanned images are scaled at a low resolution for
convenient screen display, and are not intended for duplication in printed form. Higher
resolution scanned images are provided for those pages that may be hard to read due to
small print or a poor quality original (see the Access and Exploration section in the
User's Guide for software instructions).
Finally there is also an IDRIX Technical Reference Manual that accompanies the
distribution software developed by Clark University. The IDRIX software provides basic
access and exploration capabilities with the database using GIS structures and concepts,
and serves as a link with the broader GIS and Global Change community. The IDRIX
manual is provided in bit-mapped image format (in addition to if s printed form) on the
software floppy disk. It provides detailed descriptions of the software functions and
GED1.0 Documentation Manual Introduction
1
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operations available in IDRIX, many of which are extracts from IDRISI.
This database is meant to evolve with the help of its users. Thus, it is important that we
obtain feedback for the next revision. Response forms are provided separately for this
purpose. Information about user requirements for data of unknown availability may
factor into future data development or acquisition plans. An application form is
available for those who wish to be reviewers for the database during the lifetime of the
project (through 1995). Selection is based on representing an overall balance of
disciplines and applications, as well as prominence in global change research. Reviewers
receive all project materials and updates at no cost, and review comments are
summarized in the User's Guide. The number of reviewers will be limited to
approximately 100 for each year's review cycle.
The price of this database, as distributed from NGDC, is determined by U.S. Government
policy and requirements for cost recovery. Some organizations may qualify for no-cost
distribution. Also, NGDC maintains a policy of data exchange, whereby no-cost
distribution may be approved in exchange for useful data contributions or other
collaborative agreements. All data and materials (with the exception of scanned journal
articles and third-party software) are in the public domain, in accordance with
government policy.
GED 1.0 Documentation Manual Introduction
2
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DOCUMENTATION TEMPLATE DEFINITIONS
DATA-SET DESCRIPTION
Each data-set has its own chapter in the documentation. These chapters include relevant
information provided by the contributor or other information sources. At the beginning
of each chapter there is a structured Data-Set Description that provides a Data-Set Name,
and summary information about the Source, Original Design, Integrated Data-Set,
Primary References, and Additional References; and lists of the Data-Set Files, Reprint
Files, and Source File Examples (if provided), for each data-set, exactly as the files
appear on the CD-ROM. The purpose of this section is to describe everything that
comprises the complete data-set as provided here, including key documentation
references; and to give technical and statistical information about the data structure.
The information categories in the DATA-SET DESCRIPTIONS are defined as follows:
Data-Set Name: Name of the data-set as provided and documented in the
GED. The same name appears in the Table of Contents and
data-set chapter title, although preceded by the Principal
Investigator and Analyst (if appropriate). The format of the
chapter titles is {PI} and {data-set name} in italics, preceded
by the analysts' names, if the data have been significantly re-
worked.
Principal Investigators): The principal scientist(s) responsible for the actual numerical
or classed data values represented in the data-set, and/or the
principal institution, if relevant
SOURCE
This section refers to the source data-set acquired for this project, documentation
references, and the full lineage prior to integration into the GED. This information clearly
identifies the version of the data used and gives proper citation of the actual numerical
data (regardless of format, media, etc.) and its principal investigators.
Source Data Citation: Citation of the particular data-set used as a source in the
GED. This is not a literature reference, but a citation of the
source version of the digital data-set. The format of this
citation is: {Principal Investigator}. {Availability date}.
{Data-set description or name, including geographic and
temporal coverage}. {"Digital" or "Analog"} {type, e.g.,
"Raster," "Vector," "Map," etc.} Data on a {cell size, if
standard} {projection, e.g., "Geographic (lat/long)"} {grid
dimension} grid. {City, State}: {Institution /publisher},
{number of files} on {media}, {size}. For example:
NCDC Satellite Data Services Division. 1985-1988.
GED 1.0 Documentation Manual Documentation Template Definitions
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Weekly Plate Carre6 (uncalibrated) Global Vegetation
Index Product from NOAA-9 (APR 1985 - DEC 1988).
Digital Raster Data on a Geographic (lat/long)
904x2500 grid. Washington IX: NOAA National
Climatic Data Center. 199 files on five 9-track tapes,
425MB.
Contributor(s): Person(s) or institution responsible for disposition of the data,
and for releasing the data into the public domain. In most
cases this will be the PI, however in some cases data have
corporate or institutional ownership prior to release, or are
released through an indirect route. This field also provides
contact information, if available.
Distributor(s): Data or research center(s) with official responsibility for
distributing earlier versions of the data-set, up to and
including the source used for the GED. To work
cooperatively with other distribution centers, NGDC will
refer requests for source data to these official distribution
points. Information for each of the institution abbreviations
referenced in this field follows this section.
The approximate date(s) of the project (digitizing work)
creating the data-set represented in the current release. This
will precede the publication date and may be later than the
period of the data. Also notes continuing projects.
Chronological list of the previous versions of the data-set
from the original data up to the source version used for the
GED (i.e., does not include integration into the GED, which is
described in the next section). Sufficient information should
be given to identify the previous versions and their source.
Vintage:
Lineage:
ORIGINAL DESIGN
This section refers to the nature of the data before integration into the global database
structure. This is important information when considering the reliability and potential
application of the data-set to new problems, perhaps not foreseen by the original
investigators. It is also useful for those who wish to track back to the original data for
quality control or verification purposes, or to compare with the integrated form of the
data, which may bear changes that are important for a given application.
Variables: The specific environmental/thematic measurements included
in the data-set, the units used, and the numerical or Ham
precision (class precision is a qualitative or descriptive
indicator, e.g., "species", "major types", "primary/secondary
classes", etc)
GED 1.0 Documentation Manual Documentation Template Definitions
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Origin:
Description of instrument, data sources, and/or method of
original investigation or observation.
Geographic Reference:
Geographic Coverage:
Geographic Sampling:
Time Period:
Temporal Sampling:
The coordinate system or projection, and projection
parameters (i.e., grid orientation, origin, central meridian,
zone, etc.), for the original data-set.
The geographical limits covered by the data-set.
The original spatial interval or sampling resolution of the
data, the type of spatial object, and the numerical statistic
(i.e. Vector point, line, or polygon unit with various
attributes; or Grid point sample, cell average, mode, etc.).
The time period represented in the data-set. In the case of
time series, this indicates the beginning and ending of the
data series. In the case of long-term averages, this field
indicates the period from which data were combined.
The original time interval or sampling resolution of the data
and the type of statistic (i.e. discrete sample, peak values,
running average, typical or average period, etc.).
INTEGRATED DATA-SET
This section describes the integrated version of the data-set, as provided by this project
on CD-ROM. While every attempt has been made to preserve the full content and
nature of the original data, some alterations may have been necessary to achieve a
common structure and geographic registration. For raster data, this may involve
interpolation to one of the conventional "nested" grids, or various forms of re-registration
of the grid, or perhaps both. To aid in assessing the appropriateness or accuracy of
interpolation methods, all interpolated data-sets have corresponding examples of the
original form of the data in the SOURCE directory. The original grid representation is
clearly documented in the preceding section (Original Design), and interpolation
methods are indicated in this section (Data Integration). The user must understand that
values represented on a new grid still retain the statistical meaning from their original
grid. The information provided here is thus important for proper interpretation and use
of the data-sets.
Data-Set Citation: The recommended way of referring to the integrated data-set
as published in the GED. This is not a literature reference,
but a unique citation for the digital data-set that distinguishes
it from other versions, including the source. The format is:
{Principal Investigator}, {current publication date}, {data-set
name, including geographic and temporal coverage}. "Digital
{type, e.g., "Raster," or "Vector"} Data on a {cell size, if
standard} {projection, e.g., "Geographic (lat/long)M} {grid
GED 1.0 Documentation Manual Documentation Template Definitions
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Analyst(s):
Projection:
Spatial Representation:
dimension} grid. In: Global Ecosystems Database Version 1.0:
Disc {disc number}, Boulder CO NOAA National Geophysical
Data Center, {number of independent spatial layers and
attributes} on {media}, {size}, [first published in ...] For
example:
NGDC. 1992. Monthly Generalized Global Vegetation
Index from NESDIS NOAA-9 weekly GVI Data (APR
1985 - DEC 1988). Digital Raster Data on a 10-minute
Geographic (lat/long) 1080x2160 grid. In: Global
Ecosystems Database Version 1.0: Disc A. Boulder, CO:
NOAA National Geophysical Data Center. 45
independent and 24 derived single-attribute spatial
layers on CD-ROM. 190MB. [first published in 1989]
Individual(s) responsible for the data processing and
integration methods resulting in the integrated form of the
data-set provided here.
The coordinate system or projection, and projection
parameters (i.e., grid orientation, origin, central meridian,
zone, etc.), for the integrated data-set.
The spatial interval (between grid or vector values) and other
spatial characteristics of the integrated version of the data-set,
including the type of spatial object, and the numerical statistic
(i.e. vector point, line, or polygon unit with various attributes;
or Grid point sample, cell average, mode, etc.). This may
differ from the original sampling design due to registration
differences or aggregation from finer resolution into a
standard grid dimension. If re-sampling was performed, this
field indicates the method used.
Temporal Representation: The time step and other temporal characteristics of the
integrated version of the data-set. This may differ from the
original sampling design due to phase differences or
aggregation from finer intervals into standard time sequences.
If temporal re-sampling was performed, this field indicates
the method used.
Data Representation: The form of representing the data values in the integrated
data-set, including any numerical type conversion or re-
classification that was performed. Usually this will involve
only type conversions, although occasionally actual numerical
changes may have been necessary. The units and precision
are also indicated (e.g., "Real numbers expressed to .001
inches/month," or "Byte integers representing units of 0.1
degree," or "Two-byte integers representing units of meters
above sea-level, rounded to the nearest 30 meters").
GED 1.0 Documentation Manual Documentation Template Definitions
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Layers and Attributes: Spatial Layers and Attributes. The number of geographically
different data layers (i.e., independently distributed spatial
data layers) represented, and the number of associated
attributes, regardless of file structure. For example, multiple
data mapped on political units may in reality have only one
geographic distribution but many attributes.
Compressed Data Volume: The volume in bytes of a compressed version of the data files.
This gives a more accurate estimate of scientific information
content than actual file sizes that are format dependent and
may reflect inefficient storage methods for the sake of access.
The volume estimate is obtained using PKZIP (option -es),
Version 1.1, a commonly available data compression
program.
PRIMARY REFERENCES
This section lists references that are intended to be the primary literature reference for
documentation of the data-set. These may include unpublished documents and
published articles. The references may be divided into sub-categories relating to the
various data-set elements. One of the goals of this compilation is to provide reprints of
all Primary References in addition to this manual. Due to availability and copyright
restrictions, however, some documents may not have been available at the time of
publication. Articles that are labeled with an asterisk (*) are reproduced as scanned
image-files (in PCX format) on the CD-ROM.
[sub-categories] The primary published or unpublished documents)
associated with the production or release of the data. If a
literature publication, the article is one that was intended as
documentation, and which may or may not describe related
research. A copy of the primary reference is provided with
this manual. Published articles are provided in scanned (bit-
mapped) digital image format, to ensure accurate
reproduction.
ADDITIONAL REFERENCES
This section lists key references to the nature and/or application of the database, or other
information that may be especially useful to the user. The references may be divided
into sub-categories relating to the various data-set elements.
[sub-categories] References to key publications that are relevant to the nature
or use of the data-set.
GED 1.0 Documentation Manual Documentation Template Definitions
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DATA-SET FILES
This section lists the location, names, number, and sizes of all the digital files that
comprise the complete data-set, as provided on the CD-ROM. This information is
divided into the following file categories:
REPRINT FILES
A complete listing of all bit-mapped (scanned) image files of previously published
documentation articles. These files are provided in PCX format for users who have
appropriate software to display them. They are the full-resolution digital versions of the
documentation articles that appear in the individual Data-Set chapters in the printed and
digital versions of the Documentation Manual Bach file contains one page of the scanned
article.
SOURCE EXAMPLE FILES
Listing of all source data files provided as examples for comparison and experimentation.
Some data-sets required changes, such as re-gridding, to fully integrate them with the
database. Although the integration methods are described, these example source files
can be used to verify the results, or to test other methods. The location, names, number.
and sizes of all files is given.
DATA FILE DESCRIPTION
The Data File Description section refers to the actual data files (after processing) that are
included in the database, providing technical information contained in the ASCII header
files stored under the META sub-directory on the CD-ROM. Each element of the
database (i.e., unique spatial-temporal variable or theme) contains data file-pairs, or a
series of file-pairs, each consisting of a spatial data file and its corresponding header file.
For Raster (i.e., 'image') data, these have the file extensions MMG" and ".DOC"
respectively. Vector data and header file extensions are ".VEC" and ".DVC" respectively.
A data element may include Attribute data for re-classing or re-labeling the data file.
Attribute data files and their corresponding header file extensions are ".VAL" and ".DVL"
respectively. A data element may also contain color palette (".PAL") files, and time-series
(".TS") files.
Version 1.0 of the database employs the Idrisi 4.0 file structure that was jointly developed
GED 1.0 Documentation Manual Documentation Template Definitions 8
Spatial Data:
Attribute Data:
Headers:
Palettes:
Time Series:
Disk Volume:
spatially distributed data files (MMG and *.VEC)
tabular ("values") files (*.VAL) '
ascii header ("document") files (*.DOC, *.DVC, and *.DVL)
Color palette assignment files (\PAL)
Time series files (MS)
Total size of all data-set files on disk, in bytes.
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with Clark University (described in section IV of the User's Guide, in the section titled
Database Structure). Other formats can be produced from these files using the
accompanying conversion software or user-developed programs.
The file descriptions are organized as indicated below. To avoid redundancy in the file
descriptions, only the first header of a series is shown, followed by a table of "series
parameters" that show only what changes through the series.
DATA ELEMENT: The variable or theiiie represented in this part of the data-set,
and the units used.
STRUCTURE: Raster or Vector topology (e.g., nested grid-cell or grid-point,
arc/node vector-line, etc.)
SERIES: Number and type of data series (e.g., "45 month time-series",
etc.)
SPATIAL DATA FILES: Description of the raster or vector data files, as provided in
the raster or vector header file, or first header file from a
series, exactly as it appears in the MET A directory on the CD-
ROM, including legends. If a series, the header file example
will be followed by a table of Series Parameters, showing all
parameters that change in the multiple header files of a data
file series (e.g., titles, min/max values, etc.).
ATTRIBUTE DATA FILES: Description of attribute data files, as provided in the
header file associated with an attribute (i.e., tabular
'values') file, as represented on the CD-ROM,
including legends. As above, multiple files may be
represented with a table showing only those
parameters that are different from the example file.
NOTES: Any notes or additional information for the data element, for
example notes about any color "palette" files or time-series
files included with the data-set
DATA INTEGRATION AND QUALITY
This section provides a narrative description of methods and significant procedures used
in the integration process, such as re-gridding, re-projecting, registration changes,
temporal compositing, etc. In general, as little change as possible is made from the
original data; however, to achieve comparable data structures from source data with
unstandardized formats, changes are necessary for some data-sets. The philosophy of
long-term development, as conventions become established, is that major changes should
be performed by the original investigators, if possible. This section also includes any
information on data quality issues as a result of quality assessment work.
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DEFINITION OF TERMS
Accuracy
Attribute
Attribute Layer
Bit
Byte
Cell
Characterization
Database
Data Layer
The difference between an indicated value and its true value in
nature. In practice, accuracy must be estimated through some
empirical method; however, it is poorly known for most of the
global data-sets. Accuracy should not be confused with precision,
which may far exceed accuracy in many cases.
Used here to denote a numerical or descriptive variable used to re-
classify or label the geographical objects in an existing spatial data
layer. Attributes can be linked to spatial objects in either raster or
vector data structures, using a value or a record number in the
spatial data layer as the unique link.
The portion of a data-set that represents a geographically dependent
data layer, as would be produced by assigning new attributes to
their corresponding spatial layer. For reasons of convenience in
implementing and using the database, attribute layers may be stored
as spatial data files (e.g., raster data files) rather than as attribute
values files. Nevertheless, the data-set description will refer to
independent spatial layers and dependent attributes for the purposes
of documentation.
Refers to a "binary digit", stored as a 0 or 1 in a computer data file.
A sequence of 8 bits, which are read as a unit.
Used synonymously with "pixel" and "raster" to denote the spatial
unit of assigned values in a regularly spaced (systematic) spatial
grid. See "Raster."
Used to denote the process of data integration, derivation, and
synthesis with appropriate statistical design, for the purpose of
constructing numerical descriptions of environmental or ecological
factors that have been identified as key variables for modeling. The
database and software system that provides these capabilities may
be referred to as an "adaptive characterization database." (See
Appendix A of the User's Guide)
Used here to denote an integrated assemblage of data-sets, in a
common structure and format which can be uniformly accessed by a
single system, and which employs common conventions for
interpreting geographic objects and data values.
Used here to denote spatially distributed digital (computer) data
representing uniquely defined geographical features (i.e.,
geographical objects), or a continuous distribution (such as a
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Data-set
Element
temperature field) in either raster or vector form as commonly
implemented in Geographic Information Systems. GIS layers may
be geographically independent, or may represent various attribute
assignments on a fixed spatial distribution. For documentation
purposes, this term is divided into independent and dependent
layers by the terms 'Spatial Layer/ and 'Attribute Layer/
respectively.
Used here to denote a single compilation of data by a given
Principal Investigator or Institution, usually as a definable project,
program, or research output. A data-set may contain many
variables, and may extend ova: may years, but it is defined by
theme and investigator.
Data-set Element refers to a portion of a data-set that has a uniquely
defined spatial-temporal theme. For example, a data-set dement of
the monthly GVI data may contain 45 spatial arrays (and header
files) representing one variable over time, whereas a vector polygon
file (a single spatial distribution) and its corresponding attribute
table containing many variables, may also be a single data-set
element.
Geographic
Grid
Gridding
Interpolation
Lat/Long
Aside from the common usage, 'Geographic' is also the specific
name for the Latitude/Longitude coordinate system (i.e., map
projection), sometimes referred to as 'unprojected.' It is also the
same as plate carrel, although plate carre6 may be used to refer to a
specific grid.
Used to denote the entire assemblage of raster/cell/pixel values
within a data-set. The "edges" of the grid correspond to the edges
of the outermost cells.
Used to denote the process of producing a uniform raster "grid"
from another grid or randomly spaced distribution using
appropriate interpolation methods (see interpolation).
A process of deriving an estimated value from surrounding known
or indicated values that are at a different spatial or temporal
location. Many interpolation methods exist, including multi-
directional linear and other forms of averaging, various
mathematical curve fitting, statistical surfaces, etc. The appropriate
method of interpolation must be determined for each data-set and
application, considering experimental design.
A Latitude/Longitude coordinate system, or 'projection,' defined in
degrees, minutes, and seconds of arc along polar meridians of
longitude and equatorial parallels of latitude. Latitude increments
are equi-dlstance intervals (1 minute of latitude = 1 nautical mile),
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whereas the true distance between longitude meridians varies from
equator to pole due to the convergence of the meridians at the pole.
Layer
Line
Map
Modeling
Nested Grid
Pixel
Plate Carrel
Point
Polygon
(1) A logical separation of map information according to theme.
See 'Data Layer/ (2) Used in context most often to refer to 'Spatial
Data Layer," in contrast to 'Attributes' or 'Attribute Data Layers.'
Used here to denote a series of points theoretically connected by the
spatial vectors between them, and stored in a vector data structure.
Commonly used to refer to a hand-drawn or printed geographical
display, but also used to refer to a GIS data layer and digital
cartographic files. Because of its varied meanings, which go beyond
simple data representation, the term is avoided here, using instead
the term "Data layer" to refer to the digital 'maps' in the database.
See appendix A of the User's Guide.
A convention adopted for this project whereby all raster data are
represented on grids that are commonly edge-matched and are
integer multiples of each other. This convention allows the
following raster cell sizes in a latitude/longitude coordinate system:
2-degree, 1-degree, .5-degree, 10-minute, 5-minute, 1-minute, 30-
second.
Used synonymously with "cell" and "raster" to denote the spatial
unit of assigned values in a regularly spaced (systematic) spatial
grid. See "Raster."
A map projection in Latitude/Longitude (i.e., 'Geographic')
coordinates. Sometimes used to refer to a specific grid (as in the
case of the NOAA GVI source data).
Used here to denote a data value located by geographic coordinates
and stored in a vector data structure.
Used here to denote a series of points theoretically connected by the
spatial vectors between them, and enclosing a single geographic
region that is labeled with a data value and may also be linked by
that value to a table of other "attribute" values.
Precision
Usage in this document is "numerical" precision as opposed to
"experimental" precision. It is the degree of significance to which
numerical values are expressed in the data-set, and is contrasted
with accuracy. In reference to class definitions, it is taken to mean
the level of detail to which classes are divided (in qualitative terms),
e.g., species, communities, major ecosystems, etc. It is reported as
the smallest significant unit expressed in the actual numerical or
GED 1.0 Documentation Manual Definition of Terms
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class values of the data-set. "Experimental" precision, on the other
hand, would be the expressed as the standard deviation of a set of
measurements taken during the original data collection experiment
(generally not well documented for most data-sets). Without better
documentation, one must assume that the numerical precision
chosen by the original investigator in some way represents the,
experimental precision, but often this is not the case.
Quality Assessment This term is used to refer to specific tests performed on the data-sets
in the project, to determine their quality. It is part of Quality
Assurance plan (see User's Guide for definitions). It is distinguished
from Quality Control (see User's Guide for definition) because it is a
parallel activity to the core work of integrating existing data-sets.
Results of quality assessment on specific data-sets is reported in the
DATA INTEGRATION AND QUALITY section of the data-set
documentation chapter, to the extent that information is available.
In addition to results of studies within the project itself, significant
information from users and reviewers may also be included.
Raster Used synonymously with "pixel" and "cell" to denote the spatial unit
of assigned values in a regularly spaced (systematic) spatial grid. A
Raster data structure may also be used to represent regularly spaced
point values, in which case it is assumed that the points are located
at the centroid of the raster cell.
Spatial Layer Also, 'Spatial Data Layer.' Used here to refer to the portion of a
data-set that represents an independent spatial distribution of data.
For example, remote-sensing images will contain independently
distributed data by their nature, whereas a classified raster or vector
array may be accompanied with multiple class definitions (attributes
values) for a single distribution of geographical objects (e.g., as in
choropleth mapping with multiple attributes). Note that when used
in the restrictive sense of independent data layers, this refers to the
character of the data, not necessarily the way files are actually
organized.
Spatial Data File Used here to refer to a numerical (computer) data file that contains
spatially distributed data in the documented GED data structure.
These are not necessarily geographically independent data layers,
but refer to data files as specifically stored in the database (in some
cases multiple attributes may be stored as multiple spatial data files
for convenience only, even though they are merely re-classifications
of a single spatial layer).
Resolution Used to denote the instrumental resolution, or actual sample spacing
of a data-set. The term resolution is potentially confused with
"ground resolution," which is the minimum size of a spatially
isolated object that can be accurately resolved in a given data-set
GED 1.0 Documentation Manual Definition of Terms
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(generally 3 to 4 pixels in a satellite image). Another kind of
resolution can be described as "detectibility" or "acuity/ for example
the ability to detect a road or high emission rate in a satellite image
can sometimes be at a sub-pixel level, owing to spatial association or
anomalously high signal strength.
Vector Used to denote a spatial object type that is commonly defined in
Geographic Information Systems to include point locations, lines
represented by a series of points connected by the vectors between
them, and the perimeter of areas, also represented by a series of
points connected by their spatial vectors. Vector data may also
include topological assumptions about the relationship between
various spatial objects. It is common to associate a vector data layer
with multiple attributes (values and descriptors) in a separate
attribute file. Combined vector types such as "arc-node," where line
or polygon data are combined with intersection, or "node" points,
are also common because of their topological usefulness.
GED1.0 Documentation Manual Definition of Terms
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ABBREVIATIONS AND ACRONYMS
DATA CENTERS
The following abbreviations are used in this volume to identify centers from which
source data may be obtained. These abbreviations are defined below:
CDIAC Carbon Dioxide Information Analysis Center
Oak Ridge National Laboratory
P.O. Box 2008
Oak Ridge, TN 37831-6335, USA
EDC EROS Data Center
US Geological Survey
Sioux Falls, South Dakota 57198, USA
GISS Goddard Institute of Space Studies
NASA Goddard Space Flight Center
2880 Broadway
New York, NY 10025, USA
GRID/Geneva Global Resource Information Database
Global Environment Monitoring System
United Nations Environment Program
6 Rue de la Gabelle
CH-1227 Carouge, Switzerland
GRID/Nairobi Global Resource Information Database
Global Environment Monitoring System
United Nations Environment Program
P.O. Box 30552
Nairobi, Kenya
IIASA International Institute for Applied Systems Analysis
A-2361 Laxenburg, Austria
NCAR National Center for Atmospheric Research
P.O. Box 3000
Boulder, Colorado 80307, USA
NCDC National Climatic Data Center/NESDIS
National Oceanic and Atmospheric Administration
Federal Building
Asheville, NC 28801, USA
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NGDC National Geophysical Data Center
National Oceanic and Atmospheric Administration
325 Broadway E/GC
Boulder, Colorado 80303, USA
RIVM Rljksinstituut voor Vouksgezondheid en Milieuhygiene
National Institute of Public Health and Environmental Protection
P.O. Box 1
3720 Bilthoven, The Netherlands
SD5D Satellite Data Services Division,
National Climatic Data Center/NESDIS
National Oceanic and Atmospheric Administration
Code E/CC6
Washington, DC 20233, USA
WDC World Data Centers
International Council of Scientific Unions
(see associated national data centers)
For information, contact:
Chairman, ICSU Panel on World Data Centers
University Corporation for Atmospheric Research
P.O. Box 3000
Boulder, CO 80307-3000, USA
OTHER ACRONYMS
CIA
DMA
ESRI
FAO
NESDIS
NOAA
UNEP
UNESCO
USAF
USN/FNOC
USNOO
Central Intelligence Agency, USA
Defense Mapping Agency, USA
Environmental Systems Research Institute, Inc., Redlands, California, USA
United Nations Food and Agriculture Organization
National Environmental Satellite Data and Information Service, USA
National Oceanic and Atmospheric Administration, USA
United Nations Environment Programme
United Nations Education Scientific and Cultural Organization
United States Air Force
United States Navy, Fleet Numeric Oceanographic Center
United States Naval Oceanographic Office
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A01
NGDC Monthly Generalized Global Vegetation Index from
NESDIS NOAA-9 Weekly GVT Data (APR 1985-DEC1988)
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A01
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DATA-SET DESCRIPTION
DATA-SET NAME: Monthly Generalized Global Vegetation Index from
NESDIS NOAA-9 Weekly GVI Data (April 1985 -
December 1988)
PRINCIPAL INVESTIGATORS): NOAA National Environmental
Satellite, Data, and Information
Service (NESDIS)
SOURCE
SOURCE DATA CITATION: NCDC Satellite Data Services Division. 1985-1988.
Weekly Plate Carre6 (uncalibrated) Global Vegetation Index Product from NOAA-
9 (APR 1985 - DEC 1988). Digital Raster Data on a Geographic (lat/long)
904x2500 grid. Washington DC: NOAA National Climatic Data Center. 199 files
on five 9-track tapes, 425MB.
CONTRIBUTORS):
National Climatic Data Center (NCDC)
Satellite Data Services Division (SDSD)
National Environmental Satellite, Data, and Information Service
SDSD, World Weather Building, Rm. 100
Washington, DC 20233, USA
(301) 763-8400
DISTRIBUTORS): SDSD (see Data Center Codes for address)
VINTAGE: 1985-1988 (switched to NOAA-11 in 1989, continuous operational products)
LINEAGE:
(1) NOAA-9 Satellite, AVHRR sensor array and on-board storage
(2) Global Plate Carreg weekly GVI product
NOAA/NESDIS/NCDC Satellite Data Services Division
Washington, DC
ORIGINAL DESIGN
VARIABLES: Scaled, Uncalibrated Weekly Maximum Normalized Difference Vegetation
Index (doud effects screened by 7-day maximizing procedure, but no other
corrections for atmospheric effects or pixel-to-pixel variation in look and sun
angles).
ORIGIN: NOAA-9 Polar Orbiting Satellite, Advanced Very High Resolution Radiometer
"Global Area Coverage" (AVHRR/GAC) (see Primary Documentation)
GEOGRAPHIC REFERENCE: Plate CarreS (Latitude/Longitude)
GED 1.0 Documentation Monthly Geturmliztd GVI
A01-2
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GEOGRAPHIC COVERAGE: Global
Maximum Latitude
Minimum Latitude
Maximum Longitude
Minimum Longitude
+75 degrees (N)
-55 degrees (S)
+180 degrees (E)
-180 degrees (W)
GEOGRAPHIC SAMPLING: Last ("random") element of each 4x4 array of GAC (4km)
values, mapped onto a 904x2500 Global Plate Carre6 (lat/long) grid. GAC values
are 1x4km averages (along scan-line) of sampled values within each 4x4 array of
lkm cells. Look-angle varies between pixels due to temporal compositing.
TIME PERIOD: April 1985 - December 1988
TEMPORAL SAMPLING: 7-day weekly maximum of daily values. Time of day varies
between pixels.
INTEGRATED DATA-SET
DATA-SET CITATION: NGDC. 1992. Monthly Generalized Global Vegetation Index
from NESDIS NOAA-9 Weekly GVI Data (APR 1985 - DEC 1988). Digital Raster
Data on a 10-minute Geographic (lat/long) 1080x2160 grid. In: Global Ecosystems
Database Version IX): Disc A. Boulder, CO; NOAA National Geophysical Data
Center. 45 independent and 24 derived single-attribute spatial layers on CD-ROM,
190MB.
ANALYST(s): John J. Kineman and David A. Hastings
PROJECTION: Geographic (lat/long), GED window (see User's Guide).
SPATIAL REPRESENTATION: 10-minute grid aggregating 2-4 (weekly) GVI Plate
Carre6 values (see original sampling), and interpolating from 8.6 minute to
10-minute grid cells by area-weighted average.
TEMPORAL REPRESENTATION: Monthly RMS averages of 2-4 weekly samples
DATA REPRESENTATION: Uncalibrated single-byte integer (0 to 255) values,
representing an RMS average of median weekly GVI values, with spatial
smoothing (high=>vegetation). The averaging procedure screens random "noise"
and reduces environmental and instrumental variations inherent in the GVI data.
It also provides uniform coverage (i.e., no masking), but does not eliminate
consistent environmental phenomena (such as persistent clouds).
LAYERS AND ATTRIBUTES: 45 independent and 24 derived single-attribute spatial
layers.
COMPRESSED DATA VOLUME: 47,445,363 bytes
GED IX) Documentation Momtkty Generalized GVI
A01-3
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PRIMARY REFERENCES (* reprint on CD-ROM)
GVI SOURCE DATA:
* Kidwell, K.B (ed.).1990. Global Vegetation Index User's Guide. Washington:
USDOC/NOAA National Climatic Data Center, Satellite Data Services
Division. 45p.
NOTE: This paper refers to source tapes of weekly GVI used to produce the data
represented in the GED database. It also refers to other forms of the data and
other products available from SDSD, which are not represented in the current
database. The document is reproduced in its entirety, for completeness.
PRINCIPAL COMPONENTS ANALYSIS:
* Eastman, J.R. 1992. Time series map analysis using standardized principal
components. Proceedings, ASPRS/ACSM/RT'92 Convention: Mapping and
Monitoring Global Change. Bethesda: ASPRS/ACSM.
NOTE: The examples in this paper refer to GVI data-sets for Africa that were
distributed as part of the IGBP Global Change Database Pilot Project for Africa.
These data are identical to the data described here except for their geographic
coverage.
ADDITIONAL REFERENCES
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Index (GVI) data. International Journal of Remote Sensing, 9: 1565-1572.
Smith, E.A., W.L. Crosson, HJ. Cooper and W. Heng-yi. 1990. Heat and moisture flux
modeling of the FIFE grassland canopy aided by satellite derived canopy
variables. Proceedings of the AMS Symposium on FIFE, Anaheim, CA, Feb. 7-9,1990.
154-162.
Tarpley, J. D., Schneider, S. R., and Money, R. L. 1984. Global vegetation indices from
the NOAA-7 meteorological satellite. Journal of Climate and Applied Meteorology, v.
23, pp. 491-494.
Tateishi, R., and K. Kajiwara. 1991. Land cover monitoring in Asia by NOAA GVI data.
Vol. 6, No. 4 Geocarto International, pp. 53-64.
Tateishi, R., K. Kajiwara and T. Odajima. 1991. Global land cover classification by
phenological methods using NOAA GVI data. Asian-Pacific Remote Sensing Journal.
Vol.4, No.l. pp. 41-50.
Tateishi, R. and K. Kajiwara. 1992. Global land cover monitoring by NOAA GVI data.
IGARSS'92. Houston: May 26-29.
Taylor, B.F., P.W. Dini and J.W. Kidson. 1985. Detennination of seasonal and interannual
GED 1.0 Documentation Monthly Gentrnliud GVI
A01-7
-------
variation in New Zealand pasture growth from NOAA-7 data. Remote Sensing of
Environment, 18:177-192.
Teillet, P.M., P.N. Slater, Y. Ding, R.P. Santer, R.D. Jackson, and M.S. Moran. 1990. Three
Methods for the Absolute Calibration of the NOAA AVHRR Sensors In-Flight.
Remote Sens. Environ. 31:105-120.
Thomas, G. and A. Henderson-Sdlers, 1987: Evaluation of satellite derived land cover
characteristics for global climate modelling. Climate Change, 11:313-347.
Townshend, J. R. G., Goff, T. E., and Tucker, C. J. 1985. Multitemporal dimensionality of
images of normalized difference vegetation index at continental scales. IEEE
Transactions, Geoscience and Remote Sensing, v. 23, pp. 888-895.
Townshend, J. R. G., Justice, C. O., and Kalb, V. T. 1987. Characterization and
classification of South American land cover types using satellite data. International
Journal of Remote Sensing, v. 8, pp. 1189-1207.
Townshend, J. R. G., Justice, C. O., Choudhury, B. J., Tucker, C. J., Kalb, V. T., and Goff,
T. E. 1989. A comparison of SMMR and AVHRR data for continental land cover
characterization. International Journal of Remote Sensing, v. 10, pp. 1633-1642.
Tucker, C. J., and T. A. Gatlin. 1984. Monitoring vegetation in the Nile Delta with
NOAA-6 and NOAA-7 AVHRR imagery. Photogrammetric Engineering and Remote
Sensing, 50(1), 53-61.
Tucker, C. J., Hielkema, J. U., and Roffey, j. 1985a. The potential of satellite remote
sensing of ecological conditions for survey and forecasting desert-locust activity.
International Journal of Remote Sensing, 6(1), 127-138.
Tucker, C.J., J.R.G. Townshend, and T.E. Goff. 1985. African land cover classification
using satellite data, Science, 227(4685):369-375.
Tucker, C. J., Vanpraet, C. L., Sharman., M. J., and van Ittersum, G. 1985b. Satellite
remote sensing of total herbaceous biomass production in the Senegalese Sahel:
1980-1984. Remote Sensing of Environment, 17, 233-249.
Tucker, C. J., Fung, I. Y., Keeling, C. D., and Gammon, R. H. 1986. Relationship between
atmospheric C02 variations and a satellite-derived vegetation index. Nature, v.
319, pp. 195-199.
Tueller, P.T. and S.G. Oleson. 1989. Diurnal radiance and shadow fluctuations in a cold
desert shrub plant community. Remote Sensing of Environment, 29:1-13.
Walsh, S. J. 1987. Comparison of NOAA-AVHRR data to meteorological drought indices.
Photogrammetric Engineering and Remote Sensing, 53(8), 1069-1074.Wiegand, C.
L., Gerbermann, A. Hv Gallo, K. P., Blad, B. L., and Dusek, D., 1990. Multisite
analyses of spectral-biophysical data for corn. Remote Sensing of Environment, v.
33, pp. 1-16.
Wiegand, C.L., Gerbermann, A.H., Gallo, K.P., Blad, B.L. and Dusek, D. 1990. Multisite
analyses of spectral-biophysical data for corn. Remote Sensing of Environment, v.
33, pp. 1-16.
GED 1.0 Documentation Monthly Generalized GVI
A01-8
-------
DATA-SET FILES
LOCATION
NAME
NUMBER
TODffi SQ8
Spatial Data:
\GLGEO\RASTER\
MGV8504. IMG
to
MGV8812.IMG
45
files
104,976,000
MGV0001.IMG
to
MGV0012.IMG
12
files
27,993,600
MGVC186.IMG
to
MGVC188.IMG
3
files
13,996,800
MGVC286.IMG
to
MGVC288.IMG
3
files
13,996,800
MGVC386.IMG
to
MGVC388.IMG
3
files
13,996,800
MGVC486.IMG
to
MGVC488.IMG
3
files
13,996,800
BMden i
\GLGEO\META\
MGV8504.DOC
to
MGV8812.DOC
45
files
23,091
MGV0001.DOC
to
MGV0012.DOC
12
files
7,432
MGVC186.DOC
to
MGVC188.DOC
3
files
1,494
MGVC286.DOC
to
MGVC288.DOC
3
files
1,491
MGVC386.DOC
to
MGVC388.DOC
3
files
1,491
MGVC486.DOC
to
MGVC488.DOC
3
files
1,491
Palattas t
\GLGEO\META\
MGV8.PAL
1
file
4,352
MGV4.PAL
1
file
272
MGVC8.PAL
1
file
4,352
Tina Sariaat
\GLGEO\META\
MGV.TS
1
file
411
MGV00.TS
1
file
114
Voluma on Disks
143
files
189,002,791
REPRINT FILES
LOCATION
NAME
NUMBER
tool arm
\DOCUMENT\AO1\
MGV1_01.PCX
to
MGV1_53.PCX
53
files
1,253,256
MGV1_17X.PCX
1
files
93,708
MGV2_01.PCX
to
MGV2_10.PCX
10
files
517,211
MGV2_##X.PCX
5
files
778,338
Voluma on Diafct
69
files
2,642,513
SOURCE EXAMPLE FILES
LOCATION
NAME
NUMBER
TOOL SDTC
Spatial Data:
\SOURCE\RASTER\
GVI8827.IMG
to
GVI8831. IMG
5
files
11,300,000
Headers:
\SOURCE\META\
GVI8827.DOC
to
GVI8831.DOC
5
files
2,593
Voluma on Disk:
10
files
11,302,593
GED 1.0 Documentation Monthly Generalized GVI A01-9
-------
FILE DESCRIPTION
DATA ELEMENT: Monthly Generalized GVI (April 1985 - Dec. 1988)
STRUCTURE: Raster Data Files: 10-minute 1080x2160 GED grid (see User's Guide)
SERIES: 45 month time-series
SPATIAL DATA HUES:
MGV8504.DOC
file title
April 1985 Generalized Global Vegetation Index
data type
byte
file type
binary
columns
2160
rows
1080
ref. system
lat/long
ref. units
deg
unit dist.
1.0000000
min. X
-180.0000000
max. x
180.0000000
min. Y
-90.0000000
max. Y
90.0000000
pos'n error
unknown
resolution
0.1666667
min. value
0
max. value
192
value units
uncalibrated
value error
unknown
flag value
none
flag def'n
none
legend cats
0
File Series Parameters:
File
Month
Year
Minimum
Maximum
MGV8504
April
1985
0
192
MGV8505
May
1985
0
209
MGV8506
June
1985
0
216
MGV8507
July
1985
0
226
MGV8508
August
1985
0
209
MGV8509
September
1985
0
189
MGV8510
October
1985
0
197
MGV8511
November
1985
0
197
MGV8512
December
1985
0
195
MGV8601
January
1986
0
190
MGV8602
February
1986
0
191
MGV8603
March
1986
0
194
MGV8604
April
1986
0
178
MGV8605
May
1986
0
203
MGV8606
June
1986
0
219
MGV8607
July
1986
0
211
MGV8608
August
1986
0
205
MGV8609
September
1986
0
201
MGV8610
October
1986
0
194
MGV8611
November
1986
0
197
GED 1.0 Documentation Mtmfkb/ GmmMud cvI
A01-10
-------
MGV8612
December
1986
0
195
MGV8701
January
1987
0
189
MGV8702
February
1987
0
200
MGV8703
March
1987
0
180
MGV8704
April
1987
0
184
MGV8705
May
1987
0
205
MGV8706
June
1987
0
211
MGV8707
July
1987
0
211
MGV8708
August
1987
0
200
MGV8709
September
1987
0
184
MGV8710
October
1987
0
181
MGV8711
November
1987
0
194
MGV8712
December
1987
0
191
MGV8801
January
1988
0
196
MGV8802
February
1988
0
200
MGV8803
March
1988
0
184
MGV8804
April
1988
0
187
MGV8805
May
1988
0
190
MGV8806
June
1988
0
211
MGV8807
July
1988
0
215
MGV8808
August.
1988
0
189
MGV8809
September
1988
0
174
MGV8810
October
1988
0
166
MGV8811
November
1988
0
213
MGV8812
December
1988
0
218
NOTES:
1. Color palette files are provided for display only. Color assignments are arbitrary.
2. The time-series file (MGV.TS) contains a list of the 45 files for sequential display.
3. See comments in the DATA INTEGRATION section about calibration, variability
due to orbital wander, and effects of long-term sensor drift.
GED1.0 Documentation Monthly Generalized GV7
A01-11
-------
DATA ELEMENT: Characteristic Month Averages from the Monthly
Generalized GVI (1986-1988)
STRUCTURE: Raster Data Files: 10 minute 1080x2160 GED grid (see User's Guide)
SERIES: 12 characteristic month time-series
SPATIAL DATA FILES:
MGV0001.DOC
file title
Average January Generalized Global Vegetation Index
data type
byte
file type
binary
columns
2160
rows
1080
ref. system
lat/long
ref. units
deg
unit dist.
1.0000000
min. X
-180.0000000
max. X
180.0000000
min. Y
-90.0000000
max. Y
90.0000000
pos'n error
unknown
resolution
0.1666667
min. value
0
max. value
183
value units
uncalibrated
value error
unknown
flag value
none
flag def'n
none
legend cats
0
lineage
Produced from the following 3 files:
lineage
GVI8601.IMG, GVI8701.IMG, GVI8801.IMG
File Series Parameters:
File
Characteristic Month
Minimum
Maximum
MGV0001
January
0
183
MGV0002
February
0
184
MGV0003
March
0
172
MGV0004
April
0
176
MGV0005
May
0
199
MGV0006
June
0
207
MGV0007
July
0
211
MGV0008
August
0
188
MGV0009
September
0
177
MGV0010
October
0
171
MGV0011
November
0
193
MGV0012
December
0
193
NOTES:
1. Produced by taking the mean of three years for each month
GED 1.0 Documentation Monthly Generalized GVI
A01-12
-------
DATA ELEMENT: Annual Principal Components of the Monthly
Generalized GVI for 1986,1987, and 1988
STRUCTURE: Raster Data Files: 10 minute 1080x2160 GED grid (see User's Guide)
SERIES: 3 year time-series, series of 4 Principal Components for each year
SPATIAL DATA FILES:
MGVC186.DOC
file title
1986 MGV PCA Component 1
data type
integer
file type
binary
columns
2160
rows
1080
ref. system
lat/lon
ref. units
deg
unit dist.
1.0000000
min. X
-180.0000000
max. X
180.0000000
min. Y
-90.0000000
max. Y
90.0000000
pos'n error
unknown
resolution
0.1666667
min. value
-331
max. value
1341
value units
uncalibrated
value error
unknown
flag value
none
flag def'n
none
legend cats
0
File Series Parameters:
File
Comoonent
Year
Minimum
Maximu
MGVC186
1
1986
-331
1341
MGVC187
1
1987
-495
1404
MGVC188
1
1988
-589
1363
MGVC2 86
2
1986
-591
554
MGVC287
2
1987
-639
618
MGVC288
2
1988
-700
669
MGVC386
3
1986
-433
345
MGVC387
3
1987
-540
414
MGVC388
3
1988
-605
663
MGVC486
4
1986
-332
400
MGVC487
4
1987
-419
458
MGVC488
4
1988
-513
360
NOTES:
1. Produced using IDRISI's Standardized Principal Components Analysis, on a circum-
global window between 55 deg. South and 75 deg. North Latitude.
GED 1.0 Documentation Monthly Generalized GVI
A01-13
-------
SOURCE EXAMPLE; NOAA/NCDC Weekly Plate CarreS Global
Vegetation Index from NOAA-9 (Samples for July
1988)
STRUCTURE: Raster Data Files: 8.6 minute Plate Carre£ 904x2500 grid (non-nested, see
User's Guide)
SERIES; 5 week time-series for July
SPATIAL DATA FILES:
GVI8827.DOC
file title
June 27 - July 3, 1988 Weekly Global Vegetation Index
data type
byte
file type
binary
columns
2500
rows
904
ref. system
lat/long
ref. units
deg
unit dist.
1.0000000
min. X
-180.0000000
max. X
180.0000000
min. Y
-55.0000000
max. Y
75.0000000
pos'n error
unknown
resolution
0.1440000
min. value
0
max. value
255
value units
uncalibrated
value error
unknown
flag value
none
flag def'n
none
legend cats
0
File Series Parameters:
File Year Week Minimum Maximum
GVI8827
1988
27
0
255
GVI8828
1988
28
0
255
GVI8829
1988
29
0
255
GVI8830
1988
30
0
255
GVI8831
1988
31
0
255
NOTES:
1. These source files show data artifacts and minor registration problems that were
removed in the monthly compositing (see Integration Methods).
GED 1.0 Documentation Monthly Generalized GVI
A01-14
-------
DATA INTEGRATION AND QUALITY
John J. Kineman and David A. Hastings
NOAA National Geophysical Data Center
Boulder, CO 80303, USA
MONTHLY GENERALIZED GLOBAL VEGETATION INDEX
(APRIL 1985 - DECEMBER 1988)
Advanced Very High Resolution Radiometer (AVHRR) data from NOAA Polar Orbiting
Environmental Satellites were obtained from the National Environmental Satellite, Data
and Information's (NESDIS) Satellite Data Services Division. The data were acquired in
NOAA's operational Normalized Difference Vegetation Index (NDVI) "Plate Carrel"
(latitude/longitude) weekly image format, and were subsequently converted at the
National Geophysical Data Center into 10-minute grids, composited monthly. This new
data-set is called the Monthly Generalized Global Vegetation Index (MG-GVI).
The AVHRR spectral bands used for vegetation monitoring are Channel I, a visible band
(0.58 to 0.68m) and Channel 2, a near infrared band (0.73 to 1.0m). Since the spectral
reflectance of vegetation is more than three times greater in the reflected infrared than in
the visible portion of the spectrum due to leaf structure and chlorophyll absorption in
the visible red (CH 1). The difference between the value for Channel 2 and Channel 1 is
an indication of the degree to which the sensor "footprint" includes green vegetation.
Various mathematical combinations of Channel 1 and 2 data have been found to be
sensitive indicators of the presence of green vegetation and are referred to as vegetation
indices. Because of the high dependence of these indices on the differential scattering and
absorption of red and nearlR bands, they are also dependent on leaf, plant, and canopy
structure to a significant degree. Stratified analysis using ancillary land-cover data
(along with other empirical calibrations) may thus improve interpretation. It is also
known that changes of local time of observation (caused by variation in the satellite
orbits), and thus solar azimuth and zenith, cause significant rn-homogeneities in the
vegetation index, which may be compounded by the weekly compositing procedure (see
literature by Gutman, and by Tateishi and Kajiwaia, in references above). This
phenomena may be somewhat reduced by the averaging process employed for these
generalized monthly images, but the resulting variability has not been quantified.
The basic index used by NOAA is the Unsealed Normalized Difference Vegetation Index
(XVI), defined by the equation:
XVI = (CH2 - Chi) / (Ch2 + Chi)
GED 1.0 Documentation Monthly Generalized GV.I
A01-15
-------
For vegetation, the NDVIs range from 0.1m to 0.6m, the higher values being associated
with greater density and greenness of the plant canopy. Atmospheric effects, such a
scattering and sub-pixel- sized clouds, all act to increase the value of Chi with respect to
Ch2 and reduce the values of the computed vegetation indices. Maximum values
compositing can thus be used as a method for cloud screening over a suitable series of
observations.
The normalized index has another advantage for global vegetation monitoring, for it
partially compensates for changing illumination conditions, surface slope, and viewing
aspect. Clouds, water, and snow have greater reflectance in the visible than in the near
infrared, so for these features NDVI values are negative. Rock and bare soil have similar
reflectances in the visible and near infrared and this results in vegetation indices near
zero.
The data provided by SDSD were scaled as integer values from 0 to 255 according to the
formula NDVI = 240-(XVI+0.05)*350 (see Global Vegetation Index User's Guide). In
processing, however, the scale was inverted by subtraction from 255, so that high values
in the data correspond more intuitively to high vegetation signals (it also avoids
mistaking it for other GVI products). Thus the values used in averaging and re-gridding
are described by the formula:
NDVI = (XVI+0.05)*350 + 15
The satellite images were re-sampled from weekly to monthly averages in a series of
steps. Two procedures were used to control the quality of these composite images. First,
registration accuracy was ensured by alignment of recognizable geographic locations.
Second, each weekly composite image was visually inspected for artifacts (i.e., scan lines,
orbital swaths, and other noise). If artifacts were visible approximately at the same
location in two or more images, only one of those images was used. The remaining
artifacts were removed during the monthly composite procedure, which combined all
weeks which overlapped the calendar month (thus providing up to one week overlap
between months). In this procedure, the high and low weekly values for a given month,
for each cell, were eliminated and a root-mean-square average of the remaining weekly
"median" cell values was calculated. This technique eliminated random artifacts evident
in the weekly data and biased the result toward higher (and presumably more reliable)
median values, without forcing the monthly value to its maximum. The images were
then re-gridded to a 10-minute grid using a spatially weighted average. The result is
therefore a statistic that is presumed to be generally representative of the month's
vegetation activity over a partially "smoothed" 10-minute pixel; however, as with any
such index, it must be calibrated or classified using additional information. The values
were not corrected for orbital parameters or sensor drift.
GED 1.0 Documentation Monthly Generalized GVI
A01-16
-------
PROCEDURE FOR DEVELOPING NVI MONTHLY COMPOSITE IMAGES:
Data Source: Weekly Composite Images of 7-day peak values on Global 8.6 minute grids
1. Process weekly images: 2500 cols, x 904 rows (covering 75°N-55°S latitude)
a. Identify images for each month
b. Visually inspect images for artifacts
c. Choose between images in the same month if artifacts overlap
d. Calculate registration offset (fractional cell offsets)
2. Produce composite monthly images: 2500 cols, x 904 rows
a. Produce root-mean-square average of selected weekly images for each
month, removing high and low values to eliminate remaining artifacts/ and
applying fractional registration offsets.
3. Re-grid to 10-minute cell size: 2160 cols, x 1080 (Covering 90°N to 90°S latitude)
a. Resample using a cell-overlap area-weighted linear average
b. Pad with zeros to the poles
CALIBRATION "DRIFT'
GVI is known to 'driff over time due to orbital changes (time of passage) and sensor
aging. Investigation of the monthly data-set over this time period shows the trend to be
increasing linearly with time in low vegetation areas, but is not so evident in the higher
vegetation signals (see above). Thus, the desert areas appear (incorrectly) to be
increasing in greenness by about 3% per year, whereas highly vegetated areas show little
overall change, or perhaps a slight decreasing trend (also an artifact of the drift). If one
considers the calibration drift characteristics of the two channels of AVHRR data used to
compute the GVI (e.g., Holben, 1990), it can be shown that the NDVI calculation results
in a logarithmic curve which, due tQ the parameters of the linear drift in each sensor, can
be closely approximated with a line. The observed drift in these monthly generalized
values (plotted over the 45-month time series as an average over Bare Desert regions
identified in the Olson data-set - see Chapter A05) agrees well with such prediction
based on Holben's calibration drift corrections. This means that empirical correction of
this drift in the GVI can be performed after production of the index as well as before,
with only a slight loss of accuracy (due to the non-linearity of the NDVI drift, which can
be shown to be negligible in this case).
Figure 1, below, shows a time profile of MG-GVI values as described above, comparing
spatial averages for the Nile Delta with those for Olson's Bare and Blowing Sand Desert.
The regression line for the nile delta is flat, whereas the long-term calibration drift is
evident in the desert curve.
Also evident in the 45-month desert profile of the MG-GVI, is an annual dip in these low
GVI values. Preliminary research (Dr. Alex Faizoun at LERTS in Toulouse, France)
indicates that this dip may be explainable by the annual cycle of atmospheric water
GED 1.0 Documentation Monthly Generalized GVI
A01-17
-------
content over desert regions, which becomes significant for low GVI values. Both phase
and amplitude seem to agree with these preliminary findings for the African Sahel.
Atmospheric water vapor may vary differently in different regions, however, and will
not have as significant an effect on higher GVI values (simply due to the signal-to-noise
ratio).
1W.12
144.23
132.34
12a 46
10e.ee
96.66
84.77
72.88
60.98
49.09
37.20
MONTHLY GENERALIZED VEGETATION INDEX
(April 1985 - December 1988)
n
11
Nile Delta
i \
< \
> \
( i
n
1 \
t )
t 1
t
t
9
%
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\
v
I
4
\
I
I
I
I
\
I
I
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%
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V
I
1
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Bare Desert
1
' » 1 V 1r 1 1 1 p" I 1 'I 1 i l l 1 I I I 1 1 1 I I' I I" T 1 I 1 1 T-,f I I | I "I | | I'l 1 I"!'!
Figure 5 45-month time profile of the Monthly Generalize Global Vegetation Index,
averaged over two areas; the Nile Delta and Bare or Blowing Sand Desert
(from Olson World Ecosystems version 1.4D)
Similar analysis performed on the Monthly Experimental GVI (ME-GVI, Chapter A02)
produced by Kevin Gallo indicates a similar drift in those data for the NOAA-9 series.
NOAA-11 data, which became operational in 1989, exhibit a different drift trend
(decreasing), which is evident in the Gallo data, even after application of pre-launch
corrections. Regression analyses between the Gallo data and the MG-GVI described here
indicate reasonable correlation (r=.89 for a sample month, July 1986), but emphasizes that
these two data-sets represent different parameters, MG-GVI being a generalized average
and ME-GVI being peak values.
GED 1.0 Documentation Monthly Generalized GVI
A01-18
-------
CHARACTERISTIC MONTH AVERAGES:
Twelve "characteristic" month data files were produced by averaging the three
generalized monthly data files from 1986,1987, and 1988. 1985 data were omitted
because it was an incomplete year of data. The resulting data files should reveal average
phenomena for the year (including calibration drift, which may be corrected empirically).
These averages are provided as a convenience to users, since they can be readily
compared to the climate data from Legates and Willmott and from Leemans and Cramer,
which are also characteristic months rather than true time series. Seasonal phenomena
should be well represented, however the user is cautioned to evaluate the effect of
known annual trends in the calibration of these data for any intended study.
Estimates from plotting profiles of various control areas indicate that a calibration "drift"
exists in the GVI data, and appears as an increasing trend throughout the time series in
low GVI regions. It is also inversely proportional to the indicated GVI (i.e., less for more
vegetated areas). This drift is primarily the result of the gradual delay in time of passage
of the satellite overhead, thus affecting the sun angle. Physical structure of the land
cover with respect to sun angle may therefore explain the greater effect at low GVI
values. The drift was found to be less than 3% of the maximum values in the data-set
per year.
The averaged data may reduce atypical cloud effects, however it will certainly
incorporate characteristic cloudiness effects in affected regions (e.g., the tropics). It is
possible that generalized data on cloudiness can be applied empirically to improve the
values in cloud-prone regions, but this idea has not been tested.
ANNUAL PRINCIPAL COMPONENTS OF THE MONTHLY
GENERALIZED GLOBAL VEGETATION INDEX FOR 1986.1987, AND
1988
Principal components analysis (PCA) was used to produce 12 derived digital data files of
the Global Vegetation Index using the NGDC monthly generalized data as inputs. The
PCA implementation in IDRISI 4.0 was used, choosing standardized variables and the
correlation matrix (IDRISI 4.0, Clark University). The results of such analysis require
interpretation, and research is being done. The technique was discussed by Eastman
(1992), who experimented with the NGDC data for the Africa continent Tateishi and
Kajiwara (1992) have also experimented with this use of PCA along with cluster analysis
to produce land-surface classifications based on GVI. Tateishi produced a data-set of
monthly-maximum calibrated GVI and land-cover classifications derived from this
technique (Odajima, Kajiware, and Tateishi, 1990). The Tateishi, Kajiware, and Odajima
data have been contributed for the Global Ecosystems Database/ Version 1.0, Disc B.
GED 1.0 Documentation Monthly Generalized GVI
A01-19
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Derived annual global raster arrays were produced as follows:
Input
Output
File Names
12 files: Jan.-Dec. 1986
12 files: Jan.-Dec. 1987
12 files: Jan.-Dec. 1988
PCA #1,2,3,4 for 1986 MGVC186, MGVC286, etc.
PCA #1,23,4 for 1987 MGVC187, MGVC386, etc.
PCA #1,23,4 for 1988 MGVC188, MGVC486, etc.
The above analysis results in principal components for each year, using 12 monthly
inputs. Because of the nature of PCA, the particular parameters selected for this analysis
(standardized components computed on the correlation matrix), and the performance of
the analysis on a full global window (excluding the "no-data" regions above 75-degrees
N. and below 55-degrees South), the resulting outputs are optimized to reveal specific
phenomena. The first component represents an axis of strongest combined GVI signal,
essentially equal to the annual average. A comparison of the first component with a 12-
month mean for 1986, re-scaled to match offset and gain, showed a maximum difference
of +/-1, probably due to rounding. In the "standardized" PCA analysis, each month's
spatial variation is given equal weight.
The next component represents an orthogonal axis, which, by definition, is the strongest
annual anomaly. Since the analysis is performed globally, the phase of this anomaly is
primarily driven by the summer/winter variation. This phase alignment is reinforced by
the seasonal polar "noise" in the GVI data that varies with the solar zenith angle and is
easily distinguished over the oceans (un-masked images were used in the analysis). The
third component, being also an orthogonal axis, becomes phased with the spring/fall
variation; and the fourth component then becomes aligned with the strongest bi-modal
variation. A discussion of these results in relation to seasonal patterns for the African
continent is given by Eastman (1992).
To the extent that the inter-annual drift effect noted above is a linear function of GVI,
without spatial significance (i.e., purely a linear offset and gain difference), it will be
removed by the PCA calculation (PCA will thus also remove any such trend that is
genuine, but this is an extremely unlikely occurrence for any natural phenomena within
a global window). The non-linear portion of the drift curve, which is probably due to
annual variation in the atmospheric water content as noted above, will affect Che PCA
calculation, showing a slight increase in the Spring-Autumn signal, i.e., component #3.
Since component #3 already isolates an annual cycle with similar phase and period to
fluctuations in atmospheric water (according to preliminary research in the Sahel region
of Africa conducted by LERTS in Toulouse, France), even this effect may be corrected
empirically.
The integer values in the PCA data files are as produced by the IDRISI software, and
have not been re-scaled for inter-annual comparison. In practice, empirical calibration
and re-scaling of these images may be necessary using suitable control areas, after which
GED 1.0 Documentation Monthly Generalized GVI A01-20
-------
inter-annual comparisons may be more meaningful, taking into account that there are
still atmospheric and cloud effects represented in the data.
COLOR PALETTES
A color palette has been developed based on intensity levels of the scaled MG-GVI.
Although such palettes are arbitrary, and do not represent detailed studies of land-cover
classifications, the NGDC palette has become popular among some users (it was used, for
example, by the IGBP, along with an annual average of the data-set, on the cover of
IGBP Report #15: Global Change System for Analysis, Research and Training (START).
Boulder, CO: UCAR Office for Interdisciplinary Earth Studies). These palettes are
provided with the database in both 4 bit-plane (16-color) and 8 bit-plane (256-color) form
(MGV4.PAL and MGV8.PAL, respectively).
These palettes also provide the capability to visually compare the MG-GVI documented
here with the Monthly Experimental GVI (ME-GVI) developed by Kevin Gallo (see
Chapter A02), since corresponding palettes were developed for the ME-GVI data, with
identical color-slicing according to the respective offset and gain characteristics. The
table below provides the color-slicing criteria for the 256-color palettes, for both data-sets.
avi
MQ-onri
ME-GVI
COLOR
RED
QREEN
BLUB
0
Blue
0
0
20
1
White
63
63
63
2
White
63
63
63
0
3
Blue
0
0
20
0
32.5
100
Brown
17
0
0
20
68
117
Yellow
63
51
0
40
104
134
Olive
20
30
0
50
122
142
Green
0
30
0
75
166
163
Br.Green
0
63
0
100
211
184
Green/White
32
63
32
255
255
White
63
63
63
The color-slicing levels and color definitions, which result from simple Red-Green-Blue
intensity levels (0-63) using IBM-PC conventions, are shown in the table above. "% GVI"
refers to the percent of the GVI range represented in the data-set, between XVI=0 (32.5 in
the MG-GVI data and 100 in the ME-GVI data) and the mean monthly maximum for
July.
The 16-color palette mimics the above color scheme, assuming a linear stretch to 16
classes from 0 to the Maximum data value in the file. Since the monthly maxima vary
between files, comparable displays require re-setting the maxima to a standard value for
the series. This will involve different procedures for each software package.
Since the Characteristic Month Averages retain similar scaling to the monthly data, the
GED 1.0 Documentation Monthly Generalized GVI
A01-21
-------
same color palettes can be used. A separate palette (MGVC8.PAL) is provided for the
principal components images, which must be re-scaled from minimum to maximum to
256 levels for display (e.g., using autoscaling during display with the provided software).
The MGV4.PAL palette may be used with the PCA images when re-scaling to 16 levels.
NOTES
1. These data are uncalibrated values, meaning that they are based on the NOAA
Weekly GVI product which used digital counts rather than albedos in the
calculation of the NDVL A new calibrated product has been introduced by
NOAA starting with NOAA-11 data (1990). Applying pre-launch calibrations and
converting to albedos should make it easier to combine data from different
sensors, but does not correct for drift problems noted above. The data in this
data-set are all from one sensor (NOAA-9), thus minimizing the importance of
calibration within the data-set. However, uncalibrated values may also be difficult
to compare with other GVI values in the research literature. Possibilities for
empirical calibration and intercomparison exist, as noted above.
2. Although averaging produces a "generalized" data-set with relatively clean,
continuous coverage that is suited for use in spatial analysis systems, it also
averages many other effects, such as persistent clouds, most notably along the
tropical coasts. Future work may include developing separate quality masks
based on cloud data.
3. The Principal Components images are provided for experimentation. Their
interpretation is a matter of research at present. Some of the un-desirable effects
of PCA analysis is avoided by working at a global scale, however users should be
aware that PCA analysis is highly sensitive to the geographic window (and scale)
of analysis.
REFERENCES
(see "Additional References," Pg. A01-3)
GED 1.0 Documentation Monthly Generalized GVI
A01-22
-------
A02
EDC-NESDIS Monthly Global Vegetation Index from
Gallo Bi-Weekly Experimental Calibrated GVI (April 1985 -
December 1990)
GED 1.0 Documentation Experimental Calibrated GVI
AQ2
-------
DATA-SET DESCRIPTION
DATA-SET NAME: Monthly Global Vegetation Index from Gallo Bi-
weekly Experimental Calibrated GVI (April 1985
- December 1990)
PRINCIPAL INVESTIGATOR(s): Kevin P. Gallo
USGS EROS Data Center and the
NOAA National Environmental
Satellite, Data, and Information
Service
SOURCE
SOURCE DATA CITATION: Gallo, Kevin P. 1992. Bi-Weekly Global Vegetation Index
computed from the NOAA weekly mercator AVHRR product with experimental
calibrations. Digital Raster Data on a Mercator 1038x2048 grid. In: Experimental
Calibrated Global Vegetation Index from NOAA AVHRR, 1985-1991. Boulder Co:
National Geophysical Data Center. 175 independent single-attribute spatial layers
on CD-ROM, 372MB.
CONTRIBUTOR(s):
Kevin P. Gallo
National Climatic Data Center (NCDC)
Satellite Data Services Division (SDSD)
National Environmental Satellite, Data, and Information Service
SDSD, World Weather Building, Rm. 100
Washington, DC 20233
(301) 763-8400
DISTRIBUTORS): (1) EDC (2) NGDC
VINTAGE: 1989-1991
LINEAGE:
(1) NOAA AVHRR weekly Mercator product (produced from Plate Carre§)
NOAA/NESDIS/NCDC/Satellite Data Services Division
Washington, DC
(2) Bi-weekly experimental calculation:
Kevin P. Gallo, NOAA/NESDIS/ORA
EROS Data Center
Sioux Falls, South Dakota
GED 1.0 Documentation Monthly Experimental Calibrated GVI
A02-2
-------
(3) Monthly composite and re-projection to lat/lon:
Douglas C. Binnie, USGS
EROS Data Center
Sioux Falls, South Dakota
ORIGINAL DESIGN
VARIABLES:
Normalized difference vegetation index
ORIGIN: AVHKR sensor on NOAA-9 and NOAA-11 satellites (see Primary
Documentation)
GEOGRAPHIC REFERENCE: Mercator
GEOGRAPHIC COVERAGE: Global
Maximum Latitude : +75 degrees (N)
Minimum Latitude -55 degrees (S)
Maximum Longitude : +180 degrees (E)
Minimum Longitude -180 degrees (W)
GEOGRAPHIC SAMPLING: Last ("random") element of each 4x4 array of GAC (4km)
values, mapped onto a 904x2500 Global Plate Carreg (lat/long) grid and
resampled to a 1038x2048 global Mercator grid. GAC values are 1x4km averages
(along scan-line) of sampled values within each 4x4 array of 1km cells. Look-
angle varies between pixels due to temporal sampling.
TIME PERIOD: April 1985 - December 1991
TEMPORAL SAMPLING: Bi-Weekly maximum of daily values (time of day varies
between pixels). Because of the bi-weekly maximizing procedure, individual
pixels in the bi-weekly image may be from different daily images; thus, look angle
and sun-angle (time of day) parameters vary considerably between pixels.
INTEGRATED DATA-SET
DATA-SET CITATION: EDC-NESDIS. 1992. Monthly Global Vegetation Index from Gallo
Bi-Weekly Experimental Calibrated GVI (April 1985 - December 1990). Digital Raster
Data on a 10-minute Geographic (lat/long) 1080x2160 grid. In: Global Ecosystems
Database Version 1.0: Disc A. Boulder, CO: NOAA National Geophysical Data
Center. 69 independent single-attribute data layers on CD-ROM, 161MB.
ANALYST(s): Douglas C. Binnie (USGS), David A. Hastings (NOAA), Jeffrey D. Colby
(NOAA)
PROJECTION: Geographic (lat/long), GED window (see User's Guide).
SPATIAL REPRESENTATION: 10-minute grid sample from a 10.5 degree (longitude)
Mercator grid.
TEMPORAL REPRESENTATION: Maximum daily value occuring in the month.
GED 1.0 Documentation Monthly Experimental Calibrated GVI
A02-3
-------
DATA REPRESENTATION: Single-byte integers scaled between 0 and 255,
representing maximum monthly calibrated Normalized Difference Vegetation
Index, with cloud and quality masking.
LAYERS AND ATTRIBUTES: 69 independent single-attribute spatial layers attributes
COMPRESSED DATA VOLUME: 27,100,227 bytes
PRIMARY REFERENCES (• reprint on CD-ROM)
* Kidweil, K.B (ed.). 1990. Global Vegetation Index User's Guide. Washington:
USDOC/NOAA National Climatic Data Center, Satellite Data Services
Division. 45p. .
NOTE: This paper refers to source tapes of weekly GVI used to produce the data
represented in the GED database. It also refers to other forms of the data and
other products available from SDSD, which are not represented in the current
database. The document is reproduced in its entirety, for completeness.
ADDITIONAL REFERENCES
See bibliography for NGDC Monthly Generalized Vegetation Index (Chapter A01)
GED 1.0 Documentation Monthly Experimental Calibrated GVI
A02-4
-------
DATA-SET FILES
LOCATION
Spatial Data:
\GLGEO\RASTER\
Headerst
\GLGEO\META\
Palettes t
\GLGEO\META\
\GLGEO\META\
Tim* Series:
\GLGEO\META\
Volume on Disk:
HMB
MEV8504.IMG to MEV9012.IMG
MEV8504.DOC to MEV8812.DOC
MEV4.PAL
MEV8.PAL
MEV.TS
MPHBBR
69 files
69 files
1 file
1 file
1 file
132 files
TOPIL scat
160,963,200
40,032
272
4,352
627
161,008,483
REPRINT FILES
(see documentation for A01: NGDC Monthly Generalized GVI)
SOURCE EXAMPLE FILES
LOCATION
Spatial Data:
\SOURCE\RASTER\
Headers:
\SOURCE\META\
Volume on Disk:
jnu
BEV8827.IMG, BEV8829.IMG
BEV8827.DOC, BEV8829.DOC
HPMBBR
2 files
2 files
4 files
TCEMi SOB
4,251,648
1,055
4,252,703
GED 1.0 Documentation AfbelMy Experimental CmMrated GVI
A02-5
-------
FILE DESCRIPTION
DATA ELEMENT: Monthly Experimental Calibrated GVI
STRUCTURE: Raster Data Files: 10-minute 1080x2160 GED grid (see User's Guide)
SERIES: none
SPATIAL DATA FILES:
MEV8504.DOC
file title
April 1985 Experimental Vegetation Index
data type
byte
file type
binary
columns
2160
rows
1080
ref. system
lat/long
ref. units
deg
unit dist.
1.0000000
min. X
-180.0000000
max. X
180.0000000
min. Y
-90.0000000
max. Y
90.0000000
pos'n error
unknown
resolution
0.1666667
min. value
0
max. value
181
value units
calibrated
value error
unknown
flag value
0
flag def'n
none
legend cats
0
comment
Data flags are 0, 1, and 2 for cloud, data drop, and solar
File Series Parameters:
File
Month
MEV8504
April
MEV8505
May
MEV8506
June
MEV8507
July
MEV8508
August
MEV8509
September
MEV8510
October
MEV8511
November
MEV8512
December
MEV8601
January
MEV8602
February
MEV8603
March
MEV8604
April
MEV8605
May
MEV8606
June
MEV8607
July
MEV8608
August
MEV8609
September
MEV8610
October
MEV8611
November
Year Minimum Maximum
1985
0
181
1985
0
184
1985
0
182
1985
0
185
1985
0
185
1985
0
193
1985
0
183
1985
0
183
1985
0
180
1986
0
180
1986
0
184
1986
0
184
1986
0
186
1986
0
187
1986
0
185
1986
0
186
1986
0
184
1986
0
185
1986
0
184
1986
0
186
GED 1.0 Documentation Monthly Experimental Calibrated GVI
A02-6
-------
MEV8612
December
MEV8701
January
MEV8702
February
MEV8703
March
MEV8704
April
MEV8705
May
MEV8706
June
MEV8707
July
MEV8708
August
MEV8709
September
MEV8710
October
MEV8711
November
MEV8712
December
MEV8801
January
MEV8802
February
MEV8803
March
MEV8804
April
MEV8805
May
MEV8806
June
MEV8807
July
MEV8808
August
MEV8809
September
MEV8810
October
MEV8811
November
MEV8812
December
MEV8901
January
MEV8902
February
MEV8903
March
MEV8904
April
MEV8905
May
MEV8906
June
MEV8907
July
MEV8908
August
MBV8909
September
MBV8910
October
MEV8911
November
MEV8912
December
MEV9001
January
MEV9002
February
MEV9003
March
MEV9004
April
MEV9005
May
MEV9006
June
MEV9007
July
MEV9008
August
MEV9009
September
MBV9010
October
MEV9011
November
MEV9012
December
NOTES:
1986 0 193
1987 0 191
1987 0 182
1987 0 182
1987 0 180
1987 0 183
1987 0 179
1987 0 184
1987 0 182
1987 0 183
1987 0 175
1987 0 174
1987 0 175
1988 0 178
1988 0 172
1988 0 177
1988 0 173
1988 0 172
1988 0 184
1988 0 179
1988 0 180
1988 0 192
1988 0 179
1988 0 184
1988 0 186
1989 0 181
1989 0 183
1989 0 185
1989 0 183
1989 0 190
1989 0 187
1989 0 184
1989 0 187
1989 0 184
1989 0 183
1989 0 182
1989 0 182
1990 0 182
1990 0 187
1990 0 178
1990 0 186
1990 0 181
1990 0 188
1990 0 186
1990 0 187
1990 0 182
1990 0 184
1990 0 184
1990 0 188
GED1.0 Documentation Monthly Experimental Calibrated GVI
A02-7
-------
SOURCE EXAMPLE: Gallo Bi-weekly (Mercator) Experimental Global
Vegetation Index from NOAA-9 and NOAA-11
(Samples: July 1988)
STRUCTURE: Raster Data Files: non-GED 1038x2048 mercator grid
SERIES: 5 week time-series for July
SPATIAL DATA FILES:
BEV8527.DOC
file title
July 4-17, 1988 Bi-weekly Experimental Vegetation Index
type
byte
file type
binary
columns
2048
rows
1038
ref. system
mercator
ref. units
deg
unit dist.
-999.0000000
min. X
-180.0000000
max. X
180.0000000
min. Y
-55.0000000
max. Y
75.0000000
pos'n error
unknown
resolution
unknown
min1. value
1
max. value
185
value units
calibrated
value error
unknown
flag value
none
flag def'n
none
legend cats
0
File Series Parameters:
File Week Year Minimum Maximum
BEV8827 July 4-17 1988 1 185
BEV8829 July 18-31 1988 1 184
NOTES:
GED 1.0 Documentation. Monthly Experimental Calibrated GV7
A02-8
-------
DATA INTEGRATION AND QUALITY
Kevin P. Gallo, NOAA/NESDIS
EROS Data Center
Sioux Falls, SD, USA
David A. Hastings and John J. Kineman, NOAA/NESDIS
National Geophysical Data Center
Boulder, CO, USA
INTRODUCTION
The experimental GVI (EGVT) contained on this CD-ROM was developed by Kevin Gallo
to investigate the benefits of using pre-launch calibration information to improve the
usefulness of the GVI. In addition, screening the data for low sun angle and clouds
makes the data more useful for some studies (though use of such masked data in spatial
analysis systems should be conducted with care).
The original NOAA operational GVI, available from the Satellite Data Services Division
(see above) have been widely accessible, and have been used by many scientists for
qualitative and semi-quantitative analysis. One of the major comments about the
operational GVI is that the lack of calibration of the data degrades the use of the GVI.
Different AVHRR instruments on different satellites have different calibration
characteristics, and these characteristics change with time.
The Gallo experimental data-set was an investigation into the use of simple pre-launch
calibration information in producing a GVI.
This data-set contains monthly maxima derived from Gallo's original biweekly
computations. The data were reprojected by the U. S. Geological Survey's Earth
Resources Observation Systems Data Center to a 10-minute latitude-longitude projection.
They were then re-registered at the NOAA National Geophysical Data Center.
/
DEVELOPMENT OF THE DATA
An experimental normalized difference vegetation index (NDVI) was developed and
produced during 1988 through 1990, from weekly visible and near-infrared AVHRR
channel data for 1985-1990, obtained from NOAA's Global Vegetation Index product
(Kidwell, 1991) distributed by the NOAA/NESDIS National Climatic Data Center
(NCDC), Satellite Data Services Division (SDSD). NOAA's Mercator-projected product
GED 1.0 Documentation Monthly Experimental Calibrated GVI
A02-9
-------
was used. The data are produced for the region between 75 degrees North latitude and
55 degrees South latitude. Data resolution in the Mercator projection varies from 19.6 km
pixel size at the equator to 15 km at 40 degrees (North or South). The reflectance values
of the visible and near-IR data were computed from pre-launch calibration coefficients.
The NDVI was computed as:
NDVI = (nearlR - visible)/(nearlR + visible).
The calibrated visible and near-IR data, and solar zenith angle data included on the
NOAA GVI product were used to screen the NDVI data for cloud contamination and
low (less than 15 degrees) solar elevation at the time of data acquisition. Data were also
screened for data drops. Two successive weeks of the screened NDVI data were then
composited based on the maximum NDVI value of the two weeks. The biweekly data
were processed for April 1985 through 1990. The start date of the biweekly composite
intervals was 099 (9 April) in 1985. The start dates in 1986,1987,1988 were 001 (1
January). Processing intervals changed in 1988 on 11 April to a Monday through Sunday
weekly cycle. The start date in 1989 was 002 (2 Januaiy), in 1990 was 001 (1 January) and
for 1991 was 007 (7 January).
The biweekly NDVI data have been scaled to a byte format from the original ND value
(a real number with a range from -1.00 to 1.00) computed with the above equation, using
the following conversion:
byteNDVI = (realNDVI x 100) + 100.
Thus, a byte NDVI value of 151 in the data set is equivalent to a computed real NDVI
value of 0.51. A byte NDVI value of 100 is equivalent to a computed real NDVI of 0.0.
Data tagged by the cloud, data drop, or solar elevation algorithms will include values of
0 through 2, respectively.
A FORTRAN program that computes line and sample location from latitude and
longitude is appended to this documentation.
More information can be provided by Kevin Gallo, NOAA/NESDIS, National Climatic
Data Center, Federal Building, Asheville, North Carolina 28801, USA (704) 259-0878, or
from the NGDC Global Change Data Base help line at (303) 497-6125.
DEVELOPMENT OF MONTHLY DATA FROM BI-WEEKLY DATA
The monthly data-set provided in the GED was computed from Kevin Gallo's Biweekly
Experimental Calibrated GVI data-set, distributed separately. This data-set was produced
for the ISY Global Change Encyclopedia ("GeoScope" from the Canada Centre for Remote
Sensing), and in compatible format to the GED (i.e., 10-minute, lat/long grid) to provide
GED 1.0 Documentation Monthly Experimental Calibrated GVI
A02-10
-------
a more convenient version of the bi-weekly data.
The monthly maxima of the Gallo experimental GVIs were computed by taking the
maximum values of biweekly GVIs for each month, then reprojecting the original
mercator-projected data to latitude-longitude projection. The compilation was produced
from Gallo's data by the U. S. Geological Survey's EROS Data Center.
Inspection of these data at NOAA's National Geophysical Data Center showed that the
computed data were internally consistent to within one grid cell (the locational accuracy
usually attributed to the NOAA Polar Orbiting Environmental Satellites that house the
AVHRR sensor). However, the data were misregistered to the Earth by approximately 1
grid cell (to the south). In coordination with the Canada Centre for Remote Sensing
(CCRS), the data were identically reregistered at NGDC and CCRS by removing the
northernmost row of data, and inserting a new row at the bottom of each data file. As
these rows contained no GVI values, no data were lost in the process.
COLOR PALETTES
A color palette has been developed based on intensity levels of the scaled ME-GVI
(Monthly Experimental GVI). Although such palettes are arbitrary, and do not represent
detailed studies of land-cover classifications, the NGDC palette used with the Monthly
Generalized GVI (MG-GVI) has become popular among some users. These palettes are
provided with the database in both 4 bit-plane (16-color) and 8 bit-plane (256-color) form
(MEV4.PAL and MEV8.PAL, respectively).
These palettes also provide the capability to visually compare the ME-GVI documented
here with the Monthly Generalized GVI (MG-GVI) developed at NGDC (see Chapter
A01), since identical color-slicing was used for both data-sets, according to their
respective offset and gain characteristics. The table below provides the color-slicing
criteria for the 256-color palette, for both data-sets.
GVI
MO-OVI
MI-OVI
COLOR
RBD
0R8KN
BLUB
0
Blue
0
0
20
1
White
63
63
63
2
White
63
63
63
0
3
Blue
0
0
20
0
32.5
100
Brown
17
0
0
20
68
117
Yellow
63
51
0
40
104
134
Olive
20
30
0
50
122
142
Green
0
30
0
75
166
163
Br.Green
0
63
0
100
211
184
Green/White
32
63
32
255
255
White
63
63
63
GED 1.0 Documentation Monthly Experimental Calibrated GVI
A02-11
-------
The color-slicing levels and color definitions, which result from simple Red-Green-Blue
intensity levels (0-63) using IBM-PC conventions, are shown in the table above. "% GVI"
refers to the percent of the GVI range represented in the data-set, between XVT=0 (32.5 in
the MG-GVI data and 100 in the ME-GVI data) and the mean monthly maximum for
July.
The 16-color palette mimics the above color scheme, assuming a linear re-scaling (i.e.,
"stretch" or "binning") to 16 classes from 0 to the Maximum data value in the file. Since
the monthly maxima vary between files, comparable displays require re-setting the
maxima to a standard value for the series. This will involve different procedures for
each software package.
NOTES
1. Maximizing over a full month reduces variable cloud effects, preserves the
original calibrations, and reduces temporal aliasing (i.e., the likelihood of missing
the significant event of the month); but it drastically increases temporal variability
between pixels (i.e., values may be from any day of the month), effects due to
variable look and sun angles, and the tendency toward temporal bias (e.g., data
may be only one day apart if maxima occur at the end of one month and the
beginning of the next).
2. Due to the large offset in the integer scaling, these data have a reduced dynamic
range with respect to GVI (the lower end of the NDVI range is offset to 100 in the
data-set).
3. Quality masking complicates spatial analysis (it has been recommended that
future versions provide masks separate from the primary data so that error
analysis can be performed independently).
4. Although the calibration procedure was successful in matching the NOAA-9 and
NOAA-11 data, it does not remove the calibration "drift" noted for low values of
the GVI data (see Chapter A01). Furthermore, this drift, increasing throughout
the NOAA-9 data, shifts to a decreasing trend in the NOAA-11 data.
5. There is also an obvious shift in the amount of masking, increasing sharply at the
transition between NOAA-9 and NOAA-11 data.
6. The monthly data may have lost some definition in resampling from lat/long at
360 degrees = 2500 pixels (plate carrel) to Mercator at 360 degrees = 2048, and
then back to a 10-minutes, with 360 degrees = 2160 pixels.
GED1.0 Documentation Monthly Experimental Calibrated GVI
A02-12
-------
MERCATOR PROJECTION
PROGRAM TO CONVERT LATITUDES & LONGITUDES INTO MERCATOR MI AND
MJ COORDINATES
c
c
c This program converts input latitude and longitude values into
c MI and MJ coordinates associated with the NOAA Vegetation
c Index products with Mercator projections described in Kidwell
c (1991). Written by K. P. Gallo, 11 November 1987.
c
c
c
c
real lat,long, mi, mj, in,lone, x,y,i,j,reply
data pi/3.1416/,in/2500.0/,lonc/o.o/
c
20 write(*,701) ' enter latitude and longitude in degrees '
read(*,'(BN, 2f7.2)') lat, long
write(*,*) lat, long
701 format(a\)
c
x=in*(I6n0-lonc)/360.
y=in*(lat)/360.
c
i=x+1250.0
j=-y+522.0
c
mi=(i*.8192)
mj=662.0-(log(tan(-0.00126*j+1.44136))*325.95)
c
write(*,2001) ' mj(line#)s mj, ' mi (sample#)= mi
2001 format(a,f7.2,a,f7.2)
write(*,701) ' enter a "1" for another lat,long '
read(*,'(BN,fl.0)') reply
if (reply .eq. 1) goto 20
end
GED 1.0 Documentation Monthly Experimental Calibrated GVI
A02-13
-------
A03
Leemans and Cramer UASA Mean Monthly Temperature,
Precipitation, and Cloudiness
GED 1.0 Documentation UASA Mean Monthly Temperature, Precipitation, and CUuMm*» AOS
-------
DATA-SET DESCRIPTION
DATA-SET NAME: IIASA Mean Monthly Temperature, Precipitation,
and Cloudiness
PRINCIPAL INVESTIGATORS): Rik Leemans and Wolfgang P. Cramer
International Institute for Applied
Systems Analysis
SOURCE
SOURCE DATA CITATION: Leemans, R., and W.P. Cramer. 1991. The IIASA Database
for Mean Monthly Values of Temperature, Precipitation, and Cloudiness on a Global
Terrestrial Grid. Digital Raster Data on a 30 minute Geographic (lat/long) 360x720
grid. Laxenburg, Austria: IIASA. 9-track tape, 10.3 MB
CONTRIBUTOR(s):
Dr. Rik Leemans
National Institute of Public Health and Environmental Protection, RIVM
P.O. Box 1
NL-3720 BA Bilthoven, The Netherlands
(31)30-749111
DISTRIBUTOR(s): IIASA and RIVM
VINTAGE: circa 1990
LINEAGE:
(1) Published records from 1931 to 1960 (see ORIGIN)
(2) Data integrated from multiple sources at IIASA (Leemans and Cramer)
ORIGINAL DESIGN
VARIABLES:
(1) Average Monthly Surface Temperature, converted to °C (predsion=.l°C)
(2) Monthly Average Precipitation (interpolation of measured values), uncorrected for
rain-guage bias.
(3) "Cloudiness," expressed as percentage sunshine hours of potential hours per
month at the land surface.
ORIGIN: Weather records from the following sources (see Primary Documentation):
1) World Weather Records, U.S. Weather Burear.
2) The Climate Atlas of Walter and Lieth
3) Miiller Selected Climatic Data for Vegetation Science, based on:
a) UK Meteorological Office records
b) World Survey of Climatology (Landsberg)
GED 1.0 Documentation IIASA Mean Monthly Temperature, Precipitation, and Cloudiness A03-2
-------
4) Bradley: Precipitation and Temperature Data for the Northern Hemisphere
5) Selected weather data for Europe from the UK Meteorological Office
6) Thornthwait and Mather's Temperature and Precipitation data.
7) Soviet Temperature and Precipitation data (Siberia)
8) Chinese Temperature and Precipitation data (NE China)
GEOGRAPHIC REFERENCE: latitude/longitude
GEOGRAPHIC COVERAGE: Global
Maximum Latitude : +90 degrees (N)
Minimum Latitude : -90 degrees (S)
Maximum Longitude : +180 degrees (E)
Minimum Longitude : -180 degrees (W)
GEOGRAPHIC SAMPLING: 30-minute cell values interpolated from station
observations using spatial model (see Leemans and Cramer, 1992; pgs. 13-14).
TIME PERIOD: "current climate" (or "normal climate") as characterized from 1931-1960
TEMPORAL SAMPLING: long-term means for each month composited from available
records.
INTEGRATED DATA-SET
DATA-SET CITATION: Leemans, R., and W.P. Cramer. 1992. I1ASA Database for Mean
Monthly Values of Temperature, Precipitation, and Cloudiness on a Global Terrestrial
Grid. Digital Raster Data on a 30 minute Geographic (lat/long) 360x720 grid. In:
Global Ecosystems Database Version 2.0: Disc A. Boulder, CO: NOAA National
Geophysical Data Center. 36 independent single-attribute spatial layers on CD-
ROM, 15.6MB. [first published in 1991]
ANALYST(s): Rik Leemans and Wolfgang P. Cramer, DASA, Laxenburg, Austria
PROJECTION: Geographic (lat/long), GED window (see User's Guide).
SPATIAL REPRESENTATION: Characteristic values for 30-minute cells, from a spatial
model based on irregularly located station data.
TEMPORAL REPRESENTATION: Characteristic months of average climate for 1931-
1960 (a relatively stable period).
DATA REPRESENTATION:
Temperature: 2-byte integers, representing surface air temperature in
l/10th degrees Celsius (or degrees x 10).
Precipitation: 2-byte integers, representing average monthly precipitation in
milimeters (uncorrected)
Cloudiness: 1-byte integers, representing percentage sunshine hours of
potential hours per month (0-100).
LAYERS AND ATTRIBUTES: 36 independent single-attribute spatial layers
COMPRESSED DATA VOLUME: 2,260,638 bytes
GED 1.0 Documentation HASA Mmm Monthly Ttmp*r*turt, Precipitation, ami Clouding* A03~3
-------
PRIMARY REFERENCES (* reprint on CD-ROM)
* Leemans, R. and W.P. Cramer, 1991. The DAS A database for mean monthly
values of temperature, precipitation and cloudiness of a global terrestrial
grid. Research Report RR-91-18 November 1991, International Institute of
Applied Systems Analyses, Laxenburg. 61pp.
ADDITIONAL REFERENCES
Solomon, A.M. and R. Leemans. 1990. Climatic change and landscape-ecological
response: Issues and analyses. In: Boer, M.M. and de Groot, R.S. (eds.), Landscape
Landscape Ecological Impact of Climatic Change. IOS Press, Amsterdam, pp. 293-316
(ISBN 90 5199 023 5).
Prentice, I.C., Cramer, W., Harrison, S.P, Leemans, R., Monserud, R.A. & Solomon, A.M.
1992. A global biome model based on plant physiology and dominance, soil
properties and climate. /. Biogeography (in press).
Monserud, R.A. and Leemans, R. 1992. The comparison of global vegetation maps. Ecol.
Modelling (in press).
GED 1.0 Documentation JIAS A Mean Monthly Temperature, Precipitation, and Cloudinets A03-4
-------
DATA-SET FILES
LOCATION
NAMB
NUMBER
TOOL SBB
Spatial Data:
\GLGEO\RASTER\
LCCLD01.IMG
to
LCCLD12.IMG
12
files
3,110,400
LCPRC01.IMG
to
LCPRC12.IMG
12
files
6,220,800
LCTMP01.IMG
to
LCTMP12.IMG
12
files
6,220,800
Haadara t
\GLGEO\META\
LCCLD01.DOC
to
LCCLD12.DOC
12
files
6,976
LCPRC01.DOC
to
LCPRC12.DOC
12
files
6,619
LCTMP01.DOC
to
LCTMP12.DOC
12
files
6,536
Palattaai
\GLGEO\META\
LCCLD8.PAL
1
file
4,352
Tim* Sarlaat
\GLGEO\META\
LCCLD.TS
1
file
114
LCPRC.TS
1
file
114
LCTMP.TS
1
file
114
Volume on Diaks
76
files
15,576,825
REPRINT FILES
LOCATION
NAMB
NUMBBR
TOOL 8328
\DOCUMENT\AO3\
LC1_01.PCX I
to
LC1_28.PCX
28
files
1,011,402
LC1_##X.PCX
3
files
240,738
LC2_01.PCX
to
LC2_27.PCX
27
files
1,556,067
LC2_##X. PCX
5
files
530,152
Voluma on Disk:
63
files
2,338,359
SOURCE EXAMPLE FILES
none
GED 1.0 Documentation UASA Mean Monthly Temperature, Precipitation, and Cloudineu A03-5
-------
FILE DESCRIPTION
DATA ELEMENT: Average Month Surface Air Temperature
STRUCTURE: Raster Data Files: .5-degree 360x720 GED grid (see User's Guide)
SERIES: series of 12 characteristic months
SPATIAL DATA FILES:
LCTMP01.DOC
file title
Leemans and Cramer January Temperature (0.1°C)
data type
integer
file type
binary
columns
720
rows
360
ref. system
lat/long
ref. units
deg
unit dist.
1.0000000
min. X
-180.0000000
max. X
180.0000000
min. Y
-90.0000000
max. Y
90.0000000
pos'n error
unknown
resolution
0.5000000
min. value
-583
max. value
406
value units
0.1 degrees Celsius
value error
unknown
flag value
-999
flag def'n
flag value -999 indicates no data
legend cats
0
File Series Parameters:
File Month Minimum Maxdmum
LCTMP01
January
-583
406
LCTMP02
February
-546
413
LCTMP03
March
-512
423
LCTMP04
April
-430
432
LCTMP05
May
-284
434
LCTMP06
June
-223
429
LCTMP07
July
-222
441
LCTMP08
August
-214
423
LCTMP09
September
-272
426
LCTMP10
October
-371
423
LCTMP11
November
-445
420
LCTMP12
December
-533
417
(units are irC l/10th degrees Celsius, or degrees x 10)
NOTES:
GED 1.0 Documentation UASA Mean Monthly Temperature, Precipitation, and Cloudine** A03-6
-------
DATA ELEMENT: Average Month Precipitation (uncorrected)
STRUCTURE: Raster Data File: .5-degree 360x720 GED grid (see User's Guide)
SERIES: none
SPATIAL DATA FILES:
LCPRC01.DOC
file title :
Leemans and Cramer January Precipitation (mm/month)
data type :
integer
file type :
; binary
columns :
i 720
rows :
: 360
ref. system :
: lat/long
ref. units :
: deg
unit dist. :
: 1.0000000
min. X :
! -180.0000000
max. X
: 180.0000000
min. Y
: -90.0000000
max. Y
: 90.0000000
pos'n error :
: unknown
resolution
: 0.5000000
min. value
: 0
max. value
: 942
value units ;
: millimeters /month
value error
: unknown
flag value
: -999
flag def'n
: flag value -999 indicates no data
legend cats
: 0
File Series
File
LCPRC01:
LCPRC02:
LCPRC03:
LCPRC04:
LCPRC05:
LCPRC06:
LCPRC07:
LCPRC08:
LCPRC09;
LCPRC10:
LCPRC11:
LCPRC12:
Parameters:
Month
January
February
March
April
May
June
July
August
September
October
November
December
Minimum Maximum
0 942
0 652
0 830
0 676
0 1280
0 2695
0 2774
0 1950
0 1106
0 863
0 914
0 743
NOTES:
GED 1.0 Documentation HASA Mean Monthly Temperature, Precipitation, and Clouding** A03-7
-------
DATA ELEMENT: Average Month "Cloudiness" (% sunshine)
STRUCTURE: Raster Data File: .5-degree 360x720 GED grid (see User's Guide)
SERIES: series of 12 characteristic months
SPATIAL DATA FILES:
file title
data type
file type
columns
rows
ref.
ref.
system
units
unit dist,
min. X
max.
min.
max.
X
Y
y
pos'n error
resolution
min. value
max. value
value units
value error
flag value
flag def'n
legend cats
LCCLD01.DOC
Leemans and Cramer January Cloudiness (* sunshine)
byte
binary
720
360
lat/long
deg
1.0000000
-180.0000000
180.0000000
-90.0000000
90.0000000
unknown
0.5000000
0
95
percentage sunshine hours of potential hours per month
unknown
254
flag value 254 indicates no data
0
File Series Parameters:
File
LCCLD01
LCCLD02
LCCLD03
LCCLD04
LCCLD05
LCCLD06
LCCLD07
LCCLD08
LCCLD09
LCCLD10
LCCLDll
LCCLD12
Month
January
February
March
April
May
June
July
August
September
October
November
December
Minimum Maximum
0 95
4 94
9 88
2 92
2 95
0 98
0 100
0 98
0 98
0 99
0 96
0 100
NOTES:
1. Regional discrepancies with the FAO climatic database have been noted (e.g.,
Vietnam).
GED 1.0 Documentation RASA Mean Monthly Temperature, Precipitation, and Cloudiness A03-8
-------
DATA INTEGRATION AND QUALITY
i - ¦ —
Mark A. Ohrenschall
NOAA National Geophysical Data Center
Boulder, Colorado
The source data were in lat/long projection at 0.5-degree resolution. The source files
were in a ASCII record format, with ocean cells omitted. Each data file had a header line
containing two different fortran format statements, followed by fixed-length data records
containing latitude and longitude in tenths of degrees, referencing the south-west corner
of the grid cell, followed by that cell's twelve monthly values.
A raster data file was created for each month for each parameter, setting the background
to a no-data flag and a program was written to read in grid values from the source files.
Results were checked by spot-checking individual grid points.
The original data structure was compatible with the GED grid conventions, and no
changes were made in the original data values, numerical type, or precision.
The data were inspected to verify that there were no obvious artifacts and to spot check
the final integrated data against the original source. Some comparisons were made with
other data-sets in the database, e.g., the Legates and Willmott data, finding some
discrepancies. In particular, comparison with local patterns (e.g., near Mexico) indicated
potentially large differences due to variable surface conditions. Otherwise, the data
appear to be representative of broad-scale patterns, and reviewers noted that it may
provide better resolution than the Legates and Willmot data.
GED 1.0 Documentation UASA Mtan Monthly Temperature, Precipitation, and Cloudinef A03-9
-------
A04
Legates and Willmott Monthly Average Surface Air
Temperature and Precipitation (re-gridded)
GED 1.0 Documentation Monthly Average Air Temperature and Precipitation
A04
-------
DATA-SET DESCRIPTION
data-set NAME: Monthly Average Surface Air Temperature and
Precipitation (re-gridded)
PRINCIPAL INVESTIGATORS): David R. Legates and Cort J. Willmott
SOURCE
SOURCE DATA CITATION: Legates, D.R. and C.J. Willmott, 1989. Monthly Average
Surface Air Temperature and Precipitation. Digital Raster Data on a .5-degree
Geographic (lat/long) 361x721 grid (centroid-registered on .5 degree meridians).
Boulder CO. National Center for Atmospheric Research. 4 files on 9-track tape.
83MB.
CONTRIBUTORS):
Dr. David R. Legates and
Department of Geography
College of Geo sciences
University of Oklahoma
Norman, OK 73019 USA
(405) 325-6547
DISTRIBUTORS): NCAR
VINTAGE: circa 1980's
LINEAGE:
(1) Principal Investigators: David R. Legates and Cort J. Willmott
(2) Archived and Distributed by:
Roy Jenne
National Center for Atmosphereic Research
Boulder, CO
Dr. Cort J. Willmott
Center for Climatic Research
Department of Geography
University of Delaware
Newark, DE 19716 USA
(302) 451-8998
ORIGINAL DESIGN
VARIABLES:
VARIABLE UNITS PRECISION
Measured precipitation mm/month 1mm
Guage corrected precipitation mm/month 1mm
Standard error of corrected precipitation mm/month 1mm
Surface Air temperature degrees Celsius .1 °C
ORIGIN: 24,941 independent surface air temperature and 26,858 independent
precipitation stations, and oceanic grid point estimates from a variety of sources
(see Primary Documentation).
GED 1.0 Documentation Monthly Average Surface Air Temperature and Precipitation A04-2
-------
GEOGRAPHIC REFERENCE: latitude/longitude
Centroid-registered grid cells on 30-minute lat/long meridians. Original grid
(361x721) extends from pole to pole and originates at the International Date Line.
GEOGRAPHIC COVERAGE: Global
Maximum Latitude +90 degrees (N)
Minimum Latitude -90 degrees (S)
Maximum Longitude : +180 degrees (G)
Minimum Longitude : -180 degrees (W)
GEOGRAPHIC SAMPLING: Weighted (using a spherically-based interpolation
algorithm) 30-minute cell averages of station data and oceanic trackline samples,
on a centroid-registered 30-minute grid.
TIME PERIOD: Modern "average" climate, from records mostly between 1920 and 1980.
TEMPORAL SAMPLING: 12 characteristic months and characteristic years for each
variable, representing long-term (approx. 60 year) monthly and annual means.
INTEGRATED DATA-SET
DATA-SET CITATION: Legates, D.R. and C.J. Willmott. 1992. Monthly Average
Surface Air Temperature and Precipitation. Digital Raster Data on a 30 minute
Geographic (lat/long) 360x720 grid. In: Global Ecosystems Database Version 1.0: Disc
A. Boulder, CO: NOAA National Geophysical Data Center. 48 independent and 4
derived single-attribute spatial layers on CD-ROM, 47.2MB. [first published in
1989]
ANALYSTS): John Kineman and Mark Ohrenschall
PROJECTION: Geographic (lat/long), GED window (see User's Guide).
SPATIAL REPRESENTATION: 30-minute cell values interpolated from the 4
overlapping quadrant values of the original grid, which contained values
interpolated from irregularly spaced point observations.
TEMPORAL REPRESENTATION: 12 characteristic months and characteristic years for
each variable, representing long-term (approx. 60 year) means.
DATA REPRESENTATION: 2-byte integers, representing:
VARIABLE UNITS PRECISION
1. Measured precipitation mm/month 1mm
2. Guage corrected precipitation mm/month 1mm
3. Surface Air temperature °C x 10 .1 °C
4. Standard deviation (expressed in the same units and precision as above) of the
interpolated cell values for each measurement (precipitation, corrected
precipitation, and temperature) are provided as separate layers as an estimate of
uncertainty introduced bv the re-gridding process - these three standard
deviation ("SD") files were not part of the oritmial data-set
5. RMS Std. error of corrected precip. mm/month 1mm
Note that this variable was re-gridded by a different method than the first three:
The re-gridding method employed a root-mean-square average to combine the 4
quadrant values into the newly registered grid cell for the GED.
GED 1.0 Documentation Monthly Average Surface Air Temperature and Precipitation A04-3
-------
LAYERS AND ATTRIBUTES: 52 independent and 39 derived single-attribute spatial
layers
COMPRESSED DATA VOLUME: 15,707,536 bytes
PRIMARY REFERENCES (* reprint on CD-ROM)
* Legates, David R. 1989. "A high-resolution climatology of gage-corrected global
precipitation." In: Precipitation Measurement, B. Sevruk (ed.), Proceedings of
the WMOflAHS/ETH International Workshop on Precipitation Measurement, St.
Moritz, Switzerland, Dec. 3-7,1989. Zurich: Swiss Federal Institute of
Technology, pp. 519-526.
* Legates, David R. and Cort J. Willmott. 1990. "Mean seasonal and spatial
variability in global surface air temperature." Theoretical and Applied
Climatology, vol. 41, pp. 11-21.
* Legates, David R. and Cort J. Willmott. 1990. "Mean seasonal and spatial
variability in gauge-corrected global predpitation." International Journal of
Climatology, vol. 10. pp. 111-127.
ADDITIONAL REFERENCES
Sevruk, B. 1989. "Reliability of precipitation measurement." In: Precipitation
Measurement, B. Sevruk (ed.), Proceedings of the WMO/IAHS/ETH International
Workshop on Precipitation Measurement, St. Moritz, Smtzerland, Dec. 3-7,1989.
Zurich: Swiss Federal Institute of Technology, pp. 519-526
Shepard, D. 1968. "A two-dimensioinal interpolation function for irregularly-spaded
data." In: Proceedings of 23rd National Conference of the Association for Computing
Machinery. ACM Pub. P-68. Princeton, NJ: Brandon/Systems Press, Inc.
Legates, David R. 1987. A Climatology of Global Precipitation. Pub. Climatol, 40(1):
103 p.
Willmott, C.J., C.M. Rowe, and W.D. Philpot. 1985. "Small-scale climate maps: a
sensitivity analysis of some common assumptions associated with grid-point
interpolation and contouring. The American Cartographer, 12(1): 5-16.
GED 1.0 Documentation Monthly Average Surface Air Temperature and Precipitation
A04-4
-------
DATA-SET FILES
LOCATION
NAME
NUMBER
TOOL SIZE
Spatial Data:
\GLGEO\RASTER\
LWCPRO 0.IMG to
LWCPR12.IMG
13
files
6,739,200
LWCSD00.IMG to
LWCSD12.IMG
13
files
6,739,200
LWERROO.IMG to
LWERR12.IMG
13
files
6,739,200
LiWMPROO.IMG to
LWMPR12.IMG
13
files
6,739,200
LWMSDO0.IMG to
LWMSD12.IMG
13
files
6,739,200
LWTMPO0.IMG to
LWTMP12.IMG
13
files
6,739,200
LWTSD00.IMG to
LWTSD12.IMG
13
files
6,739,200
Headers:
\GLGEO\META\
LWCPRO0.DOC to
LWCPR12.DOC
13
files
6,921
LWCSDOO.DOC to
LWCSD12.DOC
13
files
6,799
LWERROO.DOC to
LWERR12.DOC
13
files
6,908
LWMPROO.DOC to
LWMPR12.DOC
13
files
6,775
LWMSDO0.DOC to
LWMSD12.DOC
13
files
6,944
LWTMPO0.DOC to
LWTMP12.DOC
13
files
6,931
LWTSDOO.DOC to
LWTSD12.DOC
13
files
6,814
Palettes:
none
Tim* Seriest
\GLGEO\META\
LWCPR.TS
1
file
123
\GLGEO\META\
LWMPR.TS
1
file
123
\GLGEO\META\
LWTMP.TS
1
file
123
Voluma on Disk:
185
files
47,222,861
REPRINT FILES
LOCATION
NUB
NUMBER
TOOL S1ZB
\DOCUMENT\AO4\
LW1_01.PCX to
LC1_17.PCX
17
files
864,882
LW1_##X.PCX
16
files
2,871,460
LW2_1.PCX to LC1_8.PCX
8
files
695,424
LW2_#X.PCX
6
files
921,810
LW3_01.PCX to
LC1_11.PCX
11
files
577,957
LW3_##X.PCX
7
files
1,263,135
Voluma on Diakt
65
files
7,194,668
SOURCE EXAMPLE FILES
LOCATION
NAME
NUMBER
tool sob
Spatial Data:
\SOURCE\RASTER\
LWSCPO 7.IMG
1
file
520,562
LWSER07.IMG
1
file
520,562
LWSMPO 7.IMG
1
file
520,562
LWSTMO7.IMG
1
file
520,562
Headers*
\SOURCE\RASTER\
LWSCPO7.DOC
1
file
538
LWSER07.DOC
1
file
528
LWSMPO7.DOC
1
file
537
LWSTMO7.DOC
1
file
531
Volume on Dirts
8
files
2,084,382
GED 1.0 Documentation Monthly Average Surface Air Temperature and Precipitation A04-5
-------
FILE DESCRIPTION
DATA ELEMENT: Guage Corrected Precipitation (re-gridded)
STRUCTURE: Raster Data Files: .5-degree 360x720 GED grid (see User's Guide)
SERIES: none
SPATIAL DATA FILES:
LWCPROO.DOC
file title :
Legates & Willmott Annual Corrected Precipitation (mm/year)
data type :
integer
file type :
binary
columns :
720
rows
360
ref. system :
lat/long
ref. units :
deg
unit dist.
1.0000000
min. X :
-180.0000000
max. X :
180.0000000
min. Y
-90.0000000
max. Y :
90.0000000
pos'n error :
unknown
resolution :
0.5000000
min. value :
0
max. value :
6626
value units :
mi11imeters/year
value error :
unknown
flag value :
none
flag def'n :
none
legend cats :
0
File Series Parameters:
File
Month
Minimum
Maximum
LWCPROO
year cum.
0
6434
LWCPR01
January
0
1048
LWCPR02
February
0
612
LWCPR03
March
0
616
LWCPR04
April
0
545
LWCPR05
May i
0
646
LWCPR06
June
0
1129
LWCPR07
July
0
1378
LWCPR08
August
0
1327
LWCPR09
September
0
833
LWCPR10
October
0
739
LWCPR11
November
0
848
LWCPR12
December
0
876
Standard
Deviation:
LWCSD00
year exam.
0
2410
LWCSD01
January
0
255
LWCSD02
February
0
176
LWCSD03
March
0
261
LWCSD04
April
0
215
LWCSD05
May
0
264
LWCSD06
June
0
335
LWCSD07
July
0
506
GGD 1.0 Documentation Monthly Average Surface Air Temperature and Precipitation A04-6
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LWCSD08 August 0 364
LWCSD09 September 0 261
LWCSD10 October 0 328
LWCSD11 November 0 258
LWCSD12 December 0 239
ATTRIBUTE DATA FILES none
NOTES:
1. Mean and standard deviation derived from 2x2 quadrant average of the source
grid, resulting in an interpolated .5-degree (GED) grid with 1-deg. smoothing.
GED 1.0 Documentation Monthly Average Surface Air Temperature and Precipitation
A04-7
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DATA ELEMENT: Standard Error for Guage Corrected Precipitation
(re-gridded)
STRUCTURE: Raster Data Files: .5-degree 360x720 GED grid (see User's Guide)
SERIES: none
SPATIAL DATA FILES:
LWERROO.DOC
file title
Legates & Willmott Annual Standard Error (mm/year)
data type
integer
file type
binary
columns
720
rows
360
ref. system
lat/long
ref. units
deg
unit dist.
1.0000000
min. X
-180.0000000
max. X
180.0000000
min. Y
-90.0000000
max. y
90.0000000
pos'n error
unknown
resolution
0.5000000
min. value
0
max. value
344
value units
millimeters/year
value error
unknown
flag valjae
none
flag def'n
none
legend cats
0
File Series Parameters:
File
Month Minimum
Maximum
LWERR00
year cum.
0
344
LWERR01
January
0
401
LWERR02
February
0
571
LWERR03
March
0
558
LWERR04
April
0
550
LWERR05
May
0
319
LWERR06
June
0
275
LWERR07
July
0
354
LWERR08
August
0
492
LWERR09
September
0
400
LWERR10
October
0
599
LWERR11
November
0
969
LWERR12
December
0
720
ATTRIBUTE DATA FILES
none
NOTES:
1. Mean and standard deviation derived from 2x2 quadrant average of the source
grid, resulting in an interpolated .5-degree (GED) grid with 1-deg. smoothing.
2. The corrected precipitation error data were interpolated by a 2x2 r.m.s. filter.
GED 1.0 Documentation Monthly Average Surface Air Temperature and Precipitation A04-8
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DATA ELEMENT: Measured Precipitation (re-gridded)
STRUCTURE: Raster Data Files: 0.5-degree 360x720 GED grid (see User's Guide)
SERIES: none
SPATIAL DATA FILES:
LWMPROO.DOC
file title
Legates & Willmott Annual Measured Precipitation (mm/year)
integer
data type
file type
binary
columns
720
rows
360
ref. system
lat/long
ref. units
deg
unit dist.
1.0000000
min. X
-180.0000000
max. X
180.0000000
min. Y
-90.0000000
max. Y
90.0000000
pos'n error
unknown
resolution
0.5000000
min. value
0
max. value
6434
value units
mi11imeters/year
value error
unknown
flag value
none
flag def'n
none
legend cats
0
File Series Parameters:
File
Month
Minimum
Maximum
LWMPR00
year cum.
0
6434
LWMPR01
January
0
1048
LWMPR02
February
0
612
LWMPR03
March
0
616
LWMPR04
April
0
545
LWMPR05
May
0
646
LWMPR06
June
0
1129
LWMPR07
July
0
1378
LWMPR08
August
0
1327
LWMPR09
September
0
833
LWMPR10
October
0
739
LWMPR11
November
0
848
LWMPR12
December
0
876
Standard
Deviations
LWMSD00
year cum.
0
2362
LWMSD01
January
0
251
LWMSD02
February
0
172
LWMSD03
March ¦
0
253
LWMSD04
April
0
210
LWMSD05
May
0
259
LWMSD06
June
0
330
LWMSD07
July
0
496
LWMSD06
August
0
357
LWMSD09
September
0
253
LWMSD10
October
0
321
GED 1.0 Documentation Monthly Average Surf tut Air Temperature and Precipitation A04-9
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LWMSD11 November 0 252
LWMSD12 December 0 233
ATTRIBUTE DATA FILES none
NOTES:
1. Mean and standard deviation derived from 2x2 quadrant average of the source
grid, resulting in an interpolated .5-degree (GED) grid with 1-deg. smoothing.
DATA ELEMENT: Surface Air Temperature (re-gridded)
STRUCTURE: Raster Data Files: .5-degree 360x720 GED grid (see User's Guide)
SERIES: none
SPATIAL DATA FILES:
LWTMPOO.DOC
file title
Legates & Willmott Annual Temperature (0.1C)
data type
integer
file type
binary
columns
720
rows
360
ref. system
lat/long
ref. units
deg
unit dist.
1.0000000
min. X
-180.0000000
max. X
180.0000000
min. Y
-90.0000000
max. Y
90.0000000
pos'n error
unknown
resolution
0.5000000
min. value
-569
max. value
299
value units
0.1 degrees Celsius
value error
unknown
flag value
none
flag def'n
none
legend cats
0
File Series Parameters:
Pile
Month
Minimum
Maximum
LWTMP00
year cum.
-569
299
LWTMP01
January
-540
328
LWTMP02
February
-503
323
LWTMP03
March
-584
330
LWTMP04
April
-666
339
LWTMP05
May
-674
358
LWTMP06
June
-702
399
LWTMP07
July
-690
418
LWTMP08
August
-718
395
LWTMP09
September
-669
363
LWTMP1Q
October
-596
319
LWTMP11
November
-441
324
LWTMP12
December
-468
336
GED 1.0 Documentation Monthly Average Surface Air Temperature and Precipitation A04-10
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Standard Deviation:
LWTSD00
year cum.
0
152
LWTSD01
January
0
146
LWTSDO 2
February
0
156
LWTSDO 3
March
0
182
LWTSDO4
April
0
173
LWTSDO5
May
0
161
LWTSDO6
June
0
169
LWTSDO7
July
0
155
LWTSDO8
August
0
149
LWTSDO 9
September
0
156
LWTSD10
October
0
150
LWTSD11
November
0
147
LWTSD12
December
0
158
ATTRIBUTE DATA FILES none
NOTES:
1. Mean and standard deviation derived from 2x2 quadrant average of the source
grid, resulting in an interpolated .5-degree (GED) grid with 1-deg. smoothing.
GED 1.0 Documentation Monthly Average Surface Air Temperature ami Precipitation
A04-11
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SOURCE EXAMPLE: Average Monthly Air Temperature and
Precipitation (Source Examples)
STRUCTURE: Raster Data File: .5-degree, 361x721 centroid-registered grid (non-GED
registration convention - see User's Guide)
SERIES: Sample file for July
SPATIAL DATA FILES:
LWSCP07.DOC
file title :
Legates & Willmott July Corrected Precipitation (source)
data type :
integer
file type :
binary
columns :
721
rows :
361
ref. system :
lat/long
ref. units :
deg
unit dist. :
1.0000000
min. X :
-180.0000000
max. X :
180.0000000
min. Y :
-90.0000000
max. Y :
90.0000000
pos'n error :
unknown
resolution :
0.5000000
min. value :
0
max. value :
1540
value units :
millimeters/month
value error :
unknown
flag value :
none
flag def'n :
none
legend cats :
0
File Series Parameters:
File
Variable
Units Minimum Maximum
LWSCP07
Corr. Precip.
mm/month 0
1540
LWSER07
Guage error
mm/month 0
376
LWSMP07
Meas. Precip.
mm/month 0
1492
LWSTM07
Temperature
°C x 10 -693
442
NOTES:
1. Source files are provided for the user to assess the appropriateness of the GED
integration method in cases where re-gridding, or other significant alteration of the data
values was necessary to achieve intercomparability with the other data-sets. See
Integration Methods (below).
GED 1.0 Documentation Monthly Average Surface Air Temperature and Precipitation A04-12
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DATA INTEGRATION AND QUALITY
John Kineman and Mark Ohrenschall
National Geophysical Data Center
Boulder, Colorado
OVERVIEW
The Legates and Willmott data are referenced to a latitude/longitude grid with the data
values located at intersections of the .5-degree latitude and longitude meridians, globally.
This can be seen as a grid of half-degree cells with the cell centers located at the .5
degree meridian intersections. Note also that the "cell" boundaries of this type of grid
extend beyond the "edges" of the global lat/long grid extending between +/-180 degrees
longitude and +/- 90 degrees latitude. This differs from the convention adopted for the
GED, of edge alignment with a nested set of GED "conventional" latitude and longitude
meridians, one of which is .5-degrees (i.e., the GED "nested" grids - see User's Guide). In
the GED convention, the cell boundaries are aligned with the edges of the global window
and with each "nested" meridian. The difference between these two grid conventions is
cell registration, but it poses a problem for integration or intercomparison with other
data in the database since differently registered grid cells do not occupy the same
location, and thus must be either interpolated or accepted with a spatial offset of 1/2 the
diagonal of a cell (e.g., systems that would automatically grid-sample to obtain the edge-
registered grid values from a centroid-registered grid).
In a raster GIS, each number in a digital image file is referenced to a "cell," which covers
some area on the surface of the earth. Given data values spaced a half-degree apart on a
latitude/longitude grid, each value is considered to refer to a half-degree "cell" on the
surface of the earth (although with true "point" data sets the value more properly refers
to the centroid of the cell). In practice, the spatial meaning of cell values may vary
considerably between data-sets, depending on design criteria of the original investigators.
The Legates and Willmott data are carefully interpolated from irregularly spaced point
observations to values that have a spatial resolution approximately equal to the cell size
(i.e., .5-degree). It is therefore not correct to assume a spatial uncertainty of 5-degrees,
as commonly used "nearest-neighbor" resampling would. Unfortunately, owing to the
complex nature of rainfall data and the spatial interpolation techniques that were applied
(see references), any method of re-gridding introduces problems.
In resampling from the Legates and Willmott grid to the Global Ecosystems Database
grid two methods were tested: (2) combining resampling and interpolation to represent
the data on a GED-compatible 10-minute grid, and (2) regridding (interpolation) to the
GED conventional half-degree grid using a simple 2x2 quadrant average for each cell in
the new grid. The first of these products was distributed on the 1991 Prototype CD-
GED 1.0 Documentation Monthly Average Surface Air Temperature and Precipitation
A04-13
-------
ROM of the GED Database (Version 0.1 - Beta Test). Partly based on the 1991 review, the
decision was made to include the second product on the current release of the GED
database (Version 1.0). Both of these solutions are considered inferior to re-producing
the data from source material, however this will require more time and resources.
METHOD USED IN THE PROTOTYPE
The method used for the prototype was to expand (by pixel replication) the Legates and
Willmott grid by a factor of six in both row and column dimensions, window on the
inner 2160 rows and 4320 columns (excluding the outer-most three rows and columns),
and then contract (with cell averaging) by a factor of two. The result was a 10-minute
grid that can nest with other gridded images in the Global Ecosystems Database. While
the new 10-minute grid was to some degree interpolated from the original grid, the
advantage of this method was that the original grid values are preserved amongst
interpolated values, and the original data-set can be recovered from the new grid by
sampling. Its disadvantage was that it was unclear how to use this mixed grid in normal
processing, and the artificially fine grids (10-minutes) require a lot of storage space and
may mislead users into assuming greater regional resolution than actually exists. In
other words, the expanded grid would have to be aggregated to a coarser grid to have
proper meaning anyway.
METHOD USED IN THE CURRENT VERSION
The method used for the current release was a simple grid interpolation, averaging 4 cell
values to obtain a 1/2 cell offset data-set on a .5-degree grid that is compatible with the
GED convention. This, unfortunately, also smooths the original data, thus reducing its
variability and changing its spatial meaning. Statistically, the new grid represents
averages of four 1/2-degree "quadrant" cells covering a lxl degree region, taken at 1/2-
degree grid increments. The data should be interpreted with this in mind, as it is a
questionable procedure for many uses to interpolate variables such as precipitation in
this way (although the original values are themselves interpolated and spatially general).
It may be more appropriate to use this interpolated GED grid for coarser studies, at 1-
degree or greater resolution.
To assess the uncertainty in the re-gridding process, companion data files are provided
for each variable giving the standard deviation (sample s.d., i.e., 1/n-l) for eadi cell's 4
source values. This may serve as a reliability indicator for the interpolated values.
According to the NCAR documentation, the gauge-error data (for the gauge-corrected
precipitation estimates) is expressed as a standard error, however the literature references
discuss gauge-errors in percent. It was decided to interpolate the gauge-error file as
standard error estimates, using a simple root-mean-square algorithm.
Further investigation of these methods is warranted.
GED 1.0 Documentation Monthly Average Surface Air Temperature and Precipitation
A04-14
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SOURCE FILE FORMATTING
The Legates and Willmott data came as four files on tape, one file for each parameter,
with an 80-character fixed-record format containing latitude, longitude, and 13 data fields
for the twelve monthly averages and the annual average. Since each record did have
geo-referencing, a cell sequencing was unnecessary, nonetheless the data files had cell
sequencing north to south within longitude columns, with column sequencing from west
to east, beginning at 90 degrees north and 180 degrees west. Each data value was
referenced by half-degree multiples, including 90 degrees north, 90 degrees south, 180
degrees west, and 180 degrees east.
DATA PROCESSING
In processing the data, the first task was running a custom-written program to
resequence the cells and extract the data fields to produce an Idrisi image for each
parameter for each monthly and annual image. Next, a program was written to average
a moving window of 4 original cell values, writing the averages and standard deviations
of the 2x2 average to the new grid.
In the following figure, the double-line represents the original grid before regridding.
The single-line represents the half-degree meridians and parallels, as well as the new,
interpolated grid. The new values are located at the intersection of 4 original .5 degree
cells. An "X" indicates the location of data points in the original Legates and Willmott
grid.
mL & W grid cell centered on half-degree
meridians and parallels
90 N ~ I X—I—X—jh-X—I—X X X half-degree edge-aligned cells
I I | I | I | I I I compatible with the GED nested grid
89.5 N ~ | X—II—X—|—X—H—X X X structure
CONCLUSION
The representation of the Legates and Willmott data is a compromise to achieve
integration with multi-thematic data. As with any data-set, the user must assess its value
for the purpose at hand. These "re-gridded" data will loose regional variability
information due to the smoothing effect of the interpolation. The amount of loss may be
estimated by the standard deviation values provided with the re-gridded data, and by
experimenting with the sample source file provided with the database. Nevertheless, an
obvious future improvement would be to re-calculate the data-set on the desired grid
from station observations, using the original (or improved) interpolation methods.
GED 1.0 Documentation Monthly Average Surface Air Temperature and Precipitation
A04-15
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A05
Olson World Ecosystems
GED 1.0 Documentation OUoh World Ecofyftcms
A05
-------
DATA-SET DESCRIPTION
DATA-SET NAME: World Ecosystems
PRINCIPAL INVESTIGATORS): Jerry S. Olson
Global Patterns Company
SOURCE
SOURCE DATA CITATION: Olson, J.S., 1989-91. World Ecosystems (WE13 and WE 1.4).
Digital Raster data on global Geographic (lat/long) 180x360 and 1080x2160 grids.
NOAA National Geophysical Data Center. Boulder, Colorado. Various working
files from GPC on floppy disk.
CONTRIBUTOR(s): Dr. Jeny S. Olson
Global Patterns Company
Eblen Cave Road, Box 361A
Lenoir City, Tennessee
37771-9424, USA
(615) 376-2250
(Fax (615) 690-3906 c/o Business Computer Associates)
DISTRIBUTOR(s): NGDC/WDC-A
VINTAGE: circa 1970's and 1980's (continuing updates)
LINEAGE: (1) Principal Investigator:
Jerry S. Olson
Global Patterns Company
(2) Reprocessed and updated by:
Jerry S. Olson, Lee Stanley, Jeff Colby, and Mark Ohrenschall
NOAA/NGDC, Boulder, CO 80303
ORIGINAL DESIGN
VARIABLES: Characteristic (actual) ecosystem classes with respect to carbon content.
WEI .3A Major Groups at 30-minute resolution
WE1.4D Detailed Categories at mixed 30-minute and 10-minute resolution
WE1.4DR Resolution codes for WE1.4D
ORIGIN: Numerous collected maps, references, and observations (see Primary
Documentation).
GEOGRAPHIC REFERENCE: latitude/longitude
GEOGRAPHIC COVERAGE: Global
Maximum Latitude : +90 degrees (N)
Minimum Latitude : -90 degrees (S)
GED 1.0 Documentation Olson World Ecosystems
A05-2
-------
Maximum Longitude : +180 degrees (E)
Minimum Longitude : -180 degrees (W)
GEOGRAPHIC SAMPLING: Characteristic classes for 30-minute cells with 10-minute
updates for selected classes in Africa
TIME PERIOD: Modem
TEMPORAL SAMPLING: Modern composite
INTEGRATED DATA-SET
DATA-SET CITATION: Olson, J.S. 1992. World Ecosystems (WE 1.4). Digital Raster Data
on a 10-minute Geographic 1080x2160 grid. In: Global Ecosystems Database, Version
1.0: Disc A. Boulder, CO: National Geophysical Data Center. 3 independent
single-attribute spatial layers on CD-ROM, 5 MB.
ANALYSTS): Jerry S. Olson and Lee Stanley, NGDC, Boulder, Colorado
PROJECTION: Geographic Oat/long), GED window (see User's Guide).
SPATIAL REPRESENTATION:
WEI .3A: 30-minute characteristic classes on a 30-minute grid
WE1.4D: mixed 30-minute and 10-minute characteristic classes on a 10-minute grid
WE1.4DR: 10-minute cell labels
TEMPORAL REPRESENTATION: Modern composite
DATA REPRESENTATION:
WE1.3A: single-byte integer codes for 29 major ecosystem/landscape groups.
WE1.4D: single-byte integer codes for 73 detailed ecosystem/landscape types.
WE1.4DR: single-byte integer cell labels for WE1.4D resolution.
LAYERS AND ATTRIBUTES: 3 independent single-attribute spatial layers
COMPRESSED DATA VOLUME: 215,231 bytes
PRIMARY REFERENCES (* reprint on CD-ROM)
* Olson, J.S., J.A. Watts, and L.J. Allison. 1985. Major World Ecosystem Complexes
Ranked by Carbon in Live Vegetation: A Database. NDP-017. Carbon
Dioxide Information Center, Oak Ridge National Laboratory, Oak Ridge,
Tennessee.
* Olson, J.S., J.A. Watts, and L.J. Allison, 1983. Carbon in Live Vegetation of Major
World Ecosystems, Report ORNL-5862, Oak Ridge Laboratory, Oak Ridge,
Tennessee. (Incorporated in NDP-017, cited above)
ADDITIONAL REFERENCES (Also see references on page A05-36)
Olson, R. J., F. G. Goff and J. S. Olson. 1976. Development and applications of regional
data resources in energy-related assessment and planning. Advancements in
Retrieval Technology as Related to Information Systems. AGARD-CP-201. pp.
12.1-12.7, Technical Information Panel, AGARD, NATO, Washington D.C.
GED 1.0 Documentation Olson WorU Ecotyetema
A05-3
-------
"Olson, J.S., 1982. "Earth's Vegetation and Atmospheric Carbon Dioxide," in Carbon
Dioxide Review: 1982. Ed. by W.C. Clark, Oxford University Press, New York,
pp. 388-398. (Incorporated in NDP-017, cited above)
Olson, J. S., and J. A. Watts. 1982. Map of Major World Ecosystem Complexes Ranked
According to Carbon in Live Vegetation, 1982. Map insert in: W. C. Clark (ed.),
Carbon Dioxide Review: 1982, Oxford University Press, New York, (Also in Olson
et al. 1983)
Olson, J.S. and J.A. Watts, 1982. "Major World Ecosystem Complexes Ranked by Carbon
in Live Vegetation." Oak Ridge National Laboratory, Oak Ridge, Tennessee
(map).
Olson, J.S., J.A. Watts, and L.J. Allison. 1985. Major world ecosystem complexes ranked
by carbon in live vegetation: A Database. NDP-017, Carbon Dioxide Information
Analysis Center, Oak Ridge National Laboratory, Oak Ridge, Tennessee.
References used in updating from WE1.2 (CDIAC Data Package NDP-017) to WE1.4:
Barth, H. —. Mangroves. In: D.N. Sen and K.S. Rajpurohit (eds.), Contributions to the
Ecology of Halophytes. Dr. W. Junk, Publishers, The Hague (in press).
Bazilevich, N.I. 1974. Energy flow and biogeochemical regularities of the main world
ecosystems, pp. 182-186. In: Structure, Functioning and Management of Ecosystems.
Centre for Agricultural Publishing and Documentation, Wageningen, The
Netherlands.
Bazilevich, N.I., and L. Ye Rodin. 1967. Maps of productivity and the biological cycle in
the Earth's principal terrestrial vegetation types. Izv. Vses. Geogr. Obschestva.
999(3):190-194.
Bazilevich, N.I., and L. Ye Rodin. 1971. Geographical regularities in productivity and the
circulation of chemical elements in the Earth's main vegetation types. Sov. Geogr.:
Rev. and Transl. 12:24-53.
Bazilevich, N.I., and A.A. Titlyanova. 1980. Comparative studies of ecosystem function,
pp. 713-758. In: A.I. Breymeyer and G.M. Van Dyne (eds.), Grasslands, Systems
Analysis and Man. Cambridge University Press, Cambridge, United Kingdom.
Bazilevich, N.I., T.K. Gordeeva, O.V. Zalensky, L. Ye Rodin, and J.K. Ross. 1969.
Obschchie Teoreticheskie Problemi Biologicheskoi Produktivnosti. Nauka,
Leningrad.
Bazilevich, N.I. Pers. comm. 1968-1978. (1968 Symposium on Roots Systems and
Rhizosphere Organisms, Moscow, Leningrad, Dushanbe; 1974 World Soils
Congress, Moscow; and her 1978 paper read by J. Olson to International
Ecological congress, the Hague, Netherlands.
Brown, S., and A.E. Lugo. 1981. The role of the terrestrial biota in the global C02 cycle.
Preprints 26:1019-1025. In: Report of the Symposium on the Carbon Dioxide
Issue. American Chemical Society, Division of Petroleum Chemistiy, New York.
Briinig, E.F. 1969. On the limits of vegetable productivity in the tropical rain forest and
the boreal coniferous forest. J. Indian Bot. Soc. 46:314-322.
Duvigneaud, P. (ed.). 1971. Productivity of Forest Ecosystems. UNESCO, Paris.
GED 1.0 Documentation Olson World Ecosystems
A05-4
-------
Gerasimov, E.P., et al. (eds.). 1964. Fiziko-geograficheskii Atlas Mira (Physical-Geographic
Atlas of the World). USSR Academy of Science, Moscow, (also cited as Fillipov)
Goward, S. N., C. J. Tucker and D. G. Dye. 1985. North American vegetation patterns
observed with the NOAA-7 advanced very high resolution radiometer. Vegetatio
64: 3-64.
Grubb, P.J. 1977. Control of forest growth and distribution on wet tropical mountains.
Ann. Rev. Ecol. Syst. 8:83-107.
Henderson-Sellers, A., M. F. Wilson, G. Thomas, and R. E. Dickinson. 1986. Current
Global Land-Surface Data Sets for Use in Climate-Related Studies. NCAR
Technical Notes, NCAR/TN-272+STR, National Center for Atmospheric Research,
Boulder, Colorado
Hobbs, R., and H. Mooney (eds.). 1990. Remote Sensing and Biosphere Functioning.
Ecological Studies. Springer-Verlag, New York.
Koomanoff, V. A. 1988. Analysis of Global Vegetation patterns: A Comparison Between
Remotely Sensed Data and a Conventional Map. Report 890201 of Laboratory for
Global Remote Sensing Studies, Geography, University of Maryland, College Park
MD.
Kiichler, A.W. 1978. Natural vegetation map. pp. 16-17. In: E.B. Espenshade, Jr., and J.L.
Morrison (eds.), Goode's World Atlas, 15th Edition. Rand McNally & Company,
Chicago.
Loveland, T. R., J. W. Merchant, D. O. Ohlen, and J. F. Brown. 1991. Development of a
land-cover characteristics database for the conterminous United States. Photogram.
Engineering and Remote Sensing 57:1453-1463.
Muller, J.-F. 1992. Geographical distribution and seasonal variation of surface emissions
and deposition velocities of atmospheric trace gases. J. Geophysical Research 97:
3787-3804.
Rodin, L. Ye, and N.I. Bazilevich. 1967. Production and Mineral Cycling in Terrestrial
Vegetation. Oliver and Boyd, Edinburgh. [Translated from L. Ye Rodin and N.L
Bazilevich, 1965. Dynamics of the Organic Matter and Biological Turnover of Ash
Elements and Nitrogen in the Main Types of the World Vegetation. Nauka,
Moscow-Leningrad (in Russian).]
Rodin, L. Ye, and N.I. Bazilevich. 1968. World distribution of plant biomass. pp. 45-52.
In: F.E, Eckardt (ed.), Functioning of Terrestrial Ecosystems at the Primary
Production Level. UNESCO, Paris.
Rowe, J.S. 1972. Forests of Canada. Canadian Forestry Service, Ottawa.
Schmithiisen, J. 1976. Atlas zur Biogeographie. Meyers Grosser Physischer Weltatlas,
Band 3, Bibliographisches Institute, Manheim / Wien/Zurich, Switzerland.
Sollins, P., D.E. Reichle, and J.S. Olson. 1973. Organic matter budget and model for a
southern Appalachian Liriodendron forest. EDFB/IBP-73/2. Oak Ridge National
Laboratory, Oak Ridge, Tennessee.
Specht, R.L. 1981. Structural attributes - foliage projective cover and standing biomass.
In: A.N. Gillison and D.J. Anderson (eds.), Vegetation Classification in the
Australian Region. Australian National University Press, CSIRO, Canberra.
GED 1.0 Documentation Olsort World Ecosyatenu
A05-5
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DATA-SET FILES
LOCATION
HMB
NUMBER
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OWE13A.DOC
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GED 1.0 Documentation OUon World Ecosystem*
A05-6
-------
FILE DESCRIPTION
DATA ELEMENT: World Ecosystems (WE1.3A)
STRUCTURE: Raster Data File: 30-minute 720x360 GED grid (see User's Guide)
SERIES: none
SPATIAL DATA FILES:
OWE13A.DOC
file title
Olson World Ecosystems Version 1.3A
data type
byte
file type
binary
columns
720
rows
360
ref. system
lat/long
ref. units
deg
unit dist.
1.0000000
min. X
-180.0000000
max. X
180.0000000
min. Y
-90.0000000
max. Y
90.0000000
pos'n error
unknown
resolution
0.5000000
min. value
0
max. value
29
value units
classes
value error
unknown
flag value
none
flag def'n
none
legend cats
: 30
Legend:
category
0
0
category
1
1
category
2
2
category
3
3
category
4
4
category
5
5
category
6
6
category
7
7
category
8
8
category
9
9
category
10
10
category
11
11
category
12
12
category
13
13
category
14
14
category
15
15
category
16
s 16
category
17
: 17
category
18
: 18
OCEAN/SEA Oceans, Seas (including Black Sea)
CONIFOR Conifer Forest
BRODLFOR Broadleaf Forest: temperate, subtropical drought
MIXEDFOR Mixed Forest: conifer/broadleaf; so. Boreal
GRASSHRB Grassland +/- Shrub or Tree
TROPICFR Tropical/subtr. Forest: montane, seasonal,
rainforest
SCRUBWDS Scrub +/- Woodland &/or fields
(evergreen/decid.)
SEMIDTUN Semidesert shrub/steppe; Tundra (polar, alpine)
FLDWDSAV Field/Woods complex 6/or Savanna, tallgrass
NORTAIGA Northern Boreal Taiga woodland/tundra
FORFDREV Forest/Field; Dry Evergreen broadleaf woods
WETLAND Wetlands: mires (bog/fen); marsh/swamp +/-
mangrove
DESERTS Desert: bare/alpine; sandy; salt/soda
SHRBTRST Shrub/Tree: succulent/thorn
CROPSETL Crop/Settlement (irrigated or not)
CONIFRFC Conifer snowy Rainforest, coastal
not used
not used
not used
GED 1.0 Documentation Olson World Ecotytim*
A05-7
-------
category 19
category 20
category 21
category 22
category 23
category 24
category 25
category 26
category 27
category 28
category 29
19 MANGROVE Mangrove/wet forest/thicket + tidal flat
20 WALANCST Water (-51-90%) & Land, Coast/hinterland
complexes
21 not used
22 not used
23 ISLFRING Island or Fringe land (91-99% water)
24 LANDWATR Land/Water (-21-50%) complexes
25 ICE Ice: Glaciers & emerging rocks near fringe
26 POLARDES Polar Desert
27 WTNDMHTH Wooded Tundra Margin; Heath/moorland
28 not used
29 INLDWATR Inland Water bodies (including Caspian Sea)
Notes:
(1) Comment: 14 Major Ecosystem classes and 8 fringe classes, plus Ocean
(2) Lineage: Derived from WE1.4D by editing, aggregating classes, and modal
filtering to .5-degree. Also used FNOC % water for fringe classes (FNOCWAT in
Chapter A13).
(3) Completeness: .5-degree coverage complete for land areas, based on WE1.4D
(4) Consistency : All values represent spatial dominance at ,5-degree
GED1.0 Documentation Olton Worid Ecotyatenu
A05-8
-------
DATA ELEMENT: World Ecosystems (WE1.4D)
STRUCTURE: Raster Data File: lO-minute 1024x2160 GED grid (see User's Guide)
SERIES: none
SPATIAL DATA FILES:
file title
data type
file type
columns
rows
ref.
ref.
system
units
unit dist.
min. X
max.
min.
max.
X
Y
Y
pos'n error
resolution
min. value
max. value
value units
value error
flag value
flag def'n
legend cats
OWE14D.DOC
Olson World Ecosystem Classes Version 1.4D
byte
binary
2160
1080
lat/long
deg
1.0000000
-180.0000000
180.0000000
-90.0000000
90.0000000
unknown
mixed .1671.5
0
73
classes
unknown
none
none
74
Legend:
category
0
Waters, inc]
category
1
1
CCX
category
2
2
SSG
category
3
3
Not iised
category
4
4
Not used
category
5
5
Not used
category
6
6
TBE
category
7
7
Not used
category
8
8
DMB
category
9
9
Not used
category
10
10
Not used
category
11
11
Not used
category
12
12
Not used
category
13
13
Not used
category
14
14
Not used
category
15
15
Not used
category
16
16
{BBS}
category
17
17
ICE
category
18
18
Not used
category
19
19
Not used
category
20
20
SRC
category
21
21
MBC
including Ocean and Inland Waters
City complexes--being added for MM4 type cat.l
Short or Sparse Grass/shrub of semiarid climates
Temperate/Tropical-montane Broadleaf
Evergreen covers warm temperate or montane
broadleaf evergreen forest [Africa only]
Desert, mostly bare stone, clay or sand
Broadleaf Evergreen Scrub, commonly with #46
and #47
Antarctic ice cap
Snowy, rainy coastal conifer
Main Boreal conifer forest, closed or open
GED 1.0 Documentation OUon World Eco*y»tm*
A05-9
-------
category 22 : 22 SNB Snowy non-Boreal conifer forest
category 23 : 23 CDF Conifer/deciduous, snow persisting in winter
category 24 : 24 TBC Temperate Broadleaf/Conifer forest: with
deciduous and/or evergreen hardwood trees
category 25 : 25 SDF Snowy Deciduous Forest, i.e. summergreen
(=cold-dec iduous) types
category 26 : 26 TBF Temperate broad-leaf forest: deciduous,
semideciduous, and some temperate-subtropical
broadleaf evergreen types that are least
active in winter,
category 27 : 27 NSC Non-snowy conifer forest
category 28 : 28 TMC Tropical montane complexes, typically
evergreen, including dwarfed ("elfin")
forest, opening to grass, or tall or short
forbs (puna, paramo)
category 29 : 29 TBS Tropical Broadleaf Seasonal, with dry or cool
season
category 30 : 30 CFS Cool Farmland & Settlements, more or less snowy
category 31 : 31 MFS Mild/hot farmland & settlements
category 32 : 32 RGD Rain-green (drought-deciduous) or very
seasonal dry evergreen forests to open
woodlands, very frequently burned,
category 33 : 33 TRF Tropical RainForest
category 34 : 34 Not used
category 35 : 35 Not used
category 36 : 36 PRA Paddy rice and associated land mosaics
category 37 : 37 WCI Warm/hot cropland, Irrigated extensively
category 38 : 38 CCI Cool cropland with Irrigation of variable extent
category 39 : 39 CCP Cold cropland and pasture, irrigated locally
category 40 : 40 CGS Cool grass/shrub, showy in most years
category 41 : 41 MGS Mild/warm/hot grass/shrub
category 42 : 42 CSM Cold steppe/meadow +/- larch woods (in
Siberia), scrub (Bering sea) or tundra
(Tibetan highland)
category 43 : 43 SGW Savanna/Grass, seasonal woods: Trees or
shrubs above grass groundcover may be
interspersed on many scales in savana belts
of varying drought duration and high fire
frequency
category 44 : 44 MBF Mires include peaty Bogs and Fens (mostly in
high latitudes)
category 45 : 45 MOS Harsh or other swampy wetlands include
various transitionsto or mixtures with trees
category 46 : 46 MES Mediterranean-type Evergreen (mostly)
broadleaved Scrub and forest relics
category 47 : 47 DHS Dry or highland scrub, or open woodland
category 48 : 48 DEW Dry Evergreen Woodland or low forest, mapped
mostly in interior Australia and South
America
category 49 : 49 HVI Hot-mild volcanic "islands" (Galapogos), with
local denser forest on some older lava flows
but wide areas of sparse cover on recent
lavas)
category 50 : 50 SDB Sand Desert, partly Blowing dunes
category 51 : 51 SDS SemiDesert/Desert Scrub/succulent/sparse grass
category 52 : 52 CSS Cool/cold shrub semidesert/steppe
category 53 : 53 TUN Tundra (polar, alpine)
GED 1.0 Documentation OUon World Eeo&ystem*
A05-10
-------
category
54 :
54
TER
category
55 :
55
SFW
category
56 :
56
FFR
category
57 :
57
SFF
category
58 :
58
FWG
category
59 :
59
STW
category
60 :
60
SDT
category
61 ;
61
LT
category
62 :
62
NMT
category
63 :
63
WTM
category
64 :
64
HMW
category
65 :
65
CNW
category
66 :
66
CNE
category
67 :
67
CSE
category
68 :
68
CSW
category
69 :
69
PDL
category
70 :
70
GLA
category
71 :
71
SSF
category
72 :
72
MSM
category
73 :
73
ISL
Temperate Evergreen Rainforest (e.g., in Chile)
Snowy Field/Woods complex
Forest/Field complex with Regrowth after
disturbances, mixed with crops and/or other
non-wooded lands
Snowy Forest/Field, commonly openings are
pasture and/or mires
Field/Woods with Grass and/or Cropland
Succulent and Thorn Woods or scrub is widespread
Southern Dry Taiga or similar aspen/birch
with northern and/or mountain conifers
Larch Taiga with deciduous conifer
Northern or maritime taiga typifies a wide
latitude belt or a narrow altitude belt above
denser forest or woodland
Wooded tundra margin or mountain scrub/meadow)
Heath and Moorland, Wild or artificially
managed, as by burning and/or grazing. Can
include wetland (#44-45) interspersed with
drier heath, with dwarfed or taller, commonly
dense scrub on peat or sand
Coastal: Northwest quadrant near most land
Coastal: NorthEast quadrant near most land
Coastal: SouthEast quadrant near most land
Coastal: Southwest quadrant near most land
Polar desert with rock Lichens, locally
abundant or productive (even between mineral
grains) but provide little food. Animals
import residues for localized humus
Glaciers in polar or alpine complex, with
rock fringes
Salt/soda flats desert playas, occasionally
with intermittent lakes
Mangrove and non-saline swamps and tidal
Mudflats [Africa only]
Islands and shore waters in oceans and/or
lakes [Elba Island]
GED 1.0 Documentation Ol$on World Ecotyttem
A05-11
-------
Notes:
(1) Data represent mixed 0.5-degree and 10-minute classes (see WE1.4DR)
(2) In refining low vegetation classes (desert, etc.) an average of the monthly MG-GVI
data over 3 years was used. The actual multi-year average is not provided for
intercomparison, however it can easily be reproduced from the Characteristic
Month Averages in Chapter A01.
(3) In refining coastal values, an "ocean mask" was used, which was derived from the
FN0C elevation data-set. Since this mask itself may have errors, the mask is
provided with the FNOC data-set for intercomparison (see Chapter A13).
(4) comment: not all classes are used.
(5) comment: This version is a refinement of WEI .4. Changes include:
(1) Trimmed desert and bare ground using AVHRR/GVI data
(2) Trimmed coastline areas using elevation data
(3) Added Elba Island
(4) Corrected mis-located tropical montane classes
(5) Other miscellaneous corrections
(6) The data file named OWE14R provides an overlay to determine which cells
contain 10-minute and 30-minute data.
(7) Derived from Olson World Ecosystems Version 1.4 (prototype)
(8) Version 1.4 was an extension of Version 1.2, previously distributed by CDIAC,
Oak Ridge National Laboratory
(9) 10-minute updates are incomplete. Complete coverage of land areas is achieved
by a mix of 10-min and 30-min classes.
GED 1.0 Documentation Olson World Ecosystems A05-12
-------
DATA ELEMENT: World Ecosystems (WE1.4DR)
STRUCTURE: Raster Data File: 10-minute 1024x2160 GED grid (see User's Guide)
SERIES: none
SPATIAL DATA FILES:
OWE14DR.DOC
file title
Resolution codes for OWE1.4D
data type
byte
file type
binary
columns
2160
rows
1080
ref. system
lat/long
ref. units
deg
unit dist.
1.0000000
min. X
-180.0000000
max. X
180.0000000
min. Y
-90.0000000
max. Y
90.0000000
pos'n error
unknown
resolution
0.1666667
min. value
0
max. value
2
value units
classes
value error
unknown
flag value
none
flag def'n
none
legend cats
3
Legend:
category 0 : 30' data
category 1 : 10' edits
category 2 : 10' residuals from edited regions
Notes t
(1) Produced from edits of WE1.4D
(2) This layer is provided as an index or overlay to determine which values in the
WE1.4D have 10-minute spatial meaning and which have 30-minute spatial
meaning. It can be used to divide the 10-minute and 30-minute data into separate
data layers, if desired.
(3) "Residuals" are 10-minute cells within a 30-minute major ecosystem type cell that
were "orphaned" when other cells in the 30-minute region were edited. They are
coded as having 10-minute spatial interpretation only if they cover less than 1/2
the 30-minute cell (i.e., "non-modal")
GED 1.0 Documentation Okon WerW Ecomptem
A05-13
-------
SOURCE ELEMENT: World Ecosystems (WE1.4)
STRUCTURE: Raster Data File: 10-minute 1024x2160 GED grid (see User's Guide)
SERIES: none
SPATIAL DATA FILES:
OWE14.DOC
file title
Olson Ecosystem Classes Version 1.4
data type
byte
file type
binary
columns
2160
rows
1080
ref. system
lat/long
ref. units
deg
unit dist.
1.0000000
min. X
-180.0000000
max. X
180.0000000
min. Y
-90.0000000
max. Y
90.0000000
pos'n error
unknown
resolution
0.1666667
min. value
0
max. value
72
value units
classed
value error
unknown
flag value
none
flag def'n
none
legend cats
73
Legend:
category 0
category 1
category 2
category 3
category 4
category 5
category 6
category 7
category 8
category 9
category 10
category 11
category 12
category 13
category 14
category 15
category 16
category 17
category 18
category 19
category 20
category 21
category 22
category 23
category 24
0
1
CCX
2
SPV
3
Not used
4
Not used
5
Not used
6
TMT
7
Not used
8
DMB
9
Not used
10
Not used
11
Not used
12
Not used
13
Not used
14
Not used
15
Not used
16
Not used
17
ICE
18
Not used
19
Not used
20
SRC
21
MBC
22
SNB
23
CDS
24
SED
Waters, including Ocean and Inland Waters
City complexes--being added for MM4 type cat.l
Shortgrass prairie variant of 40 or 41
Temperate to montane tropical (major forest and
woodland)
Desert, mostly bare
Antarctic ice, land or grounded shore ice
Snowy, rainy coastal conifer (with alder etc.)
Main Boreal conifers
Snowy non-Boreal conifer forest
Conifer/deciduous, snow persisting in winter
(semi) Evergreen/deciduous, little/no snow
GED 1.0 Documentation Olson World Ecosystems
A05-14
-------
category
25 :
; 25
SDF
Similar to 26, snow persisting in winter
category
26 ;
: 26
TDP
Temperate ~deciduous forest, little or no snow
category
27 :
: 27
NSC
Non-snowy conifer forest
category
28 :
: 28
TMC
Tropical montane complexes (tree & other)
category
29 :
: 29
TSF
Tropical seasonal forest (-evergreen...) (major
forest/woodland)
category
30 :
: 30
CFS
Cool farmland & settlements (-snowy)
category
31 i
: 31
MFS
Mild/hot farmland & settlements
category
32 :
: 32
RGD
Rain-green (drought-deciduous) (major forest and
woodland)
category
33 ;
: 33
TRM
Tropical rainforest (major forest and woodland)
category
34
: 34
Not used
category
35
: 35
Not used
category
36
: 36
PRA
Paddy rice and associated lands (part anaerobic)
category -
37 i
: 37
WCI
Warm/hot crops with extensive irrigation
category
38
: 38
CCI
Cool crops with irrigation (variable extent)
category
39
: 39
CCP
Cold crops, pasture, irrigation -local
category
40
: 40
CGS
Cool (snowy) grass/shrub (including much 2)
category
41
: 41
MGS
Mild/warm/hot grass/shrub
category
42
: 42
CSM
Cold steppe/meadow + /- larch, scrub
category
43
: 43
STB
Savanna, mostly tallgrass + bush fallow/woods
category
44
: 44
MAG
Mire (acid bog &/or groundwater-fed fen), -cold
peatland (or muck): sphagnum, grass-like, and/or
dwarf shrub or mire tree vegetation
category
45
: 45
MOS
Marsh or other swamp (warm-hot) salty/freshwater
marsh, thicket, -flooded woods
category
46
: 46
MET
Mediterranean evergreen tree/scrub (winter rain)
category
47
: 47
ODH
Other dry or highland scrub/tree (juniper, etc.)
category
48
: 48
EAQ
Eucalyptus or Acacia, quebracho, saxaul
category
49
: 49
HVI
Hot-miId volcanic "islands" (variable veg.)
category
50
: 50
SDB
Sand desert, partly blowing
category
51
: 51
ODS
Other desert and semidesert
category
52
: 52
CSS
Cool/cold shrub semidesert/steppe (sagebrush...)
category
53
: 53
TUN
Tundra (polar, alpine)
category
54
: 54
TRC
Temperate rainforest (+/- conifer) (major forest
and woodland)
category
55
: 55
SCW
Similar to 58: cool-cold (-persistent snow)
category
56
: 56
RWC
Regrowing woods + crop/grass
category
57
: 57
SWC
Similar to 56: cool-cold (-persistent snow)
category
58
: 58
GCW
Grass/crop + <40% woods: warm, hot
category
59
: 59
STW
Succulent and thorn woods
category
60
: 60
SDT
Southern dry taiga (and other aspen/birch, etc.)
category
61
: 61
SLT
Siberian larch taiga [partly other taiga 21]
category
62
: 62
NMT
Northern or maritime taiga/tundra
category
63
: 63
WTM
-Wooded tundra margin (or mt. scrub, meadow)
category
64
: 64
HMW
Heath and moorland, wild or artificial (-grazed)
category
65
: 65
NW
NW quadrant near most land (...mainland, large
island, ...)
category
66
: 66
NE
NE quadrant near most land (peninsula, small
islands, ...)
category
67
: 67
SE
SE quadrant near most land (...or isthmus)
category
68
: 68
SW
SW quadrant near most land
category
69
s 69
PDL
Polar desert (rock lichens)
category
70
: 70
GLA
Glaciers (other polar and alpine)
category 71
: 71
SSF
Salt/soda flats (playas, lake flats rarely -wet)
category
72
: 72
MSM
Mangrove swamp/mudflat [Africa only]
GED 1.0 Documentation Olson World Ecosystems A05-15
-------
NOTES:
(1) Data represent mixed 0.5-degree and 10-minute classes
(2) This data set is the one that was contributed for the 1992 International Space Year
(ISY) Global Change Encyclopedia (GlobeScope). It is included here for
comparison to the subsequent versions produced by Jerry Olson and incorporated
into GED Version 1.0, but also to provide a link between these newer versions and
the ISY discs. Both data and legends have changed in the newer versions.
GED 1.0 Documentation OIson World Ecosystems
A05-16
-------
DATA INTEGRATION AND QUALITY
fTU ..._ .... _
Jerry Olson
Global Patterns Company
Lenoir City, Tennessee
John J. Kineman, Mark A. Ohrenschall, and Jeffrey D. Colby
NOAA Natioinal Geophysical Data Center
Boulder, Colorado
PREFACE (Jerry Olson, April 22,1992)
Several years spent before and after my 1985 early retirement from Oak Ridge National
Laboratory (ORNL) in Tennessee brought together ideas and data on global patterns of
ecological systems (ecosystems). Patterns previously mapped by large computers (Olson
et al. 1983,1985) are now made available, with improvements, for personal computers
(PCs).
Parts of 3 years in Europe (1985-88) and in Western States and the Pacific (1988-91)
helped improve my World Ecosystems database. It was licensed for the National Center
for Atmospheric Research (NCAR), in Boulder, Colorado, to help set the parameters for
calculating air-landscape interaction in a new Community Climate Model (CCM2, in
NCAR's Climate and Global Dynamics Division, CGD). Soon NCAR's Atmospheric
Chemistry Division (ACD) started using the 1989 version for estimating chemical
contributions from plants or fires to air (Mtiller 1992).
In Boulder, I also started refining the half-degree resolution of my previous worldwide
grid (WEI .2: 720 columns x 360 rows of picture elements or pixels to 10-minute
resolution, initially for a pilot project chosen for Africa by the World Data Center-A).
WDC-A's host, the National Geophysical Data Center of the National Oceanic and
Atmospheric Administration (NGDC/NOAA), meanwhile was distributing other data,
using the larger capacity of compact disks.
During the beta test (outside checking) of NOAA's Global Ecosystem Database (GED) in
late 19911 compared my mapping with the index of greenness estimated from NOAA's
meteorological satellites and with GIS layers contributed by others. The combined
features WE1.4D show more than any data layer could alone about global patterns. But
they also emphasize a problem we face repeatedly-striving for breadth of global
coverage while working toward depth of data layers, and eventually of understanding,
and of actions to improve our world. The grouping of types in WEI 3A (section 2 below)
is a step toward handling such breadth and depth together.
GED 1.0 Documentation Olson World Ecosystems
A05-17
-------
Acknowledgement: I thank Lee Stanley of GPC and Mark Ohrenschall, John Kineman,
and David Hastings of NGDC/NOAA and WDC-A. We used Idrisi Geographic
Information System (GIS) software version 3.0 from Ron Eastman, Clark University,
Worcester, Massachusetts, 01610; version 4.0 was not available during this work.
World Ecosystems WE is a Trademark and Global Patterns trade name of Global Patterns
Company of Roane County,Tennessee. Please contact the author for further information
or advanced or trial versions of WE or further documentation. These working versions of
the World Ecosystems data-set are released for public testing by GPC and for educational
uses, with the understanding that it is incomplete. Improvements by users may be
offered to GPC for "in kind" trade as part of the license fee for later versions that are not
released to the public domain, i.e. for research and monitoring groups for whom the
most current or tested version is important for their work.
INTRODUCTION
This report explains how the World Ecosystem data-set version 1.4D (WE1.4D), and
version 1.3A (WEI .3A) were produced from previous versions, and how they describe
land parts of Earth's sphere of life, or Biosphere.
Detailed ecosystem types (0-73) in WE1.4D, at both 10-minute and 30-minute resolution,
are related to the broader Main Groups of ecosystem types (0-29) in WEI .3A, at 30-
minute resolution. The land Groups include forests of conifer, broadleaved, mixed, and
mostly tropical moist broadleaved (mostly evergreen) types. Other mixtures include:
grass-shrub, shrub-tree, semidesert and tundra, field/woods and savanna, northern taiga,
forest/field and dry evergreen woods, wetlands, desert, succulent/thorn woods, crop
and settlements, and other (ice and fringe) types.
Since WE1.4D incorporates data at mixed resolutions (10 and 30 minutes lat/long), a
separate data element (OWE14DR) is provided with resolution codes for the main file
(OWE14D). A special palette file (OWE13A.PAL) is provided for the WEI .3A data,
mostly for convenience in recognition of some conventional color assignments.
HISTORY OF THE OLSON DATA SET
The original version (1.0) of the Olson Ecosystems data set was produced for the DOE
Carbon Dioxide Information and Analysis Center in Oak Ridge Tennessee by Jerry S.
Olson, Julia A. Watts, and Linda J. Allison. Reprints of the Primary Documentation from
this work are included on disc (see Reprint Files, above), and should be consulted for
detailed information on the creation of these data and their use of estimating carbon
content.
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DATA UPDATING PROCEDURES FOR THE 1991 PROTOTYPE (WE1.4)
During the summer of 1989, Jerry Olson, Lee Stanley and research assistants from the
National Geophysical Data Center updated the data set, "Major World Ecosystem
Complexes Ranked by Carbon in Live Vegetation: A Database." The results of this
update have been incorporated into Olson World Ecosystem WEI .4.
Data were revised at both 30 and 10 minute grid cells. Changes were first made for the
30 minute data between 20 degrees West and 70 degrees East. In addition, modifications
were made to limited portions of the United States data. Revisions were made in the
following ecological classes:
(1) tropical forest (type 33)
(2) polar deserts (type 69)
(3) ice (type 70)
(4) a few areas of mangrove/tropical swamp forest (type 72)
Updates for the United States were quite limited and affected mostly the islands and
coastlines of Alaska. To a lesser extent changes were made along the western and
eastern coastlines of the lower 48 states.
Modifications at 10 minute resolution were numerous, but were confined to the African
continent and some coastlines. They included changes in tropical montane complexes
(type 28), boradleaved evergreen forest types at high altitudes with cool climates despite
tropical latitudes (type 6), for example Cameroon, Ethiopia, and other areas of East
Africa and some in the Atlas Mountains; mangrove tropical swamp forests (type 72), and
coastlines. Salt/soda flats (type 71) were not systematically reviewed but received
sample editing.
SUBSEQUENT EDITING FOR WE1.3A AND WE1.4D
Greenness indices from Advanced Very High Resolution Radiometer (AVHRR) satellite
data were used in certain desert and coastal ecosystems. WE1.4D is a first step toward
global resolution at 10 arc-minutes, replacing a test version called GOLSON in GED
Prototype (Version 0.1). Most of the main land cover complexes are still effectively
mapped at 3C (half-degree) scale in WE1.4D. Ten arc-minute (100 improvements are
mostly limited to areas with low greenness indices from NOAA satellites and, in Africa,
to mangrove (type #72) and mountain complexes (#6,28). Conditions of high and
intermediate greenness are important, but have quite different meanings in different
parts of the biosphere.
The quality of basic geographic data is very uneven from various parts of the world. The
computer media becoming available from the NOAA National Geophysical Data
Center/World Data Center-A (WDC-A) and from Global Patterns Company (GPC)
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provide worldwide coverage of many features that can be quantified for interpreting
changes of climate and atmospheric chemistry and many feedbacks on life.
Ten-minute mapping of certain landscape types was donated in 1989 for NGDC's Africa
Pilot Project for the IGBP, as one testing step of GPC. Yet comparable refinement to 10'
has not yet been done evenly on any continent. The main patterns of the Olson World
Database for the NOAA CD-ROM in 1992 (GED) still have the same half-degree
resolution as the 1982 printed map of Olson and Watts (~75 x 150 cm: enclosed with and
documented by Olson et al. 1983, and the 1985 re-release of the same report with
computer-readable data by Oak Ridge National Laboratory, ORNL). ORNL's Carbon
Dioxide Information and Analysis Center (CDIAC contact: Tom Boden) will continue to
distribute such maps, and the Olson et al. (1985) Numeric Data Set 017, which is called
WEI .2 in the Global Patterns numbering series.
MAIN LANDSCAPE GROUPS AND ECOSYSTEM TYPES
The documentation file OWE14D.DOC gives the detailed category legend for WE1.4D,
modified slightly from that of the test version (GOLSON) prepared in 1989 for testing in
1990-91. Closely related types from WE1.4D are put in GROUPS, with Group numbers, in
the two sections below (A-main types, and B-selected "fringe" types). These MAJOR
GROUPS and numbers were used to create a new 30-minute data file (WE1.3A).
The narrower type numbers of WE1.4D are listed below each Major Group description.
Brackets [] enclose those legend numbers that are still applied very unevenly. Braces {}
foretell more subdivisions, not yet used or even explained here. This list is expanded
slightly from previous ORNL reports (Olson et al. 1983,1985), with additions between 0
and 19, and above 71. Readers should consult GPC and references just cited for more
explanation. Readers should be forewarned that the Canadian Centre for Remote Sensing
(CCRS) compact disk will use an intermediate version, renumbered to omit certain
numbers that were deliberately skipped here. Despite potential confusion in numbering
sequence between CCRS and other releases, the three-LETTER mnemonic codes given
below between old (ORNL/GPC/NOAA) numbers and titles should clarify the match
with the ISY Global Change Encyclopedia (GeoScope).
The Group sequence below is arranged to take advantage of a standard IBM color palette
for either the Enhanced Graphic Adapter (EGA), or Video Graphics Adapter (VGA).
Thus, some color conventions (e.g. purple for tropical moist forest) follow the UNESCO
vegetation committee suggestions or our older ORNL printed map (Olson and Watts
1982). In most printing, black on the video screen (0) is replaced with pale background
for the ocean (e.g. pale cyan). A 16-color IDRISI color palette is provided that retains the
IBM color scheme with this minor change to the background (OWE13A.PAL).
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MAJOR GROUP DESCRIPTION
(OWE13A)
A. Main LAND GROUPS of Ecosystem Complexes (1-14):
(0) SEAS Oceans, Mediterranean Sea, Black Sea
FORESTS:
(1) CONIFOR CONIfer FORest here stands for all complexes dominated by
coniferous trees (evergreen or deciduous, in snowy climate or
not), except for the coastal fringe below (i.e. group 15 type 20 in
section 2B):
WE1.4D classes grouped here:
#21 MBC Main Boreal Conifer forest, closed or open;
#22 SNB Snowy Non-Boreal conifer forest;
#27 NSC Non-Snowy Conifer forest.
(2) BRODLFOR BROADLEAF FORest of temperate and seasonally dry
-subtropical (rain-green or partly drought-deciduous) groups (#32
for the latter).
WE1.4D classes grouped here:
#25 SDF Snowy Deciduous Forest, i.e. summergreen (= cold-deciduous)
types;
#26 TBF Temperate Broadleaf Forest: deciduous, semidetiduous, and some
temperate-subtropical broadleaf evergreen types that are least
active in winter. (The latter could be shifted to type #6 and
perhaps to group 5 later, in order to get more broadleaf evergreen
types together.)
[#61 TBE Temperate/Tropical-montane Broadleaf Evergreen covers warm
temperate or montane broadleaf evergreen forest, so far mostly in
Africa where our pilot test for 10' started.
#32 RGD Rain-green (Drought-deciduous) or veiy seasonal dry evergreen
forests to open woodlands, very frequently burned.
(3) MDCEDFOR MIXED FORest here includes not only deciduous-conifer
mixtures, within stands and as mosaics over the landscape, but
many gradations toward broadleaved evergreen. Conifers are
common, but often uneven; native and/or planted.
WE1.4D classes grouped here:
#23 CDF Conifer/Deciduous Forest: snow persisting in winter;
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#24 TBC Temperate Broadleaf/Conifer forest: with deciduous and/or
evergreen hardwood trees;
[#54] TER Temperate Evergreen Rainforests, e.g. in Chile.
For simplicity, southern Boreal (= taiga in Russian) deciduous mixtures with
aspen, birch, and/or larch as well as evergreen conifers are included here:
#60 SDT Southern Dry Taiga, or similar aspen/birch with northern and/or
mountain conifers;
#61 LT Larch Taiga with deciduous conifer.
(4) GRASSHRB GRASS-SHRUB-HERB complexes vary widely in structure,
precipitation and temperature. Few trees (mostly sparse, planted,
or streamside/ravine patches, if any) break the open horizon.
Cropland, especially dryland cereal grains or local irrigation, can
be important economically, but is a minor fraction of total land
cover/use in most years.
WE1.4D classes grouped here:
[#2] SSG Short or Sparse Grass/shrub of semiarid climates;
#40 CGS Cool Grass/Shrub, snowy in most years
#41 MGS Mild/warm/hot Grass/Shrub,
#42 CSM Cold Steppe/Meadow, +/- larch woods (in Siberia), scrub (Bering
sea) or tundra (Tibetan highland). (This class might be regrouped
with the tundra margin group, especially when better defined at
10' resolution.)
(5) TROPICFR = TROPICAL/subtropical moist or Broadleaf Humid FORest. Most
are evergreen but deciduous forms increase in the subtropics,
especially with extreme monsoon droughts.
WE1.4D classes grouped here:
#28 TMC Tropical Montane Complex, typically evergreen, including
dwarfed ("elfin") forest, opening to grass, or tall or short forbs
(puna, paramo) above timberline;
#29 TBS Tropical Broadleaf Seasonal, with dry or cool season;
#33 TRF Tropical RainForest.
(6) SCRUBWDS SCRUB-WOODS Complexes, often with grass or crops locally,
tend to have a dry season and/or pronounced fire. Trees are not
always rare, but may be short or open-grown. The bigger ones
tend to cluster on favorable substrate or terrain, or near places
where fire starts or spreads less often.
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WE1.4D classes grouped here:
{#16} BES Broadleaf Evergreen Scrub, commonly with the following
#46 MES Mediterranean-type Evergreen (mostly) broadleaved Scrub and
forest relics;
#47 DHS Diy or Highland Scrub or open woodland.
(7) SEMIDTUN SEMIDesert or TUNdra. Open shrub or shrub-steppe (low grass)
of very dry regions may grade into the preceding groups 5 and 6.
Dwarf-shrub or grass-like (graminoid) tundra tends to occur
above the altitudes or latitudes of local tree line (see groups 9 and
27 below).
WE1.4D classes grouped here:
#51 SDS SemiDesert/Desert Scrub/succulent/sparse grass;
#52 CSS Cool/cold Shrub Semidesert/steppe;
#53 TUN Tundra (polar, alpine).
(8) FLDWDSAV FIELD/WOODS mosaic or SAVANNA. Tall grass or crops
together often cover more area than forest or woodland in
Field/woods:
grouped here:
Snowy Field/Woods complex;
Field/Woods with Grass and/or Cropland;
Savanna/Grass, Seasonal Woods: Trees or shrubs above grass
groundcover may be interspersed on many scales in savanna belts
of varying drought duration and high fire frequency.
(9) NORTAIGA NORThern TAIGA or SUBALPINE narrow-crowned sparse
conifer and/or dwarf deciduous tree/scrub/meadow/wetland
mosaics
WE1.4D classes grouped here:
#62 NMT Northern or Maritime Tiaga typifies a wide latitude belt or a
narrow altitude belt above denser forest or woodland.
{#62a} or a new number might distinguish the subalpine mosaics at
lower latitudes.
(10) FORFDREV FOREst/FIELD or DRy EVergreen mixtures commonly have much
broadleaf tree and tall shrub; but conifers pure or mixed (as in
group 3) may be important Nonwooded land is also interspersed,
especially where low forest or open woodland is cleared and
burned for crops or grazing, and where drought or seasonally wet
soil limits establishment or the mature height and density of trees.
WE1.4D classes
#55 SFW
#58 FWG
#43 SGW
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WE1.4D classes grouped here:
#56 FFR Forest/Field complex with Regrowth after disturbances, mixed
with crops and/or other non-wooded lands;
#57 SFF Snowy Forest/Field, commonly openings are pasture and/or
mires;
#48 DEW Dry Evergreen Woodland or low forest, mapped mostly in
interior Australia and South America.
(11) WETLAND Mires, Marshes, or Swamps.
WE1.4D classes grouped here:
#44 MBF Mires include peaty Bogs and Fens (mostly in high latitudes;
#45 MOS Marsh or Other Swampy wetlands include various transitions to
or mixtures with trees.
(Also see group 19 below for #72 mangrove, digitized first for Africa in GED.)
(12) DESERTS -Mostly Bare, Sandy, or Salt-Soda deserts grade into semideserts
(group 7); both have patches interspersed within the other and
within dry grassland.
WE1.4D classes grouped here:
#8 DMB Desert, Mostly Bare stone, clay or sand;
#50 SDB Sand Deserts, partly Blowing Dunes;
#71 SSF Salt/Soda Flats: desert playas, occasionally with intermittent
lakes.
(13) SHRBTRST SHRUB-TRee, Succulent or Thorn thickets are alternatives to the
tree/grass life form strategy response to tropical droughts. Two
droughts per year may occur near the equator as rain belts shift
north or south; or droughts may persist with little or no relief as
in eastern-most Brazil.
WE1.4D classes grouped here:
#59 STW Succulent and Thorn Woods or scrub is widespread;
#49 HVI Hot Volcanic Islands presently is used in the Galapogos Islands,
which have local denser forest on some older lava flows but wide
areas of sparse cover on recent lavas.
(14) CROPSETL CROP/SETTLement/Commerdal Complexes include rice and
other irrigated cropland (#36; 37-39) and other cropland, with
interspersed villages, cities, or industrial areas (#30,31).
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WE1.4D classes grouped here:
Cool Farmland and Settlements, more or less snowy;
Mild-hot Farmland and Settlements;
Paddy Rice and Associated land mosaics;
Warm-hot Cropland, Irrigated extensively;
Cool Cropland with Irrigation of variable extent;
Cold Cropland and Pasture, irrigated locally.
#30
CFS
#31
MFS
#36
PRA
#37
WCI
#38
CCI
#39
CCP
B. Ice, Land-water and Other FRINGES (15-29):
Glacier ice and the following mostly narrow fringe types can be distinguished on a
separate video display (pagedown image with Idrisi software using the same color
palette as for 0-14). Or a palette with more colors can be defined by the user.
(15) CONIFERFC CONIFER RAINForest FRinge Coast is here applied to snowy
conifer rainforest in a narrow band from the southern Alaska to
coastal Washington and Oregon:
WE1.4D classes grouped here:
#20 SRC Snowy, Rainy Coastal Conifer
(16-18) temporarily reserved for later uses.
(19) MANGROVE is separately digitized only for Africa.
WE1.4D classes grouped here:
#72 MSM Mangrove and non-saline Swamps and tidal Mudflats; may also
be common within group 5,7 or 10.
(20) WALANCST WAter/LANd mixtures & COASTal SYSTems. Previously mapped
mostly as Coast/hinterland complexes:
WE1.4D classes grouped here:
#65 CNW Coastal: NorthWest quadrant near most land;
#66 CNE Coastal: NorthEast quadrant near most land;
#67 CSE Coastal: Southeast quadrant near most land;
#68 CSW Coastal: Southwest quadrant near most land;
{80} CWL Coastal Water/Land (-51-90% water) besides those oriented per
#65-68: beach and various dunes, cliff/rock/fjord, and delta
complexes as well as inland types are common. Locating such
kinds of coastal ecosystems and landscapes are refinements for
the future.
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(21-22)
reserved for later use.
(23) ISLFRING ISLand-shore water FRINGes really just mean >90% water. But in
practice this applies mostly to small islands. Edges of islands or
mainland may occur, with near-shore ocean or inland water
bodies:
WE1.4D classes grouped here:
#73 1SL Islands and shore waters in oceans and/or lakes.
(24) LANDWATR LAND-WATER combinations, with water -31-50%, include not
only additional coastal pixels with more land but also many 10'
land pixels with small lakes or wide rivers or reservoirs.
WE1.4D classes grouped here:
{#74-76} in GPC's extended legend are expected to include complexes with
lake and wetland mixtures, alluvial wildlands, floodplain and/or
shoreline farms and settlements or ports.
(25) ICE is mostly in Antarctica (#17, or new #12 when the long legend is
revised) or Greenland, or in smaller glaciers (#70).
WE1.4D classes grouped here:
#17 ICE Antarctic glacial cap [may be #12 in future versions];
#70 GLA Glaciers in polar or alpine complex, with rock fringes.
(26) POLARDES POLAR "DESert" spans small but somewhat diverse areas where
precipitation is low and/or rarely melted as water.
WE1.4D classes grouped here:
#69 PDL Polar "Desert" with rock Lichens, locally abundant or productive
(even between mineral grains) but provide little food. Animals
depend on nearby waters, and import some residues from their
food chains for localized humus.
(27) WTNDMHTH Wooded TUNDra or Moorland-HEATH types
WE1.4D classes grouped here:
#63 WTM Wooded Tundra Margin or mountain scrub/meadow
#64 HMW Heath and Moorland, Wild or artificially managed, as by burning
and/or grazing. Moorland conventionally includes wetland
(#44-45) interspersed with drier heath, with dwarfed or taller,
commonly dense scrub on peat or sand.
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(28)
reserved for later use.
(29) INLDWATR INLAND WATER here refers to specific lake body pixels in which
land is negligible. Otherwise not distinguished from #0 in long
legend.
SOURCES
Improved mapping of the main ecosystem groups described above, depends mainly on
sources noted in this report and Olson et al. (1983,1985). Data from these sources helped
to improve and sometimes combine current information about global patterns in
ecological and landscape systems. WE1.3A and WE1.4D represent examples of doing that
using the sources and history outlined below.
A. Maps and Source Data for Numeric Data Package-17 (NDP-017 = WEI .2)
1) Hummel-Reek Database (1978-79).
To aid studies of carbon cycling and climate at ORNL, Hummel and Reck (1979)
contributed a computer-readable data-set from General Motors Laboratory. They had
digitized a land-use map from Oxford Economic Atlas (Jones 1972; also Cohen 1973).
Their main refinement was to add snow duration in one or two quarters of the year
(respectively "cool" and "cold") because it strongly affected albedo, or reflectivity of the
regional surface affecting their climate models.
2) ORNL Map and Database (1978-85)
The Olson and Watts (1982) map resampled the modified Gall projection of the Oxford
Economic Atlas maps to half-degrees in both latitude and longitude. Fig. 1 of Olson et al.
(1983) shows our splitting of several categories, especially "grazing lands" and certain
forests-especially Boreal (= taiga in Russian) and mosaics of wooded/non-wooded types
(see below). The Russian-language Physical-Geographic Atlas of the World was cited by
Olson et al. (1983) after Gerasimov, Committee Chairman; Hllipov, the operational Editor
is cited as author of the same atlas in NCAR's library in Boulder. Global vegetation map
plates were used previously;continental and USSR maps in some of the revisions.
Unpublished maps of the former Soviet Union from Natalia Bazilivich are being digitized
for NOAA databases by Dmitri Varlyguin at Clark University.
Tropical/subtropical broadleaf humid forest includes extreme "rainforest" and other
somewhat seasonal (but not necessarily deciduous) forms. In printing Olson and Watts
(1982), blue stipples were inserted over the purple to separate the former type (#33) from
the latter (#29). Hand-controlled (red line) printing for mangroves on Olson and Watts
(1972) used information from any source. Yet half-degree pixels seem too coarse for
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digitizing such a "fringe" type of the tropical/subtropical land-saltwater margin. Its type
(#72) was added for the ICSU/UNEP project in 1989 when finer 10' pixels were first
incorporated.
B. Early revisions by Olson (Global Patterns Company)
1) Europe (1985-88)
In October-November 1985, visits to the European Space Agency (ESA) found much
semote sensing information at laboratories in Frascati and Ispra, Italy that was useful for
ecosystem mapping. From late May 1986 to 1987, cross-checking of maps in Sweden,
Belgium, Netherlands, Germany, Denmark, Norway, and Iceland showed more possible
refinements than have been used so far. In July 1987, botanical fieldwork included
Greece.
In April and June-July, 1988, two trips to Austria were added to different routes in
Sweden and Germany. At the International Institute for Applied Systems Analysis
(IIASA, at Laxenburg, near Vienna), a data-set organized for analysis of acid deposition
quantified percentages of forest and total land, but for grid cells of 0.5 degrees latitude x
1 degree longitude.
2) USA and Pacific (especially 1987-91)
Browsing in libraries and research laboratories in Asia, Australia and New Zealand and
the USA as well as Europe, showed many more maps or articles than can be cited.
Observations were recorded on diverse base maps, many of which have schematic
overlays of green showing forest or tree cover. Some provide much finer resolution than
maps at a national to global level and also suggest mosaic combinations: Forest/field has
most continuity between the main wooded parts of a patchwork. Reld/woods has more
continuity between croplands, grasslands or other non-wooded land categories than
between forest/woodland patches (woodlots, plantations, regrowing forests-commonly
degraded by thinning, grazing, or fire).
The triangle diagram shown below as Figure 1 (from Olson et al. 1983) ideally suggests
60 per cent nonwoods component for separating Field/woods (above) from more evenly
divided Forest/field (40-60% nonwoods parts of the mosaic). Below that level Olson
divides broadleaved (or more concisely broadleaf) forest or woodland (>75% of the
woods stand area), from broadleaf/conifer mixed woods (25-50% conifer), and a wider
band called conifer (>50% conifer).
Broadleaf gradations above or below 25% may be recognized but are less commonly
mapped. This tradition reflects common attribution of more economic value to
"softwood" forest products or of more ecological/biophysical indicator value to percent
conifer than "hardwood" when in mixtures.
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Where trees are sparse and/or dwarfed by cold, drought or other stress, tall or dense
scrub may be included in green overlay: e.g. my groups 6 and 13. Olson's use of the
term "woods," like "the bush" in Australia, is a broad grouping, ranging from such
shrubby low growth to closed or open forest, of tall, medium, or low stature.
The Cairns and Brisbane-Cooloola areas of Queensland, were visited in September, 1990,
and southeastern New South Wales in October-December. As in Australia, New Zealand
broadleaf woods are mostly evergreens (southern beech, Nothofagus, and many others).
These could be separated in new types when the Olson legend is being extended instead
of being simplified as in this report. {Type #77 will be for southern conifers (Podocarpus,
etc.) and/or planted Pinus alternating with broadleaved forest, fjords, and glaciated
peaks; #78 for forest that is tall (>30 m) and/or dense (>70% foliage cover); #79 for other
Eucalyptus forest (30-70%.}
In Japan, several agencies are active in developing imagery for sample localities. The
Institute of Agro-environmental Research in the science city Tsukuba (northeast of
Tokyo) has data files directly relevant to grazing and some tree crops as well as to
farming. Forestry records also have potential, and a national land digital database (of
land use and elevation) for planning may be even more helpful, with pixels at a level of
10 km.
Much finer resolution is available in most countries of the world but many questions
remain about how to shift from "thinking locally" to mapping and thinking globally.
METHODS
Showing just one land type or group for all nine 10' subcells in one half-degree cell is
commonly a simplification of the real world. Yet heterogeneous regions may have one
main category taken as representative: a "winner" among competing nominee types. The
"runner-up" candidates may be winners in other cells or blocks. The hope is that suitable
proportions of all types used in modeling the environment of a wider surrounding area,
or the whole planet, will average out. But wetland, mountain summit and some other
types often occur only in minor proportions. These may be under-represented by
weighting schemes in which "winner takes all."
Shifts toward finer resolution (e.g. from the 30' grid called WEI .3A to 10* pixels of
WE1.4D) are partly justified to overcome or avoid such bias, as well as to refine
boundary shapes. An attempt was made to compensate by including
"representa tives-at-large" among the mapped pixels-located in places where the minority
type is relatively important but not necessarily the single commonest type or group.
During processing, a 30' cell may be temporarily flagged with a minor type instead of
losing the tatter's identity and approximate location completely. Later editing ought to
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100
/"Non- \ Percentage of
/ Woods" \
X 80
Non-Woods
/ Field/Woods \
/ Complex \
Vegetation types
V60 in
Forest/Held
Complex
Regional
\ 4ft
/ Broad-
\
Complex
/ Broad-
Conifer \
Coniferous \
/ Leaved
/ Leaved
(with >
>
/
II
/ Forest and
/ Conifer
Broad-Leaved)
\ Forest and
/""/
Mixed Woods
Woods
\ Woodland
\ 0
0 25
50
75
100
Percentage of Conifer Trees (or projected canopy cover) among overstory species
Figure 6 Approximate relations of tree cover, regional percent of non-tree formations,
and major kinds of forest, interrupted woods, and non-woods systems, (from
ORNL-DWG-81-9450, Oak Ridge National Laboratory)
show which 107 subcell(s) deserve the less common labels when most become reassigned
like their commoner neighbors.
Techniques of map or database improvement include digitizing from paper map sources
or adapting global database information that is already computer-readable. Both
approaches are essential, but the emphasis may shift as work progresses. Early editing of
data has used only a fairly small fraction of the possible refinements. WE1.4D illustrates
using data already digitized from satellites.
In 1989 the new digitizing of shore types (especially mangrove, #72) and montane
tropical complexes (#28 and/or #6) used the ocean mask and altitude files from the
FNOC Terrain data-set [Chapter A13 in this volume], as improved by Roy Jenne and
Dennis Joseph of NCAR and John Kineman of NOAA. For Africa, the proper elevation
for montane rainforest was found to be only adjacent to where it had been marked on
Olson and Watts (1982). Altitude data, first at and then 10' resolution also clarified
where the Olson data had correctly included the peak or where it had originally lacked
enough location control to do so. The real refinements at 1C are mostly limited to the
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few types just mentioned and others which happen to have low greenness.
A. Editing from previous maps and diverse sources
For Africa, earlier 30' type locations were first refined manually where available maps or
references allowed. Then the 30' grid was expanded 3-fold in both coordinates. That
meant fewer 10' pixels needed to be fixed along the edges or within a 3x3 array of
identical values-compared with editing all 9 values independently. However, pending
such follow-up checking at 1C, mountain labels may be left temporarily pinned on some
pixels in a valley or on a plain or plateau below altitudes defining the real peak(s).
Much of the 1989 editing was done with Wordstar-2000, convenient (though tedious) for
dealing with single cells or data strings in large files. Within Idrisi, substituting of new
values for old ones was also applied not only to points, rows, or columns, but to
rectangular arrays (commonly 3,6, or 9 10' pixels wide, e.g. in case 1, 2, or 3 of the
half-minute pixels required large-area correction).
However, the difficulty of mislocating points or boundaries, relative to a sparse printed
latitude-longitude net or landmarks, had to be diminished first. This was accomplished
by using reference data already digitized in the GED Prototype disk.
8. Associating vegetation and greenness indexes
Indices of vegetation greenness from weather satellites of NOAA's National
Environmental Satellite, Data, and Information Service (NESDIS) could be used in several
ways. At NASA's Goddard Space Flight Center (GSFC) and the University of Maryland,
Koomanoff (1988) used the old Olson et al. (1985: WEI .2) database to show almost
normally distributed variations of greenness for some type groups (eg. her Figs. 4.1 and
4.3). Skewness for other groups (her Figs. 4.2-4.6) and more diversity for others (even
distinct peaks of greenness for her Figs. 4.7-4.16) indicated that the lumped groups were
heterogeneous, and individual cover types (as originally mapped or refined later) may be
significantly more homogeneous.
Those and other Maryland analyses used early AVHRR indices averaged over one whole
year. Ignoring medium- and long- infrared channels (#3-5), channel signals 1 and 2
(0.58-0.68 jim visible; 0.73-1.10 pm near-infrared) are commonly expressed as ratios of
difference/sum of reflectances Chi and Ch2: i.e.
XVI = (Ch2 - Chl)/(Ch2 + Chi) (1)
This unsealed index ranges from -0.1 for water, cloud or ice or+/- 0.1 for nearly bare
rock or soil to -0.6 or 0.7 for dense, vigorous vegetation. NOAA then derives integer
values rescaled to
GED 1.0 Documentation Olson World Ecoeyattms
A05-31
-------
NDVI = (XVI+0.05)*350 + 15. (2)
Composite sampling and regridding discards values that are low artificially (due to
clouds, haze or dust). Extra bias toward exceptionally green values by this procedure
was decreased by saving the last physically acceptable weekly value.
Second generation NOAA products include a weekly summary of equal latitude -
longitude grid cells (~16 km at the equator) for latitudes 75N to 55S. Further NOAA
quality control in developing the NGDC monthly GED grids used here included (1)
checking registration accuracy against prominent geographic features and (2) inspection
for artifacts (e.g. bad scan lines and system noise) and selection of images without co-
located artifacts. Then (3), both the low and high values were discarded from the
remaining weekly pixel values within each month, to eliminate random noise evident in
the weekly files. (4) A root-mean-square average of the remaining "median" weekly
values within each month was computed for each pixel. (5) The images were then re-
gridded to a 10-minute grid using a spatially weighted average. (6) The images used to
process the World Ecosystems data-set were multi-year averages of these monthly
"generalized" images [provided in Chapter A01 of this volume].
The GED compact disk also has corrections from Kevin Gallo for pre-launch calibration,
drift of the satellite or instrument, arid refinements related to solar zenith declination
angles. Gallo's file of weekly data masked the unusually low values of NDVI that may
be clouds in some places but glaciers or bare desert in others. Monthly summary files
from Gallo were not ready when the work took place from December 1985 through
November 1988 average 1CK NDVI and GVI intervals.
Another kind of monthly AVHRR summary from Japan [Tateishi and Kajiwara - see
reference in Chapter A01 of this volume] deliberately selects the greenest values for each
month, and therefore has least risk of cloud contamination of the image. However, that
advantage is traded off against highest exaggeration of locally high selection (e.g.
irrigated cropland; dense, tall forest) or of seasonal trend favoring the summer end of
spring (or monsoon) season or autumn transition months. Neither the Gallo or Japanese
file is yet likely to be as representative as Kineman's 3 year average used here.
After exploring data for particular months, annually averaged 3-month seasonal images
(December-February, March-May, June-August, September-November) and a 3-year
average for all 12 months were produced. Another simplification was to establish
categories for the Monthly Generalized Global Vegetation Index (MGV), each step
matching 11 levels of the scaled MGV values (which range from 0 to about 211). Our first
questions concerned lower intervals, i.e.,
low GVI Levels 0,1,2,3: for MGV = 0-11,12-22,23-33,34-44, respectively
GED 1.0 Documentation Olson World Ecosystems
A05-32
-------
Briefer inspection and analysis included:
medium GVI Levels 4, 5, 6: for MGV = 45-55,56-66, 67-77; and
high GVI Levels 7-11: for MGV > 77.
Clearly the latter deserve more attention. Lands in the high range have most green
foliage generating organic production, nutrient recycling, and evaporation.
RESULTS
ECOSYSTEMS, VEGETATION, AND LANDSCAPES
1) Desert, cold, and water: low GVI landscapes
Investigation was made to determine the match between low greenness index (MG-GVI,
Chapter A01) and sand desert areas (type 50 on my legend), e.g. the Ergs of the Sahara.
The lowest GVI categories (Categories 1 and 2; MGV = 12-33) were associated with salt
flats or intermittent playa lakes (type #71), except for some matches with water that were
used to refine shore delineation. Especially at the 10' pixel resolution, pixels or clusters
of pixels showed up in the depressions located from altitude files (some below sea-level)
or shown in many atlases.
A few very low index values also appeared on the highest Himalaya Mountains and
ranges on or west of the Tibetan Plateau. These may represent glaciers (#70) or other
very snowy landscapes that may be missed or mislabelled #71, or else mixed with #8 as
bare "alpine" desert, along with the following true desert types.
The next lower level (Level 3; MGV = 34-44) in desert areas was also not mainly in areas
where the working database or extra maps showed most dunes. A "mostly bare" desert
category, already defined as #8 was only sporadically used before 1991. It includes some
sand but commonly also rocky and fine-soil deserts with little or no green cover.
Independent cartography confirms many such landscapes, but more checking is required,
especially outside Africa. In the Nubian, eastern and western Arabian, and some Iranian
deserts, areas originally mapped as grass-shrub (Group 4, type #41, because of their
designation as grazing lands on the Oxford Economic Atlas) effectively belong in this
bare or true desert category in most years. Nomadic economies depend on distant herd
migrations to find the exceptional times and places where grazers can be kept alive, even
if not in thriving condition.
GED 1.0 Documentation ohon World Ecotystems
A05-33
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2) Gradients (Ecotones) of Intermediate Greenness (GVT Levels 4-6)
In the Sahara and elsewhere, some dune regions showed higher index values for
greenness (Levels 4 and 5) than the landscape types of the preceding paragraphs.
Seasonal or sporadic variation in the index suggested ephemeral vegetation where
occasional rains occur. Alternatively, plants on the inter-dune depressions could be
sub-irrigated from rains previously intercepted along the truly bare dune ridges. For part
of the Kalahari desert, GVI Level 6 (MGV = 67-77) overlapped areas of Kalahari sand
that was mapped as #50. It has not been confirmed whether this and a few other areas
represent just the upper range of a pixel variations for sand desert and semidesert type,
or if a "sand hill grass/shrub" category should be created (#87 reserved), or if it should
be coded with existing shrub-grass types #50 or 51.
Oases (irrigated agriculture #37, Group 14) are likely to occur more often as
higher-resolution pixels are provided for. Most seem too localized to show even at
1C—even when associated with persistent marshy vegetation from natural seepage or
drainage (#45, Group 11).
In the USA, higher-resolution ("1.1 km) AVHRR imagery has been treated in more detail
by Loveland et al. (1991). They map somewhat wider areas of effectively "bare" landscape
and infer (pers. com.) that these match deserts with only a few per cent of green cover.
Desert pixels of 10' and especially 3C typically include mosaics of such nearly bare land
plus shrub or shrub-steppe or irrigated cover, and so are less likely to be considered bare
in the aggregate.
At high latitudes, the low sun angle, especially in winter, limits use of AVHRR. Data are
not even retained above 75 N latitude. Nevertheless, a reasonable distinction between
high Arctic tundra (annual mean GVI Level 3) and low Arctic tundra (GVI Level 4 or
lower range of 5). The Wooded Tundra fringe (mapped, illustrated and discussed in
detail by Larsen 1989, for North America) conversely has GVI mostly 4, less often (or less
clearly) 3. It needs to be much better defined at the 10' resolution than the initial 30'
mapping.
Within the Northern Taiga and other Boreal forest belts, there is also an orderly
progression of the GVI (from the MGV data-set), despite numerous inclusions of locally
lower GVI. The inclusions of land-water mixtures (see section 4C) accounts for much of
the seeming "noise" that is related to lakes and mires but these are not yet provided for
in WE1.4D. Analyzing how the whole complex can be resolved, with better resolution
from Local Area Coverage (LAC) AVHRR and still finer satellite imagery, will be a major
contribution of the planned BOREAS project of NASA and other sponsors.
GED 1.0 Documentation Olson World Ecosystems
A05-34
-------
RESOLUTION CODES AND 10-MINUTE UPDATES FOR WE1.4D
The resolution code overlay (OWE14DR) was produced by first tagging all pixels on the
WE1.4D 10-minute grid that differed from their 30-minute mode (for the standard 30-
minute grid registration). These cells were coded 1 against a 0 background. Known
classes that were edited at 10-minutes were then over-written onto the grid. The
resulting map thus provides the following codes;
EXPLANATION OF RESOLUTION CODES
0 unaltered cells representing 30-minute spatial dominance (expanded to a
10-minute grid)
1 edited 10-minute cells
2 residual, or "orphaned" cells from 30-minute regions within which other 10-
minute updates were made. These cells are presumed to represent spatial
dominance at less than 15-minutes (only coded if such cells cover less than
half of the original 30-minute cell), because the other cells in the 30-minute
region have been changed.
The following table describes the specific 10-minute updates made to the data-set, on a
background of 30-minute values:
TABLE OF 10-MINUTE EDITS IN OWE14D
OLSON14D DESCRIPTION
CLASS
0 Water, coastline edits for Africa and some other coasts
6 Montane forest, edits in Africa only
8 Bare desert, updated globally using average GVI.
28 Tropical montane, edits for Africa only
65-68 Coastline, mostly Africa but other areas as well.
71 Salt/soda flats, updated globally using average GVI.
72 Mangroves, Africa only
73 Island/Coastal (Elba Island only)
GED 1.0 Documentation OUtm Worid Ecosystems
A05-35
-------
REFERENCES
ORIGINAL REFERENCES
Extensive references for the original work are given in Olson et al. (1983) and its excerpt
(scanned images of this reference are provided on the CD-ROM - see Primary
Documentation, above). All references related to the present work are listed under
Additional References/ above.
REFERENCES FOR RECENT UPDATES AND COMPARISONS
Cohen, S. (ed.). 1973. The Oxford World Atlas. Oxford University Press, London.
Goward, S. N., C. J. Tucker and D. G. Dye. 1985. North American vegetation patterns
observed with the NOAA-7 advanced very high resolution radiometer. Vegetotio
64: 3-64.
Henderson-Sellers, A., M. F. Wilson, G. Thomas, and R. E. Dickinson. 1986. Current
Global Land-Surface Data Sets for Use in Climate-Related Studies. NCAR Technical
Notes, NCAR/TN-272+STR, National Center for Atmospheric Research, Boulder,
Colorado
Hobbs, R., and H. Mooney (eds.). 1990. Remote Sensing and Biosphere Functioning.
Ecological Studies. Springer-Verlag, New York.
Hummel, J.R., and R.A. Reck. 1979. A global surface albedo model. J. Appl. MeteoroL
18:239-253.
Jones, D.B. (ed.). 1972. Oxford Economic Atlas of the World, 4th Ed. Oxford University Press,
London.
Koomanoff, V. A. 1988. Analysis of Global Vegetation patterns: A Comparison Between
Remotely Sensed Data and a Conventional Map. Report 890201 of Laboratory for
Global Remote Sensing Studies, Geography, Univ. of Maryland, College Park MD.
Larson, J. A. 1989. The northern forest border in Canada and Alaska: Biotic communities
and ecological relationships. Ecological Studies 70. Springer-Verlag, New York.
Loveland, T. R., J. W. Merchant, D. O. Ohlen, and J. F. Brown. 1991. Development of a
land-cover characteristics database for the conterminous United States. Photogmm.
Engineering and Remote Sensing 57:1453-1463.
Olson, J.S. 1992. Global changes and resource management. ASPRSJACSMJRY92 Technical
Papers, Volume 1. P. 32-42.
GED 1.0 Documentation Oison World Ecosystem
A05-36
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A06
Leemans Holdridge Life Zone Classifications
GED 1.0 Documentation HoMrfga l#> Ztm CM/fcuffcw
A06
-------
DATA-SET DESCRIPTION
DATA-SET NAME: Holdridge Life Zone Classifications
PRINCIPAL INVESTIGATORS): Rik Leemans
International Institute for Applied
Systems Analysis
SOURCE
SOURCE DATA CITATION: Leemans, R., 1989. Global Holdridge Life Zone
Classifications. Digital Raster Data on a 0.5-degree Geographic (lat/long) 360x720
grid. Laxenberg, Austria: HASA. Floppy disk, 0.26 MB.
CONTRIBUTORS): Dr. Rik Leemans
RTVM
National Institute of Public Health and Environmental Protection
P.O. Box 1,3720 BA
Bilthoven, The Netherlands
(31)30-749111
DISTRIBUTORS): HASA and RIVM
VINTAGE: circa 1989
LINEAGE:
(1) Rik Leemans, Principal Investigator
International Institute for Applied Systems Analysis (HASA)
Laxenberg, Austria
ORIGINAL DESIGN
VARIABLES: Characteristic life zone classes as predicted by climate, according to the
Holdridge classification method.
ORIGIN: Classification based on climate parameters (temperature and precipitation)
from the HASA database (see data-set A03). (see Primary Documentation)
GEOGRAPHIC REFERENCE: latitude/longitude
GEOGRAPHIC COVERAGE: Global
Maximum Latitude
Minimum Latitude
Maximum Longitude
Minimum Longitude
+90 degrees (N)
-90 degrees (S)
+180 degrees (E)
-180 degrees (W)
GEOGRAPHIC SAMPLING: Characteristic classes for 0.5-degree grid cells.
GED 1.0 Documentation Holdridge Life Zone Classifications
A06-2
-------
TIME PERIOD: Modern, 1931 through 1960.
TEMPORAL SAMPLING: Modern estimate, based on average or "normal" climate.
INTEGRATED DATA-SET
DATA-SET CITATION: Leemans, R. 1992. Global Holdridge Life Zone Classifications.
Digital Raster Data on a 0.5-degree Geographic (lat/long) 360x720 grid. In: Global
Ecosystems Database Version 1.0: Disc A. Boulder, CO: NOAA National Geophysical
Data Center. 2 independent single-attribute spatial layers on CD-ROM, 0.5MB.
[first published in 1989]
ANALYST(s): Rik Leemans
PROJECTION: Geographic (lat/long), GED window (see User's Guide).
SPATIAL REPRESENTATION: Characteristic classes for 0.5-degree cells
TEMPORAL REPRESENTATION: Modern estimate
DATA REPRESENTATION: 1-byte integers, representing characteristic classes
LAYERS AND ATTRIBUTES: 2 independent single-attribute spatial layers
COMPRESSED DATA VOLUME: 32,624 bytes
PRIMARY REFERENCES (* reprint on CD-ROM)
Leemans, Rik, 1989. "Possible Changes in Natural Vegetation Patterns Due to a
Global Warming." In: Hackl, A. (eds.), Der Treibhauseffekt: das Problem •
Mogliche Folgen - Erforderliche MaBnahmm. Akademie fur Umwelt und
Energie, Laxenburg, Austria, pp 105-122.
* Leemans, Rik, 1990. "Possible Changes in Natural Vegetation Patterns Due to a
Global Warming." IIASA Working Paper WP-90-08 and Publication
Number 108 of the Biosphere Dynamics Project. Laxenburg, Austria:
International Institute of Applied Systems Analysis. 22 pp.
ADDITIONAL REFERENCES
Solomon, A.M. and R. Leemans. 1990. Climatic change and landscape-ecological
response: Issues and analyses. In: Boer, M.M. and de Groot, R.S. (eds.), Landscape
Landscape Ecological Impact of Climatic Change. IOS Press, Amsterdam, pp. 293-316
(ISBN 90 5199 023 5).
Prentice, I.C., Cramer, W., Harrison, S.P, Leemans, R., Monserud, R.A. & Solomon, AM.
1992. A global biome model based on plant physiology and dominance, soil
properties and climate. J. Biogeography (in press).
Monserud, R.A. and Leemans, R. 1992. The comparison of global vegetation maps. EcoL
Modelling (in press).
GED 1.0 Documentation Holdridge life Zone Classification*
A06-3
-------
DATA-SET FILES
LOCATION
NAME
NUMBER
TOMi SIZE
Spatial Data:
\GLGEO\RASTER\
Headers:
\GLGEO\META\
PalattMt
Tim* s*ri«st
LHOLD.IMG
LHOLDAG.IMG
LHOLD.DOC
LHOLDAG.DOC
none
none
1 files
1 files
1 files
1 files
259,200
259,200
2,459
1,146
VoIxumi on Disk:
4 files
522,005
REPRINT FILES
LOCATION
HMB
NUMBER
idik. am
\DOCUMENT\A06\
LH 01.PCX to LH_17.PCX
LH_##X.PCX
17 files
4 files
628,049
400,880
Volume on Disk:
21 files
1,028,929
SOURCE EXAMPLE
FILES
none
GED 1.0 Documentation Holdridge Uft Zone Classifications
A06-4
-------
FILE DESCRIPTION
DATA ELEMENT: Holdridge Life Zones Classification
STRUCTURE: Raster Data Files: 0.5-degree 360x720 GED grid (see User's Guide)
SERIES: none
SPATIAL DATA FILES:
file title
data type
file type
columns
rows
ref.
ref.
system
units
unit dist.
min. X
max.
min.
max.
X
Y
Y
pos'n error
resolution
min. value
max. value
value units
value error
flag value
flag def'n
legend cats
LHOLD.DOC
Leemans' Holdridge Life Zones Classification
byte
binary
720
360
lat/long
deg
1.0000000
-180.0000000
180.0000000
-90.0000000
90.0000000
unknown
0.5000000
0
38
classed
unknown
none
none
40
Legend:
category
0
0
Oceans
category
1
1
Ice
category
2
2
Po Des
category
3
3
Po Dry Tu
category
4
4
Po Mois T
category
5
5
Po Wet Tu
category
6
6
Po Rain T
category
7
7
Bor Des
category
8
8
Bor Dry B
category
9
9
Bor Mois
category
10
10
Bor Wet F
category
11
11
Bor Rain
category
12
12
ClTmp Des
category
13
13
ClTmp D/B
category
14
14
ClTmp Ste
category
15
15
ClTmp MsF
category
16
16
ClTmp Wet
category
17
17
ClTmp RnF
category
18
18
WmTmp Des
category
19
19
WmTmp D/B
category
20
20
WmTmp Thn
category
21
21
WmTmp Dry
Ice
Polar Desert
Polar Dry Tundra
Polar Moist Tundra
Polar Wet Tundra
Polar Rain Tundra
Boreal Desert
Boreal Dry Bush
Boreal Moist Forest
Boreal Wet Forest
Boreal Rain Forest
Cool Temperate Desert
Cool Temperate Desert Bush
Cool Temperate Steppe
Cool Temperate Moist Forest
Cool Temperate Wet Forest
Cool Temperate Rain Forest
Warm Temperate Desert
Warm Temperate Desert Bush
Warm Temperate Thorn Steppe
Warm Temperate Dry Forest
GED 1.0 Documentation Holdrtdgt lift Zont CltuaificaHont A06-5
-------
category
22 :
22
WmTmp MsF
category
23 :
; 23
WmTmp Wet
category
24 :
24
WmTmp RnF
category
25 :
: 25
SbTrp Des
category
26 :
: 26
SbTrp D/B
category
27 :
: 27
SbTrp Thn
category
28 :
: 28
SbTrp Dry
category
29 :
; 29
SbTrp MsF
category
30 :
: 30
SbTrp Wet
category
31 :
: 31
SbTrp RnF
category
32 :
: 32
Trop Des
category
33 !
: 33
Trop D/B
category
34 i
: 34
Trop ThnS
category
35 :
: 35
Trop VDry
category
36
: 36
Trop DryF
category
37
: 37
Trop MsFo
category
38
: 38
Trop WetF
category
39
: 39
Trop RnFo
Warm Temperate Moist Forest
Warm Temperate Wet Forest
Warm Temperate Rain Forest
Subtropical Desert
Subtropical Desert Bush
Subtropical Thorn Steppe
Subtropical Dry Forest
Subtropical Moist Forest
Subtropical Wet Forest
Subtropical Rain Forest
Tropical Desert
Tropical Desert Bush
Tropical Thorn Steppe
Tropical Very Dry Forest
Tropical Dry Forest
Tropical Moist Forest
Tropical Wet Forest
Tropical Rain Forest
NOTES:
GED 1.0 Documentation Holdrldge life Zone Classification*
A06-6
-------
DATA ELEMENT: Holdridge Life Zones Aggregated Classification
STRUCTURE: Raster Data Files: .5-degree 360x720 GED grid (see User's Guide)
SERIES: none
SPATIAL DATA FILES:
LHOLDAG.DOC
file title
Leemans' Holdridge Life Zones Aggregated Classification
data type
byte
file type
binary
columns
720
rows
360
ref. system
lat/long
ref. units
deg
unit dist.
1.0000000
min. X
-180.0000000
max. X
180.0000000
min. Y
-90.0000000
max. Y
90.0000000
pos'n error
unknown
resolution
0.5000000
min. value
0
max. value
14
value units
classed
value error
unknown
flag value
none
flag def'n
none
legend cats
15
Legend:
category
0
0
Oceans
category
1
1
Tundra
category
2
2
Cold Park
category
3
3
Forest Tu
category
4
4
Boreal Fo
category
5
5
Cool Dese
category
6
6
Steppe
category
7
7
Temprt Fo
category
8
8
Hot Deser
category
9
9
Chapparal
category
10 : 10
WmTmp For
category
11 : 11
Trop Semi
category
12
12
Trop DryF
category
13
: 13
Trop Seas
category
14
14
Trop Rain
NOTES:
Tundra
Cold Parklands
Forest Tundra
Boreal Forest
Cool Desert
Steppe
Temperate Forest
Hot Desert
Chapparal
Warm Temperate Forest
Tropical Semi-Arid
Tropical Dry Forest
Tropical Seasonal Forest
Tropical Rain Forest
GED 14) Documentation Holdridge lift Zone Claeaiflcatknu
A06-7
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DATA INTEGRATION AND QUALITY
Mark A. Ohrenschall
NOAA National Geophysical Data Center
Boulder, CO
The Leemans Holdridge Classification source data came as a compressed file containing
two variables, "standard" and "aggregated with Olson's ecosystem classes." The data
were in a lat/long projection on a half-degree grid bounded by 90 degrees north, 90
degrees south, 180 degrees west, and 180 degrees east. The data are treated as average
cell values.
Both data files were in compressed or run-length encoded format. A fortran routine to
decode the data files was provided, which was modified to generate the desired output,
separating the two numerical values and expanding the run-length encoded grid. This
program produced an integer-ASCII Idrisi file, for which an IDRISI header (.DOC) file
was created. The data-set was then converted to a byte-binary file type in IDRISI.
Legend information was then entered by keyboard.
Although class 39 is documented for the "standard" version, this value did not occur in
the data-set. The original structure of the data-set was compatible with the GED
conventions, and thus did not require re-working.
GED 1.0 Documentation Holdridge Ufe Zone ClaMxficaHont
A06-8
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A07
Matthews Vegetation, Land Use, and Seasonal Albedo
GED 1.0 Documentation Vegetation, Land Um< and Seasonal Albedo
A07
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DATA-SET DESCRIPTION
DATA-SET NAME: Vegetation, Land Use, and Seasonal Albedo
PRINCIPAL iNVESTlGATOR(s): Elaine Matthews
Goddard Institute for Space Studies
SOURCE
SOURCE DATA CITATION: Matthews, E., 1983. Global Vegetation, Land-Use, and
Seasonal Albedo [NASA Goddard Institute for Space Studies]. Digital Raster Data
on a 1-degree Geographic (lat/long) 180x360 grid. Boulder, CO: National Center
for Atmospheric Research. 9 track tape, 0.8 MB
CONTRIBUTORS): Dr. Elaine Matthews
NASA Goddard Space Flight Center,
Institute for Space Studies
2880 Broadway
New York, NY 10025 USA
DISTRIBUTORS): NCAR
VINTAGE: circa 1980
LINEAGE: (1) Principal Investigator:
Elaine Matthews
NASA Goddard Institute of Space Studies
(2) Archived and Distributed by:
Roy Jenne
National Center for Atmosphereic Research (NCAR)
ORIGINAL DESIGN
VARIABLES:
1. Vegetation, representing natural (pre-agricultural) vegetation based on the
UNESCO (1973) classification system.
2. Cultivation Intensity derived from land use data, representing areal extent
of presently cultivated land in the 1-degree cells.
3. Seasonal Albedo, as present integrated surface albedo for January, April,
July, October for snow-free conditioins except for permanently snow-
covered continental ice, incorporating natural vegetation and cultivation
characteristics from the vegetation and cultivation-intensity data sets.
NOTE: Data are included for land areas only, including continental ice (Water,
including oceans and lakes, are coded 0).
ORIGIN: digitized from numerous published sources and satellite imagery (see Primary
Documentation)
GED 1.0 Documentation Vegetation, Land Use, and Seasonal Albedo
A07-2
-------
GEOGRAPHIC REFERENCE: latitude/longitude
GEOGRAPHIC COVERAGE: Global
Maximum Latitude : +90 degrees (N)
Minimum Latitude: -90 degrees (S)
Maximum Longitude: +180 degrees (E)
Minimum Longitude: -180 degrees (W)
GEOGRAPHIC SAMPLING: integrated values for 1 degree grid cells
TIME PERIOD: drca 1950/s through 197Cs
TEMPORAL SAMPLING: Modern composite of available data
INTEGRATED DATA-SET
DATA-SET CITATION: Matthews, E. 1992. Global Vegetation, Land-Use, and Seasonal
Albedo. Digital Raster Data on a 1-degree Geographic (lat/long) 180x360 grid. In:
Global Ecosystems Database Version 1.0: Disc A. Boulder, CO: NOAA National
Geophysical Data Center. 6 independent single-attribute spatial layers on CD-
ROM, 1.6 MB. [first published in 19831
ANALYST(s): Elaine Matthews
PROJECTION: Geographic (lat/long), GED window (see User's Guide).
SPATIAL REPRESENTATION: integrated values for 1-degree grid cells
TEMPORAL REPRESENTATION: Modern composite
DATA REPRESENTATION:
Vegetation Type: 1-byte integers: integrated type classes for 1-degree
cdls.
Cultivation Intensity. 1-byte integers: classes (0-5) of areal extent within 1-
degree cells.
Seasonal Albedo: 2-byte integers: percent (x 100) integrated albedo.
LAYERS AND ATTRIBUTES: 6 independent single-attribute spatial layers
COMPRESSED DATA VOLUME: 45,646 bytes
PRIMARY REFERENCES (* reprint on CD-ROM)
* Matthews, E. 1983. "Vegetation, Land-Use and Seasonal Albedo Data Sets:
Documentation of Archived Data Tape." NASA Technical Memorandum
#86107.
* Matthews, E., 1983. "Gobal vegetation and land use: New high resolution data
bases for climate studies." Journal of Climatology and Applied Meteorology, vol.
22, pp. 474-487.
ADDITIONAL REFERENCES
Matthews E., 1985. "Atlas of archived vegetation, land-use, and seasonal albedo data
sets." NASA Technical Memorandum #86199.
GED 1.0 Documentation Vegetation, Land Use, and Seasonal Albedo
A07-3
-------
DATA-SET FILES
LOCATION
NAME
NUMBER
TODIL SEES!
Spatial Data:
\GLGEO\RASTER\
MAVEG.IMG
1 files
64,800
MACULT.IMG
1 files
64,800
MALBFA.IMG
1 files
129,600
MALBSM.IMG
1 files
129,600
MALBSP.IMG
1 files
129,600
MALBWN.IMG
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Headers:
\GLGEO\RASTER\
MAVEG.DOC
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MALBFA.DOC
1 files
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MALBSM.DOC
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504
MALBSP.DOC
1 files
499
MALBWN.DOC
1 files
504
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none
Tina Series:
none
Volume on Disk:
12 files
653,487
REPRINT FILES
LOCATION
NAMB
NUMBER
T3BIL SEES
\DOCUMENT\AO7\
MA1_01.PCX to
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14 files
297,060
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3
361,780
MA2_01.PCX to
MA2_14.PCX
14 files
639,909
MA2_##X.PCX
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none
GED 1.0 Documentation Vegetation, Land Use, and Seasonal Albedo
A07-4
-------
FILE DESCRIPTION
DATA ELEMENT; Vegetation Type
STRUCTURE: Raster Data File: 1-degree 180x360 GED grid (see User's Guide)
SERIES: none
SPATIAL DATA FILES:
MAVEG.DOC
file title : Matthews Vegetation Types
data type : byte
file type : binary
columns : 360
rows : 180
ref. system : lat/long
ref. units : deg
unit dist. : 1.0000000
min. X : -180.0000000
max. X : 180.0000000
min. Y : -90.0000000
max. Y : 90.0000000
pos'n error : unknown
resolution : 1.0000000
min. value : 0
max. value : 31
value units : classed
value error : unknown
flag value : none
flag def'n : none
legend cats
: 33
category
0 :
0
Water
(including lake and ocean)
category
1 :
1
TER
Tropical evergreen rainforest, mangrove
forest
category
2 :
2
TES
Tropical/subtropical evergreen seasonal
broadleaved forest
category
3 :
3
SER
Subtropical evergreen rainforest
category
4 :
4
TSP
Temperate/subpolar evergreen rainforest
category
5 :
5
TSB
Temperate evergreen seasonal broadleaved
forest, siimmer rain
category
6 :
6
EBS
Evergreen broadleaved sclerophyllous forest,
winter rain
category
7 :
7
TEN
Tropical/subtropical evergreen needleleaved
forest
category
8 :
8
TSE
Temperate/subpolar evergreen needleleaved
forest
category
9 :
9
TSD
Tropical/subtropical drought-deciduous forest
category
10 :
10
CDE
Cold-deciduous forest, with evergreens
category
11 :
11
CDF
Cold-deciduous forest, without evergreens
category
12 :
12
XFW
Xeromorphic forest/woodland
category
13 :
13
ESW
Evergreen broadleaved sclerophyllous woodland
category
14 :
14
ENW
Evergreen needleleaved woodland
category
15 :
15
TDD
Tropical/subtropical drought-deciduous
woodland
GED 1.0 Documentation Vegetation, Land Use, and Seasonal Albedo
A07-5
-------
category
16
: 16
CDW
category
17
: 17
EBT
category
18
: 18
ENM
category
19
: 19
DDS
category
20
: 20
CDS
category
21
: 21
XSD
category
22
: 22
ATM
category
23
: 23
TGW
category
24
: 24
TGV
category
25
: 25
TGS
category
26
: 26
TGN
category
27
: 27
MGN
category
28
: 28
MSG
category
29
; 29
FFO
category
30
: 30
DES
category
31
: 31
ICE
category
32
: 32
CUL
NOTES:
Cold-deciduous woodland
Evergreen broadleaved shrubland/thicket,
evergreen dwarf-shrubland
Evergreen needleleaved or microphyllous
shrubland/thicket
Drought-deciduous shrubland/thicket
Cold-deciduous subalpine/subpolar shrubland,
cold-deciduous dwarf shrubland
Xeromorphic shrubland/dwarf shrubland
Arctic/alpine tundra, mossy bog
Tall/medium/short grassland with 10-40% woody
tree cover
Tall/medium/short grassland with <10% woody
tree cover or tuft-plant cover
Tall/medium/short grassland with shrub cover
Tall grassland, no woody cover
Medium grassland, no woody cover
Meadow, short grassland, no woody cover
Forb formations
Desert
Ice
Cultivation
GED 1.0 Documentation Vegetation, Land U$e, and Seasonal Albedo
A07-6
-------
DATA ELEMENT: Cultivation Intensity
STRUCTURE: Raster Data Files: 1-degree 180x360 GED grid (see User's Guide)
SERIES: none
SPATIAL DATA FILES:
MACULT.DOC
file title
Matthews Cultivation Intensity
data type
byte
file type
binary
columns
360
rows
180
ref. system
lat/long
ref. units
deg
unit dist.
1.0000000
min. X
-180.0000000
max. X
180.0000000
min. Y
-90.0000000
max. Y
90.0000000
pos'n error
unknown
resolution
1.0000000
min. value
0
max. value
5
value units
classed
value error
unknown
flag value
none
flag def'n
none
legend cats
6
Legend:
category 0 :
0 Water (including lake and ocean)
category 1 :
1 0%
category 2 :
2 20%
category 3 :
3 50%
category 4 :
4 75%
category 5 :
5 100%
NOTES:
GED 1.0 Documentation Vegetation, Land Use, and Seasonal Albedo
AO7-7
-------
DATA ELEMENT: Seasonal Albedo
STRUCTURE:
SERIES: none
SPATIAL DATA FILES: Raster Data Files: 1-degree 180x360 GED grid (see User's Guide)
MALBFA.DOC
file title
Matthews Fall Albedo (% X 100)
data type
integer
file type
binary
columns
360
rows
180
ref. system
lat/long
ref. units
deg
unit dist.
1.0000000
min. X
-180.0000000
max. X
180.0000000
min. Y
-90.0000000
max. Y
90.0000000
pos'n error
unknown
resolution
1.0000000
min. value
0
max. value
7500
value units
percentage X 100
value error
unknown
flag value
none
flag def'n
none
legend cats
0
File Series:
File Season
MALBFA Fall
MALBSM Summer
MALBSP Spring
MALBWN Winter
Minimum
0
0
0
0
Maximum
7500
7500
7500
7500
NOTES:
GED 1.0 Documentation Vegetation, Land Use, and Seasonal Albedo
A07-8
-------
DATA INTEGRATION AND QUALITY
Mark A. Ohrenschall
NOAA National Geophysical Data Center
Boulder, CO
The Matthews data were in a lat/long projection on a one-degree grid bounded by 90
degrees North, 90 degrees South, 180 degrees West, and 180 degrees East. The data-sets
consisted of three files, VEGTYPE, CULTTNT, and ALBEDO. All files were in ASCII
fixed field format, with cell sequencing scanning left to right, bottom to top in the one-
degree grids. The VEGTYPE and CULTTNT files consisted of a sequence of two-digit
integers and the ALBEDO file consisted of a sequence of four-digit reals (2 decimal
places). The four albedo grids were stacked together in the ALBEDO file.
Programs were written to read each file and write the appropriate values into an IDRISI
raster data file in ASCII (for inspection), and then converted to binary. All grids were
then inverted to place North at the top. The four seasonal albedo files were then
windowed from the stacked data file, multiplied by 100 and converted to byte-binary
data types.
The original numerical values are thus preserved, except for scaling of the albedos to
allow byte storage. All final data files were inspected for agreement with the original
data.
GED 1.0 Documentation Vegetation, Land Ute, and Seasonal Albedo
A07-9
-------
A08
Lerner, Matthews and Fung Methane Emission From
Animals
GED 1.0 Documentation Methane Emission From Animal*
A08
-------
DATA-SET DESCRIPTION
DATA-SET NAME: Methane Emission From Animals
PRINCIPAL INVESTIGATORS): Jean Lerner, Elaine Matthews, and
Inez Fung
Goddard Institute for Space Studies
SOURCE
SOURCE DATA CITATION: Lerner, J., E. Matthews, and I. Fung. 1989. Methane
Emmission From Animals: A Global High Resolution Database from the NASA
Goddard Institute for Space Studies. Digital Raster Data on a 1-degree
Geographic (lat/long) 180x360 grid. Boulder, CO: National Center for
Atmospheric Research. 1 floppy disk, 1.3 MB.
CONTRIBUTORS): Drs. Jean Lerner, Elaine Matthews and Inez Fung
NASA Goddard Space Flight Center,
Institute for Space Studies
2880 Broadway
New York, NY 10025 USA
DISTRIBUTORS): NCAR
VINTAGE: circa 1987
LINEAGE:
(1) Data Development:
Jean Lerner, Elaine Matthews and Inez Fung
NASA Goddard Institute of Space Studies
New York, NY
(2) Archived and Distributed by:
Roy Jenne
National Center for Atmosphereic Research
Boulder, CO
ORIGINAL DESIGN
VARIABLES:
Animal Density for various animals, expressed in number of animals per square
kilometer.
Annual Methane Emmission. in kilograms per square kilometer
ORIGIN: (see Primary Documentation)
1. Domestic animals: 1984 FAO Production Yearbook
2. Wild and domestic caribou: Anderson, 1978; Nowak and Paradiso, 1983;
GED 1.0 Documentation Mtthatu Etnittion From Animal*
A08-2
-------
Jackson, 1986.
3. Matthews Vegetation and Land Use data (see AO7)
GEOGRAPHIC REFERENCE: latitude/longitude
GEOGRAPHIC COVERAGE: Global
+90 degrees (N)
Maximum Latitude
Minimum Latitude
Maximum Longitude
Minimum Longitude
-90 degrees (S)
+180 degrees (E)
-180 degrees (W)
GEOGRAPHIC SAMPLING: Averages over 1-degree grid cell areas
TIME PERIOD: Modern statistical compilations, circa 1980's
TEMPORAL SAMPLING: Modern composite of available data
INTEGRATED DATA-SET
DATA-SET CITATION: Lerner, J., E. Matthews, and I. Fung. 1992. Methane Emmission
from Animals: A Global High Resolution Database. Digital Raster Data on a 1-degree
Geographic (lat/long) 180x360 grid. In: Global Ecosystems Database Version 1.0: Disc
A. Boulder, CO: NOAA National Geophysical Data Center. 11 independent
single-attribute spatial layers on CD-ROM, 2.9 MB. [first published in 1988]
ANALYST(s): Jean Lerner, Elaine Matthews, and Inez Fung
PROJECTION: Geographic (lat/long), GED window (see User's Guide).
SPATIAL REPRESENTATION: Averages over 1-degree grid cell areas
TEMPORAL REPRESENTATION: Modern composite
DATA REPRESENTATION:
Animal Density: Number/km2, with precisions up to 107; expressed as 4-byte
IEEE real numbers to 10 significant digits
Methane Emmission: Kg/km2, V-l Kg/km2, expressed as 4-byte IEEE real
numbers
LAYERS AND ATTRIBUTES: 11 independent single-attribute spatial layers
COMPRESSED DATA VOLUME: 130,257 bytes
PRIMARY REFERENCES (* reprint on CD-ROM)
* Lerner, Matthews, E., and Fung, I. 1988. "Methane emissions from animals:A
global high-resolution data base." Global Biogeochemical Cycles, vol. 2, no.2,
pp. 139-156.
ADDITIONAL REFERENCES
GED 1.0 Documentation Methane Emiuion From Animal*
A08-3
-------
DATA-SET FILES
LOCATION
NAME
NUMBER
TOOL SIZE
Spatial Data:
\GLGEO\RASTER\
LMFCAML.IMG
1
file
259,200
LMFCARB.IMG
1
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Haadarat
\GLGEO\META\
LMFCAML.DOC
1
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611
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1
file
612
LMFCOW .DOC
1
file
633
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1
file
615
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1
file
610
LMFHORS.DOC
1
file
611
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627
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1
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623
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1
file
610
LMFSHEP.DOC
1
file
612
LMFWBUF.DOC
1
file
619
Palettess
none
Time Series:
none
Voluna on Disk:
22
files
2,857,983
REPRINT FILES
LOCATION
NAME
NUMBER
TCDKL SDK
\DOCUMENT\AO8\
LMF1_01PCX to LC1_18.PCX
18 files
1,180,734
LMF1_# #X.PCX
5 files
656,178
Volume on Disk:
23 files
1,836,912
SOURCE EXAMPLE FILES
hpne
GGD 1.0 Documentation Methane Emission From Animals A08-4
-------
FILE DESCRIPTION
DATA ELEMENT: Animal Density
STRUCTURE: Raster Data Files: 1-degree GED 180x360 grid (see User's Guide)
SERIES: Animals
SPATIAL DATA FILES:
LMFCAML.DOC
file title
Lerner et al. Camel Density
-------
DATA ELEMENT: Annual Methane Emmission
STRUCTURE: Raster Data Files: 1-degree GED 180x360 grid (see User's Guide)
SERIES: none
SPATIAL DATA FILES:
LMFMETH.DOC
file title
Matthews & Fung Annual Methane Emission (Kg/Km~2)
data type
real
file type
binary
columns
360
rows
180
ref. system
1at/Ion
ref. units
deg
unit dist.
1.0000000
min. X
-180.0000000
max. X
180.0000000
min. Y
-90.0000000
max. Y
90.0000000
pos'n error
unknown
resolution
1.0000000
min. value
0.0000000
max. value
11400.0000000
value units
kilograms / square kilometer
value error
unknown
flag value
-1.0000000
flag def'n
flag value signifies land with no methane
legend cats
0
comment
ocean has the value -100
NOTES:
1. These data are stored as real numbers (IEEE 4-byte floating point reals) to
preserve the full range of numerical values in the original data-set.
GED 1.0 Documentation Meihatu Emission From Animals
A08-6
-------
DATA INTEGRATION AND QUALITY
Mark A. Ohrenschall
National Geophysical Data Center
Boulder, CO
Data were read from floppy disk and converted to the GED format, separating each
variable into different GIS files without altering the original numerical values. Legend
information was entered from the accompanying documentation. All final data files
were inspected for agreement with the original versions.
GED 1.0 Documentation Mtfhane Emittion From Animal*
A08-7
-------
A09
Matthews & Fung Global Distribution, Characteristics and
Methane Emission of Natural Wetlands
GED 1.0 Documentation Methane Emission of Natitml Wetlands
A09
-------
DATA-SET DESCRIPTION
DATA-SET NAME: Global Distribution, Characteristics and Methane
Emission of Natural Wetlands
PRINCIPAL INVESTIGATORS): Elaine Matthews and Inez Fung
Goddard Institute for Space Studies
SOURCE
SOURCE DATA CITATION: Matthews, E., 1989. Global Data Bases on Distribution,
Characteristics and Methane Emission of Natural Wetlands from the NASA Goddard
Institute of Space Studies. Digital Raster Data on a 1-degree Geographic (lat/long)
180x360 grid. Boulder, CO: National Center for Atmospheric Research. Floppy
disk, 1.2 MB.
CONTRIBUTOR(s): Dr. Elaine Matthews and Dr. Inez Fung
NASA Goddard Space Flight Center,
Institute for Space Studies
2880 Broadway
New York, NY 10025
DISTRIBUTORS): NCAR
VINTAGE: circa 1986
LINEAGE:
(1) Elaine Matthews
NASA Goddard Space Flight Center
Institute of Space Studies
New York, NY
(2) Archived and Distributed by:
Roy Jenne
National Center for Atmosphereic Research
Boulder, CO
ORIGINAL DESIGN
VARIABLES:
Wetland Types:
Wetland Data Sources:
Fractional Inundation:
12 integrated wetland type classes for 1-degree grid
cells.
combinations (7 codes) of sources used to determine
Wetland Type for 1-degree grid cells.
Inundated proportion of 1-degree grid cells
GED 1.0 Documentation Methane Emission of Natural Wetlands
A09-2
-------
Vegetation Types: 178 UNESCO vegetation type classes for 1-degree grid
cells.
Zobler Soil Types: 106 Zobler soil classes for 1-degree grid cells.
ORIGIN: Integration of 3 independent digital sources:
1. Matthews Vegetation and Land Use data-set (see A07)
2. Zobler FAO soils data-set (see All)
3. ONC Charts
GEOGRAPHIC REFERENCE: latitude/longitude
GEOGRAPHIC COVERAGE: Global
Maximum Latitude
Minimum Latitude
Maximum Longitude
Minimum Longitude
GEOGRAPHIC SAMPLING:
TIME PERIOD: Modern
TEMPORAL SAMPLING: Composite Modern composite
+90 degrees (N)
-90 degrees (S)
+180 degrees (E)
-180 degrees (W)
INTEGRATED DATA-SET
DATA-SET CITATION: Matthews, E. and I. Fung. 1992. Global Data Bases an
Distribution, Characteristics and Methane Emission of Natural Wetlands. Digital Raster
Data on a 1-degree Geographic (lat/long) 180x360 grid. In: Global Ecosystems
Database Version 1.0: Disc A. Boulder, CO: NOAA National Geophysical Data
Center. 11 independent single-attribute spatial layers on CD-ROM, 1.3 MB. [first
published in 1989]
ANALYST(s): Elaine Matthews and Inez Fung, NASA/GISS, New York, New York
PROJECTION: Geographic (lat/long), GED window (see User's Guide).
SPATIAL REPRESENTATION: Characteristic classes and averages over 1-degree grid
cell areas.
TEMPORAL REPRESENTATION: Modern composite
DATA REPRESENTATION:
Wetland Types 2-byte integer class codes
Wetland Data Sources 2-byte integer source codes
Fractional Inundation 2-byte integers (% of cell)
Vegetation Types 2-byte integer class codes
Zobler Soil Types: 2-byte integer class codes
LAYERS AND ATTRIBUTES: 5 independent single-attribute spatial layers
COMPRESSED DATA VOLUME: 30,914 bytes
PRIMARY REFERENCES (* reprint on CD-ROM)
* Matthews, E. 1989. Global Data Bases on Distribution, Characteristics and Methane
Emission of Natural Wetlands: Documentation of Archived Data Tape.
GED 1.0 Documentation Methane Emiseim of Natural Wetlandt
A09-3
-------
NASA Technical Memorandum 4153.
* Matthews, E. and I. Fung. 1987. Methane emission from natural wetlands: Global
area, distribution and environmental characteristics of sources. Global
Biogeochemical Cycles, 1, 61-86.
ADDITIONAL REFERENCES
FAO. 1971-1981. Soil Map of the World, Vols. 1-10 (1:5M scale maps and accompanying
texts), UNESCO, Paris.
Matthews, E. 1983.: Global vegetation and land use: new high-resolution data bases for
climate studies. /. Clim. Appl. Meteorol., 22,474-487.
UNESCO. 1973. International classification and mapping of vegetation. UNESCO,Paris.
Zobler, L. 1986. A world soil file for global climate modeling. NASA Technical
Memorandum 87802.
GED 1.0 Documentation Methane Emission of Natural Wetlands
A09-4
-------
DATA-SET FILES
LOCATION
£AMB
HTMBHR
tool arm
Spatial Data:
\GLGEO\RASTER\
Headers:
\ GLGEO \META\
Palettest
Time Seriesi
MFWFRIN.IMG
MFWSOL.IMG
MFWSRC.IMG
MFWVEG.IMG
MFWWET.IMG
MFWFRIN.DOC
MFWSOL.DOC
MFWSRC.DOC
MFWVEG.DOC
MFWWET.DOC
none
none
1 files
1 files
1 files
1 files
1 files
1 files
1 files
1 files
1 files
1 files
129,600
129,600
129,600
129,600
129,600
2,572
5,160
829
11,389
1,186
Volume on Diskt
10 files
669,136
REPRINT FILES
LOCATION
MMg
mncBiR
nrtmr. am
\DOCUMENT\A09\
MFW1_01.PCX to
MFW2_01.PCX to
MFW2_# #X.PCX
MFW2_21.PCX
MFW2_26
21 files
26 files
5 files
537,013
1,376,180
428,032
Volume on Disks
52 files
2,341,225
SOURCE EXAMPLE FILES
none
GED 1.0 Documentation Methmn* Emittion of N*tur*l Wrtitmdt
A09-5
-------
FILE DESCRIPTION
DATA ELEMENT: Wetland Types
STRUCTURE: Raster Data Files: 1-degree GED 180x360 grid (see User's Guide)
SERIES: none
SPATIAL DATA FILES:
MFVWET.DOC
file title
Matthews and Fung Wetland Type
data type
integer
file type
binary
columns
360
rows
180
ref. system
lat/long
ref. units
deg
unit dist.
1.0000000
min. X
-180.0000000
max. X
180.0000000
min. Y
-90.0000000
max. Y
90.0000000
pos'n error
unknown
resolution
1.0000000
min. value
0
max. value
12
value units
characteristic classes
value error
unknown
flag value
-1
flag def'n
flag value signifies water
legend cats
13
Legend:
category 0 :
0 other land (non-wet)
category 1 :
1 frst bog forested bog
category 2 :
2 nfrst bog nonforested bog
category 3 :
3 frst swmp forested swamp
category 4 :
4 nfst swmp nonforested swamp
category 5 :
5 alvl form alluvial formations
category 6 :
6 trpcl/sub tropical/subtropical forest/woodland
category 7 :
7 temp frst temperate forest/woodland
category 8 :
8 hi-lat tm high-latitude temperate/boreal
forest/woodland/shrub
category 9 :
9 shrb/dsrt shrubland; xeromorphic formations; desert
category 10 :
10 wd grass wooded grassland
category 11 :
11 nwd grass nonwooded grassland
category 12 :
12 tundra tundra
NOTES:
GED 1.0 Documentation Methane Emission of Natural Wetlands
A09-6
-------
DATA ELEMENT: Wetland Data Sources
STRUCTURE: Raster Data Files: 1-degree GED 180x360 grid (see User's Guide)
SERIES: none
SPATIAL DATA FILES:
MFWSRGDOC
file title
Matthews and Fung Wetland Data Source
data type
integer
file type
binary
columns
360
rows
180
ref. system
lat/long
ref. units
deg
unit dist.
1.0000000
min. X
-180.0000000
max. X
180.0000000
min. Y
-90.0000000
max. Y
90.0000000
pos'n error
unknown
resolution
1.0000000
min. value
0
max. value
7
value units
characteristic classes
value error
unknown
flag value
-1
flag def'n
flag value signifies water
legend cats
8
Legend:
category 0 s
0 other land (non-wet)
category 1 :
1 U+F+O UNESCO + FAO + ONC
category 2 :
2 U+O UNESCO + ONC
category 3 :
3 U+F UNESCO + FAO
category 4 :
4 U UNESCO
category 5 :
5 O+F ONC + FAO
category 6 :
6 0 ONC
category 7 :
7 F FAO
NOTES:
GED 1.0 Documentation Methane Emission of Natural Wetland*
A09-7
-------
DATA ELEMENT: Fractional Inundation
STRUCTURE: Raster Data Files: 1-degree GED 180x360 grid (see User's Guide)
SERIES: none
SPATIAL DATA FILES:
MFWFRIN.DOC
file title
Matthews and Fung Fractional Inundation
data type
integer
file type
binary
columns
360
rows
180
ref. system
lat/long
ref. units
deg
unit dist.
1.0000000
min. X
-180.0000000
max. X
180.0000000
min. Y
-90.0000000
max. Y
90.0000000
pos'n error
unknown
resolution
1.0000000
min. value
0
max. value
100
value units
percent inundation
value error
unknown
flag value
-1
flag def'n
flag value signifies water
legend cats
101
NOTES:
1. Legend not shown (category # = integer percent value)
GED 1.0 Documentation Methane Emiatim of Natural Wetland*
A09-8
-------
DATA ELEMENT: Vegetation Type
STRUCTURE: Raster Data Files: 1-degree GED 180x360 grid (see User's Guide)
SERIES: none
SPATIAL DATA FILES:
MFWVEG.DOC
file title
Matthews and Fung Vegetation Type
data type
integer
file type
binary
columns
360
rows
180
ref. system
lat/long
ref. units
deg
unit dist.
1.0000000
min. X
-180.0000000
max. X
180.0000000
min. Y
-90.0000000
max. Y
90.0000000
pos'n error
unknown
resolution
1.0000000
min. value
0
max. value
178
value units
characteristic classes
value error
unknown
flag value
-1
flag def'n
flag value signifies water
legend cats
179
Legend:
category
0
0
other land
(non-wet)
category
1
1
l.A.l
Tropical evergreen rainforest
category
2
2
l.A.la
lowland
category
3
3
l.A.lb
submontane
category
4
4
l.A.lc
montane
category
5
5
l.A.lc2
needleleaved
category
6
6
l.A.le
cloud
category
7
7
l.A.lf
alluvial
category
8
8
l.A.lfl
frequently flooded
category
9
9
l.A.lf3
seasonally water-logged
category
10
10
l.A.lg
swamp
category
11
11
1.A.lg2
dominated by palms
category
12
12
l.A.lh
bog
category
13
13
1.A.2
Tropical/subtropical evergreen seasonal
forest
category
14
14
1.A.2&
lowland
category
15
15
l.A.2b
submontane
category
16
16
l.A.2b2
needleleaved
category
17
17
l.A.2c
montane
category
18
18
1.A.3
Tropical/subtropical semi-deciduous forest
category
19
19
1.A.4
Subtropical evergreen rainforest
category
20
20
l.A.4b
submontane
category
21
21
1.A.4C
montane
category
22
22
1.A.4C2
needleleaved
category
23
23
l.A.4£
alluvial
category
24
24
1.A.5
Mangrove forest
GED 1.0 Documentation Methane Emieaim of Natural Wetlandg
A09-9
-------
category
25 :
25
1.A.6
Temperate/subpolar evergreen rainforest
category
26 :
26
1.A.6a
temperate
category
27 :
27
1.A.6al
broadleaved
category
28 :
28
1.A.6a2
broadleaved with needleleaved trees
category
29 :
29
1.A.7
Temperate evergreen broadleaved seasonal
forest
category
30 :
30
1.A.8
Evergreen broadleaved sclerophyllous forest
(winter r
category
31 :
31
l.A.8a
1owland/submont ane
category
32 :
32
1. A. 8b
lowland/submontane, generally less than 50m
tall
category
33 :
33
1.A.9
Tropical/subtropical evergreen needleleaved
forest
category
34
34
1.A.9a
1 owl and / submont cine
category
35
35
l.A.9b
lowland/subalpine
category
36
36
1.A.-10
Temperate/subpolar evergreen needleleaved
forest
category
37
37
l.A.lOc
with conical crowns
category
38
38
l.A.lOd
with cylindro-conical crowns (boreal)
category
39
39
l.A.lOe
with cylindro-conical crowns
(boreal):water-logge
category
40
40
l.B.l
Tropical/subtropical drought-deciduous forest
category
41
41
l.B.la
broadleaved lowland/submontane
category
42
42
1.B.lb
montane (and cloud)
category
43
43
1.B.2
Cold-deciduous broadleaved forest with
evergreen tree
category
44
44
l.B.2a
with evergreen broadleaved trees and
climbers
category
45
45
l.B.2b
with evergreen needleleaved trees
category
46
46
l.B.2c
subalpine and subpolar
category
47
47
l.B.2d
subalpine/subpolar alluvial
category
48
48
1. B. 2e
waterlogged
category
49
49
1.B.3
Cold-deciduous forest without evergreen trees
category
50
50
l.B.3a
temperate 1owland/submontane
category
51
51
l.B.3b
mont ane/borea1
category
52
52
l.B.3bl
broadleaved
category
53
53
l.B.3b2
needleleaved (e.g. Larix)
category
54
54
l.B.3c
subalpine/subpolar
category
55
55
l.B.3d
alluvial
category
56
56
l.B.3d2
regularly flooded with abundant herbaceous
underg
category
57
: 57
1.B.3e
swamp or peat
category
58
: 58
l.C.l
Extremely xeromorphic sclerophyllous-
dominated forest
category
59
59
l.C.2
Extremely xeromorphic thorn forest
category
60
60
l.C.2a
mixed deciduous-evergreen
category
61
61
l.C.2b
deciduous
category
62
62
l.C.2c
evergreen
category
63
63
2.A.1
Evergreen broadleaved woodland
category
64
64
2.A.2
Evergreen needleleaved woodland
category
65
65
2.A.2a
with rounded crowns
category
66
66
2.A.2al
with evergreen sclerophyllous understorey
(Medite
category
67
: 67
2.A.2b
with conical crowns (subalpine)
category
68
: 68
2.A.2c
with cylindro-conical crowns (boreal)
category
69
: 69
2.A.2d
waterlogged
category
70
: 70
2.B.1
Tropical/subtropical drought-deciduous
GED 1.0 Documentation Methane Emission of Natural Wetlands A09-10
-------
woodland
category
71
71
2.B.la
1owland/submont ane, broadleaved
category
72
72
2.B.lb
montane (and cloud)
category
73
73
2.B.2
Cold-deciduous woodland with evergreen trees
category
74
74
2.B.3a
broadleaved (2.B.3 Cold-deciduous woodland
without
category
75
75
2.B.3b
needleleaved
category
76
76
2.B.3b2
mixed broadleaved-needleleaved
category
77
77
2.C
Extremely xeromorphic woodland
category
78
78
2.C.1
Extremely xeromorphic
schlerophyllous-dominated woodl
category
79
79
2.C.2
Extremely xeromorphic thorn woodland
category
80
80
2.C.2a
mixed deciduous-evergreen
category
81
81
2.C.2c
deciduous
category
82
82
2.C.3
Extremely xeromorphic succulent woodland
category
83
83
3 . A.l
Evergreen broadleaved shrubland or thicket
category
84
84
3.A.la
low bamboo thicket
category
85
85
3.A.Id
sclerophyllous shrubland or thicket
category
86
86
3.A.2
Evergreen needleleaved or microphyllous
shrubland or
category
87
87
3.A.2a
needleleaved
category
88
88
3.A.3b
microphyllous
category
89
89
3.B.1
Drought-deciduous shrubland with evergreens
category
90
90
3.B.2
Drought-deciduous shrubland without
evergreens
category
91
91
3.B.2b
subalpine/subpolar
category
92
92
3.B.3b
subalpine/subpolar (3.B.3 CoId-deciduous
shrubland)
category
93
93
3.B.3bl
dwarf shrubland, with forbs
category
94
94
3.B.3b2
dwarf shrubland, with lichens
category
95
95
3.b.3c
alluvial
category
96
96
3. C
Extremely xeromorphic subdesert shrubland
category
97
97
3.C.1
Extremely xeromorphic evergreen subdesert
shrubland
category
98
: 98
3.C.la
evergreen
category
99
: 99
3.C.lal
broadleaved
categorylOO
: 100
3.C.la2
microphyllous, or leafless with green stems
categorylOl
: 101
3.C.Ia3
succulent
category102
: 102
3.C.lb
s emi-deciduous
category103
: 103
3. C.lbl
facultatively deciduous
category104
s 104
3.C.2
Extremely xeromorphic deciduous subdesert
shrubland
categoryl05
: 105
3.C.2b
with succulents
categoryl06
: 106
4.A.l
Evergreen dwarf-shrub thicket
category107
: 107
4.A.2
Evergreen dwarf shrubland
category 108
: 108
4.A.2a
dense cushion
categorylOS
: 109
4.A.3
Mixed evergreen dwarf shrub/herbaceous
formation
categoryllO
: 110
4. C
Extremely xeromorphic subdesert dwarf
shrubland
category111
; 111
4.C.la
evergreen (4.C.1 Extremely xeromorphic
subdesert dw
categoryll2
: 112
4.C.2
Extremely xeromorphic deciduous subdesert
dwarf shrub
categoryll3
: 113
4.D
Tundra
category 114
: 114
4.D.1
Mainly bryophyte tundra
categoryll5
: 115
4.D.2
Mainly lichen tundra
GED 1.0 Documentation Meihane Emittion of Natural Wetland* A09-11
-------
category116
: 116
4.D.2a
categoryll7
: 117
4.D.2b
category118
: 118
4. E
categoryll9
: 119
4.E.2b
categoryl20
: 120
5.A.1
category121
: 121
5.A.la
category122
: 122
5.A.lal
category123
: 123
5.A.lc
category124
: 124
5.A.lcl
category125
: 125
5.A.Ic2
categoryl26
: 126
5.A.2
category127
: 127
5.A.2c
categoryi28
: 128
5.A.3c
categoryl29
: 129
5.A.4
categoryl30
: 130
5.A.5
categoryl31
: 131
5.A.5a
category132
: 132
5.A.5al
category133
: 133
5.A.5a2
category 134
: 134
5.B.1
categoryl35
: 135
5.B.la
categoryl36
: 136
5.B.lal
category137
: 137
5.B.lb
categoryl38
: 138
5.B.lc
categoryl39
: 139
5.B.2
categoryl40
: 140
5.B.3
category141
: 141
5.B.3c
categoryl42
: 142
5.B.3e
categoryl43
: 143
5.B.4
categoryl44
: 144
5.B.4a
categoryl45
: 145
5.B.5
category 146
: 146
5.B.5al
categoryl47
: 147
5.B.5a2
categoryl48
: 148
5.B.5b
category149
: 149
5.B.5b2
categoryl50
: 150
5.C.1
categoryl51
: 151
5.C.la
categoryl52
: 152
5-C.lc
categoryl53
: 153
5.C.Id
categoryl54
: 154
5.C.2
categoryl55
: 155
5.C.2al
category156
: 156
5.C.2c
categoryl57
: 157
5.C.3
category158
: 158
5.C.3b
categoryl59
: 159
5.C.3c
category 160
: 160
5.C.3e
categoryl61
; 161
5.C.5
categoryl62
: 162
5.C.5a
categoryl63
: 163
5.C.5b
categoryl64
: 164
5.C.5d
categoryl65
: 165
5.C.6
with caespitose dwarf shrubs and moss
with creeping or matted dwarf shrubs and
moss
Mossy bog formations with dwarf shrubs
string bog (4.E.2 Non-raised mossy bog)
Tall grassland with 10-40% tree cover
with evergreen broadleaved tree cover
wet or flooded most of year
with deciduous broadleaved tree cover
seasonally flooded
with deciduous broadleaved tree cover
Tall grassland with < 10% tree cover
with deciduous broadleaved tree cover
with deciduous broadleaved shrub cover
Tall grassland with tuft plant cover (usually
palms)
Tall grassland without woody cover
tropical grassland
seasonally flooded
wet or flooded most of year
Medium grassland with 10-40% tree cover
with evergreen broadleaved tree cover
wet or flooded most of year
with semi-evergreen broadleaved tree cover
with deciduous broadleaved tree cover
Medium grassland with <10% tree cover
Medium grassland with shrub cover
with deciduous broadleaved shrub cover
with deciduous thorny shrub cover
Medium grassland with open cover of tuft
plants (usua
subtropical, with open groves of palms
Medium grassland without woody cover
wet or flooded most of year (5.B.5a mainly
sod gr
on sandy soil or dunes
mainly bunch grasses
wet or flooded most of year
Short Grassland with 10-40% tree cover
with evergreen broadleaved tree cover
with deciduous broadleaved tree cover
with evergreen needleleaved tree cover
Short grassland with < 10% tree cover
seasonally flooded (5.C.2a with evergreen
broadle
with deciduous broadleaved tree cover
Short grassland with shrub cover
with semi-evergreen broadleaved shrub cover
with deciduous broadleaved shrub cover
with deciduous thorny shrub cover
Short grassland without woody cover
tropical alpine, open/closed bunch-grasses
wijth tuf
tropical alpine, open bunch grasses
bunch grasses of varying coverage with dwarf
shrubs
Short grassland without woody cover
GED1.0 Documentation Methane Emiuion of Natural Wetlands
A09-12
-------
categoryl66 :
166
5.C.6a
categoryl67 :
categoryl68 :
167
168
5.C.6b
5.C.7
category169 :
169
5.C.7a
category170 :
categoryl71 :
170
171
5.C.7b
5.C.7b2
categoryl72 :
172
5•C.7b3
categoryl73 s
categoryl74 :
173
174
5.C.8
5.C.8a
category175 :
categoryl76 :
categoryl77 :
category178 :
175
176
177
178
5.D.2
5.D.2a
6
7
NOTES:
short-grass communities in semi-arid
climates
bunch-grass communities (tussock)
Short to medium tall mesophytic grassland
(meadow)
sodgrass communities, forbs in low altitude,
cool h
alpine/subalpine meadows, high latitudes
alpine/subalpine meadows, high latitudes,
rich in
snow-bed communities in high latitude
alpine/suba
Graminoid tundra
bunch-form with mosses and lichens
(Eriophorum)
Low forb communities (< lm)
perennial flowering forbs and ferns
desert
ice
GED1.0 Documentation Mttiutm Embtion of Vi*tu*4$
A09-13
-------
DATA ELEMENT: Soil Types
STRUCTURE: Raster Data Files: 1-degree GED 180x360 grid (see User's Guide)
SERIES: none
SPATIAL DATA FILES:
MFWSOLDOC
file title
FAO Soil Types of Matthews & Fung Wetland Locations
data type
integer
file type
binary
columns
360
rows
180
ref. system
lat/long
ref. units
deg
unit dist.
1.0000000
min. X
-180.0000000
max. X
180.0000000
min. Y
-90.0000000
max. Y
90.0000000
pos'n error
unknown
resolution
1.0000000
min. value
0
max. value
107
value units
characteristic classes
value error
unknown
flag value
-1
flag def'n
flag value signifies water
legend cats
108
Legend:
category
0
0
other
land (non-wet)
category
1
1
AF
Ferric Acrisol
category
2
2
AG
Gleyic Acrisol
category
3
3
AH
Humic Acrisol
category
4
4
AO
Orthic Acrisol
category
5
5
AP
Plinthic Acrisol
category
6
6
BC
Chromic Cambisol
category
7
7
BD
Dystric Cambisol
category
8
8
BE
Eutric Cambisol
category
9
9
BF
Ferralic Cambisol
category
10
10
B6
Gleyic Cambisol
category
11
11
BH
Humic Cambisol
category
12
12
BK
Calcic Cambisol
category
13
13
BV
Vertic Cambisol
category
14
14
BX
Gelic Cambisol
category
15
15
CG
Glossic Chernozem
category
16
16
CH
Haplic Chernozem
category
17
17
CK
Calcic Chernozem
category
18
18
CL
Luvic Chernozem
category
19
19
DD
Dystric Podzoluvisol
category
20
20
DE
Eutric Podzoluvisol
category
21
21
DG
Gleyic Podzoluvisol
category
22
22
E
Rendzina
category
23
23
FA
Acric Ferralsol
category
24
24
FH
Humic Ferralsol
category
25
25
FO
Orthic Ferralsol
GED 1.0 Documentation Methatu Emluion of Natural Wetland*
A09-14
-------
category 26
category 27
category 28
category 29
category 30
category 31
category 32
category 33
category 34
category 35
category 36
category 37
category 38
category 39
category 40
category 41
category 42
category 43
category 44
category 45
category 46
category 47
category 48
category 49
category 50
category 51
category 52
category 53
category 54
category 55
category 56
category 57
category 58
category 59
category 60
category 61
category 62
category 63
category 64
category 65
category 66
category 67
category 68
category 69
category 70
category 71
category 72
category 73
category 74
category 75
category 76
category 77
category 78
category 79
category 80
category 81
category 82
26
FP
Plinthic Ferralsol
27
FR
Rhodic Ferralsol
28
FX
Xanthic Ferralsol
29
GC
Calcaric Gleysol
30
GD
Dystric Gleysol
31
GE
Eutric Gleysol
32
GH
Humic Gleysol
33
GM
Mollic Gleysol
34
GP
Plinthic Gleysol
35
GX
Gelic Gleysol
36
HC
Calcic Phaeozem
37
HG
Gleyic Phaeozem
38
HH
Haplic Phaeozem
39
HL
Luvic Phaeozem
40
I
Lithosol
41
JC
Calcaric Fluvisol
42
JD
Dystric Fluvisol
43
JE
Eutric Fluvisol
44
JT
Thionic Fluvisol
45
KH
Haplic Kastanozem
46
KK
Calcic Kastanozem
47
KL
Luvic Kastanozem
48
LA
Albic Luvisol
49
LC
Chromic Luvisol
50
LF
Ferric Luvisol
51
LG
Gleyic Luvisol
52
LK
Calcic Luvisol
53
LO
Orthic Luvisol
54
LP
Plinthic Luvisol
55
LV
Vertic Luvisol
56
MG
Gleyic Greyzem
57
MO
Orthic Greyzem
58
ND
Dystric Nitosol
59
ME
Eutric Nitosol
60
NH
Humic Nitoaols
61
OD
Dystric Histosol
62
OE
Eutric Histosol
63
OX
Gelic Histosol
64
PF
Ferric Podzol
65
PG
Gleyic Podzol
66
PH
Humic Podzol
67
PL
Leptiv Podzol
68
PO
Orthic Podzol
69
PP
Placic Podzol
70
QA
Albic Arenosol
71
QC
Cambic Arenosol
72
QF
Ferralic Arenosol
73
QL
Luvic Arenosol
74
RC
Calcaric Regosol
75
RD
Dystic Regosol
76
RE
Eutric Regosol
77
RX
Gelic Regosol
78
SG
Gleyic Solonetz
79
SM
Mollic Solonetz
80
SO
Orthic Solonetz
81
TH
Humic Andosol
82
TM
Mollic Andosol
GED 1.0 Documentation Methane Emission of Natural Wetland*
A09-15
-------
category
83
83
TO
Ochric Andosol
category
84
84
TV
Vitric Andosol
category
85
85
U
Ranker
category
86
86
VC
Chromic Vertisol
category
87
87
VP
Pellic Vertisol
category
88
88
WD
Dystric Planosol
category
89
89
WE
Eutric Planosol
category
90
90
WH
Humic Planosol
category
91
91
WM
Mollic Planosol
category
92
92
WS
Solodic Planosol
category
93
93
WX
Gelic Planosol
category
94
94
XH
Haplic Xerosol
category
95
95
XK
Calcic Xerosol
category
96
96
XL
Luvic Xerosol
category
97
97
XY
Gypsic Xerosol
category
98
98
YH
Haplic Yermosol
category
99
99
YK
Calcic Yermosol
categorylOO
100
YL
Luvic Yermosol
categorylOl
101
YT
Takyric Yermosol
categoryl02
102
YY
Gypsic Yermosol
categoryl03
103
ZG
Gleyic Solonchak
category104
104
ZM
Mollic Solonchak
categoryl05
105
ZO
Orthic Solonchak
categoryl06
106
ZT
Takyric Solonchak
category 107
107
ice
NOTES:
GED1.0 Documentation MetfiatM Emtofcm of NafuralWetimnJ*
A09-16
-------
DATA INTEGRATION AND QUALITY
Mark A. Ohrenschall
NOAA National Geophysical Data Cento1
Boulder, CO
Data were read from floppy disk and converted to the GED format, separating each
variable into different GIS files without altering the original numerical values. Legend
information was entered from the accompanying documentation. All final data files
were inspected for agreement with the original data.
GED 1.0 Documentation Metimn* Emttrim ofNmimrml Wttltmda
A09-17
-------
A10
Wilson and Henderson-Sellers Global Land Cover and
Soils data for GCMs
GGD 1.0 Documentation Land Cover and Soilt data for GCM*
A10
-------
DATA-SET DESCRIPTION
DATA-SET NAME: Global Land Cover and Soils Data for GCMs
PRINCIPAL INVESTIGATORS): MJ. Mylne (n6e Wilson) and Anne
Henderson-Sellers
SOURCE
SOURCE DATA CITATION: Wilson, M.F. and A. Henderson-Sellers, 1985. A global
archive of land cover and soils data for use in general circulation climate models. Digital
Raster Data on a 1-degree Geographic (lat/long) 180x360 grid. NCAR, Boulder,
Colorado. 0.3 MB.
CONTRIBUTORS): Dr. Anne Henderson-Sellers, Director
Climatic Impacts Centre
Macquarie University
School of Earth Sciences
New South Wales: 2109 : Australia
DISTRIBUTORS): NCAR
VINTAGE: circa 1980's
LINEAGE: (1) M.F. Mylne (formerly Wilson) and A. Henderson-Sellers, Principal
Investigators
Department of Geography
University of Liverpool (U.K.)
(2) Data archived and distributed by:
Roy Jenne
National Center for Atmospheric Research (NCAR)
ORIGINAL DESIGN
VARIABLES: Characteristic lxl-degree vegetation, soil and reliability classes
ORIGIN: Integrated data sources including the FAO/UNESCO Soil Map of the World,
Oxford Regional Economic Atlas of the USSR and Eastern Europe, and Central
Asia and East European map sheets.
GEOGRAPHIC REFERENCE: lat/long
GEOGRAPHIC COVERAGE: Global
Maximum Latitude : +90 degrees (N)
Minimum Latitude : -90 degrees (S)
Maximum Longitude ; +180 degrees (E)
Minimum Longitude : -180 degrees (W)
GEOGRAPHIC SAMPLING: Characteristic classes for 1-degree grid cell areas
GED 1.0 Documentation Lund Cover and Sofa tot* for GChb
A10-2
-------
TIME PERIOD: Modern period, circa 196CS and 7CS
TEMPORAL SAMPLING: Modem composite
INTEGRATED DATA-SET
DATA-SET CITATION: Wilson, M.F. and A. Henderson-Sellers. 1992. A global archive of
land cover and soils data for use in general circulation climate models. Digital Raster
Data on a 1-degree Geographic (lat/long) 180x360 grid. In: Global Ecosystems
Database Version 1.0: Disc A. Boulder, CO: NOAA National Geophysical Data
Center. 5 independent single-attribute spatial layers on CD-ROM, 0.3M6. [first
published in 1985]
ANALYST^): M.F. Mylne (n6e Wilson) and Anne Henderson-Sellers
PROJECTION: Geographic (lat/long), GED window (see User's Guide).
SPATIAL REPRESENTATION: Characteristic classes for 1-degree grid cells
TEMPORAL REPRESENTATION: Modern composite
DATA REPRESENTATION: 1-byte integer values representing characteristic classes and
reliability codes for 1-degree grid cells.
LAYERS AND ATTRIBUTES: 3 independent single-attrubute spatial layers with 2
attribute layers (represented as raster data files for convenience).
COMPRESSED DATA VOLUME: 29,038 bytes
PRIMARY REFERENCES (~ reprint on CD-ROM)
* Wilson, M.F., and A. Henderson-Sellers, 1985. "A Global Archive of Land Cover
and Soils Data for Use in General Circulation Climate Models." Journal of
Climatology, vol. 5, pp. 119 -143.
ADDITIONAL REFERENCES
* Henderson-Sellers, A., M.F. Wilson, G. Thomas, and R.E. Dickenson. 1986. Current
Global land-Surface Data Sets for Use in Climate-Related Studies. NCAR Technical
Note TN-272+STR. Boulder, CO National Center for Atmospheric Research.
GED 1.0 Documentation Land Caotx and Soil* data for GCM»
A10-3
-------
DATA-SET FILES
LOCATION
NAME
NUMBER
touvl arzB
Spatial Data:
\GLGEO\RASTER\
WHCOV1.IMG
1 files
64,800
WHCOV2.IMG
1 files
64,800
WHLREL.IMG
1 files
64,800
WHSOIL.IMG
1 files
64,800
WHSREL.IMG
1 files
64,800
Headers:
\GLGEO\RASTER\
WHCOV1.DOC
1 files
3, 988
WHCOV2.DOC
1 files
3, 990
WHLREL.DOC
1 files
630
WHSOIL.DOC
1 files
2,203
WHSREL.DOC
1 files
650
Palettes t
none
Time Series:
none
Volume on Disk:
10 files
335,461
REPRINT FILES
LOCATION
NAME
NUMBER
mat, sds
\DOCUMENT\A10\
WH1_01PCX to WH1 25.PCX
25 files
975,479
WH1_##X.PCX
10 files
966,891
WH2_001.PCX to WH2_108.PCX
108 files
2,446,005
WH2_# # #X.PCX
27 files
2,241,326
Volume on Disk* 170 files 6,629,701
SOURCE EXAMPLE FILES
none
GED1.0 Documentation Land Cover and Soil* data for GCMb
A10-4
-------
FILE DESCRIPTION
DATA ELEMENT: Primary and Secondary Vegetation Class
STRUCTURE: Raster Data Files: 1-degree GED 180x360 grid (see User's Guide)
SERIES: primary and secondary classes
SPATIAL DATA FILES:
WHCOV1.DOC
file title
Wilson & Henderson-Sellers Primary Land Cover Classes
data type
byte
file type
binary
columns
360
rows
180
ref. system
lat/long
ref. units
deg
unit dist.
1.0000000
min. X
-180.0000000
max. X
180.0000000
min. Y
-90.0000000
max. Y
90.0000000
pos'n error
unknown
resolution
1.0000000
min. value
0
max. value
73
value units
characteristic classes
value error
: unknown
flag value
: none
flag def'n
: none
legend cats
: 81
File Series Parameters:
File Description Minimum Maximum
WHCOV1 Primary Land-Cover Classes 0 73
WHCOV2 Secondary Land-Cover Classes 0 80
Legend:
category 0
category 1
category 2
category 3
category 4
category 5
category 6
category 7
category 8
category 9
category 10
category 11
category 12
0 Open Water
1 INW Inland water
2 BOM Bog or marsh
3 ICE Ice
4 PAR Paddy rice
5 MAN Mangrove (tree swamp)
6 Not used
7 Not used
8 Not used
9 Not used
10 ONE Dense needleleaf evergreen forest
11 ONE Open needleleaf evergreen woodland
12 DMN Dense mixed needleleaf and broadleaf, evergreen and
deciduous forest
GED 1.0 Documentation Land Cover and Soils data for GCMa
A10-5
-------
category
13 :
13
OMN
Open mixed needleleaf and broadleaf, evergreen
deciduous woodland
category
14 :
14
EBW
Evergreen broadleaf woodland
category
15 :
15
EBC
Evergreen broadleaf cropland
category
16 :
16
EBS
Evergreen broadleaf shrub
category
17 :
17
ODN
Open deciduous needleleaf woodland
category
18 :
18
DDN
Dense deciduous needleleaf forest
category
19 :
19
DEB
Dense evergreen broadleaf forest
category
20 :
20
DDB
Dense deciduous broadleaf forest
category
21 :
21
ODB
Open deciduous broadleaf woodland
category
22 :
22
DTC
Deciduous tree crops (temperate)
category
23 :
23
OTW
Open tropical woodland
category
24 :
24
WOS
Woodland + shrub
category
25 :
25
DDD
Dense drought deciduous forest
category
26 :
26
ODD
Open drought deciduous woodland
category
27 :
27
DES
Deciduous shrub
category
28 :
28
THS
Thorn shrub
category
29 :
29
Not
used
category
30 :
30
TMP
Temperate meadow and permanent pasture
category
31 :
31
TRG
Temperate rough grazing
category
32 :
32
TGS
Tropical grassland + shrub
category
33 :
; 33
TRP
Tropical pasture
category
34 :
: 34
RGS
Rough grazing + shrub
category
35 :
: 35
PAT
Pasture + tree
category
36 :
: 36
SAR
Semi arid rough grazing
category
37 :
i 37
TSG
Tropical Savanna (grassland + tree)
category
38 s
: 38
Not
used
category
39 !
: 39
PAS
Pasture + shrub
category
40 :
: 40
ARC
Arable cropland
category
41 :
: 41
DFA
Dry farm arable
category
42 :
: 42
NMG
Nursery and market gardening
category
43 :
: 43
CAS
Cane sugar
category
44
: 44
MAI
Maize
category
45
: 45
COT
Cotton
category
46
: 46
COF
Coffee
category
47
: 47
VIN
Vineyard
category
48
: 48
IRG
Irrigated cropland
category
49
: 49
TEA
Tea
category
50
: 50
ERF
Equatorial rain forest
category
51
: 51
ETC
Equatorial tree crop
category
52
: 52
TBF
Tropical broadleaf forest (slight seasonality)
category
53
: 53
Not
used
category
54
: 54
Not
used
category
55
: 55
Not
used
category
56
: 56
Not
used
category
57
: 57
Not
used
category
58
: 58
Not
used
category
59
: 59
Not
used
category
60
: 60
Not
used
category
61
: 61
TUN
Tundra
category
62
: 62
DWS
Dwarf shrub (tundra transition and high altitu
wasteland)
category
63
: 63
Not
used
category
64
: 64
Not
used
category
65
: 65
Not
used
category
66
: -66
Not
used
category
67
: 67
Not
used
GED 1.0 Documentation L*nd Cover mud Soil* data for GCMt
A10-6
-------
category
68 :
68
Not used
category
69 :
: 69
Not used
category
70 :
; 70
SDB Sand desert and barren land
category
71 :
: 71
SDS Scrub desert and semi desert
category
72 :
! 72
Not used
category
73 :
: 73
SDT Semi desert + scattered trees
category
74 :
: 74
Not used
category
75 ;
: 75
Not used
category
76 ;
¦ 76
Not used
category
77 :
: 77
Not used
category
78 :
: 78
Not used
category
79 :
: 79
Not used
category
80 :
: 80
Urban
NOTES:
GED l.o Documentation Land Cover and Soil$ data jot GCM» A10-7
-------
DATA ELEMENT; Soil Class
STRUCTURE: Raster Data Files: 1-degree GED 180x360 grid (see User's Guide)
SERIES: primary and secondary classes
SPATIAL DATA FILES:
WHSOIL.DOC
file title
: Wilson & Henderson-Sellers Code and Properties of Soil
Classes
data type
byte
file type
binary
columns
360
rows
180
ref. system
lat/long
ref. units
deg
unit dist.
1.0000000
min. X
-180.0000000
max. X
180.0000000
min. Y
-90.0000000
max. Y
90.0000000
pos'n error
unknown
resolution
1.0000000
min. value
0
max. value
34
value units
characteristic classes
value error
unknown
flag value
none
flag def'n
none
legend cats
35
Legend:
category
0 :
0
category
1 :
1
not
used
category
2 :
2
not
used
category
3 :
3
not
used
category
4 :
4
not
used
category
5 :
5
not
used
category
6 :
6
not
used
category
7 :
7
not
used
category
8 :
8
not
used
category
9 :
9
not
used
category
10 j
; 10
not
used
category
11 :
: 11
LCF
LIGHT, COARSE, FREE
category
12 :
: 12
LIF
LIGHT, INTERMEDIATE, FREE
category
13 :
: 13
LFF
LIGHT, FINE, FREE
category
14 !
: 14
LCI
LIGHT, COARSE, IMPEDED
category
15 :
: 15
LI I
LIGHT, INTERMEDIATE, IMPEDED
category
16 :
: 16
LFI
LIGHT, FINE, IMPEDED
category
17 !
: 17
MCF
MEDIUM, COARSE, FREE
category
18 !
: 18
MIF
MEDIUM, INTERMEDIATE, FREE
category
19 :
: 19
MFF
MEDIUM, FINE, FREE
category
20 i
: 20
MCI
MEDIUM, COARSE, IMPEDED
category
21 ;
: 21
Mil
MEDIUM, INTERMEDIATE, IMPEDED
category
22 :
: 22
MFI
MEDIUM, FINE, IMPEDED
category
23 :
: 23
DCF
DARK, COARSE, FREE
category
24 :
: 24
DIP
DARK, INTERMEDIATE, FREE
GED 1.0 Documentation Land Cover and Soils data for GCMt
A10-8
-------
category 25
category 26
category 27
category 28
category 29
category 30
category 31
category 32
category 33
category 34
25 DFF
26 DCI
27 DII
28 DFI
29 L-P
30 M-P
31 D-P
32 not used
33 not used
34 ICE
DARK, FINE, FREE
DARK, COARSE, IMPEDED
DARK, INTERMEDIATE, IMPEDED
DARK, FINE, IMPEDED
LIGHT, —, POOR
MEDIUM, —, POOR
DARK, POOR
NOTES:
1. Categories refer to COLOR, TEXTURE, DRAINAGE
2. In the printed documentation Code 32 is listed between 25 and 27 which is taken
as a typographical error since Code 26 has nine occurences and Code 32 has zero
occurences.
GED 1.0 Documentation Land Cotter and Soils data for GCMt
A10-9
-------
DATA ELEMENT: Vegetation and Soil Class reliability
STRUCTURE: Raster Data Files: 1-degree GED 180x360 grid (see User's Guide)
SERIES: reliability files for each primary variable (vegetation and soils)
SPATIAL DATA FILES:
WHLREL.DOC
file title
Wilson & Henderson-Sellers Land Cover Reliability
data type
byte
file type
binary
columns
360
rows
180
ref. system
lat/long
ref. units
deg
unit dist.
1.0000000
min. X
-180.0000000
max. X
180.0000000
min. Y
-90.0000000
max. Y
90.0000000
pos'n error
unknown
resolution
1.0000000
min. value
0
max. value
5
value units
characteristic classes
value error
unknown
flag value
none
flag def'n
none
legend cats
6
File Series:
File Description Minimum Maximum
WHLREL Land-Cover Class Reliability 0 5
WHSREL Soil Class Reliability 0 5
Legends:
WHLREL.DOC
WHSREL.DOC
category 0 :
: 0
category 0 :
: 0
category 1 :
: 1 High
category 1 :
; 1
High
category 2 :
: 2
category 2 :
: 2
Good
category 3 :
i 3
category 3 :
: 3
Moderate
category 4 :
: 4
category 4 :
: 4
Fair
category 5 :
: 5 Low
category 5 :
: 5
Poor
NOTES:
GED 1.0 Documentation land Cover and Soils data for GCMi
AlO-10
-------
DATA INTEGRATION AND QUALITY
Mark A. Ohrenschall
NOAA National Geophysical Data Center
Boulder, CO
Data were read from floppy disk and converted to the GED format, separating each
variable into different GIS files without altering the original numerical values. Legend
information was entered from the accompanying documentation. All final data files
were inspected for agreement with the original data.
GED 1.0 Documentation Lund Cover and Soil* data for GCMt
A10-11
-------
All
Staub and Rosensweig Zobler Soil Type, Soil Texture,
Surface Slope, and Other Properties
GED 1.0 Documentation Soil Type, Soil Textmrt, Surfac* Slop*, tmd Other Prop*rti*» All
-------
DATA-SET DESCRIPTION
DATA-SET NAME: Zobler Soil Type, Soil Texture, Surface Slope, and
Other Properties
PRINCIPAL INVESTIGATORS): Leonard Zobler
NASA Goddard Institute for Space
Studies
SOURCE
SOURCE DATA CITATION: Staub, B. and C. Rosenzweig, 1987. Global Digital Data
Sets of Soil Type, Soil Texture, Surface Slope, and Other Properties. Digital Raster Data
on a 1-degree Geographic (lat/long) 180x360 grid. NCAR, Boulder, Colorado.
0.45 MB.
CONTRIBUTORS): Dr. Leonard Zobler
Goddard Institute of Space Science
Columbia University
2880 Broadway
New York, NY 10025 USA
DISTRIBUTORS): NCAR
VINTAGE: circa 1980's
LINEAGE: (1) Principal Investigator:
Leonard Zobler
Columbia University
NASA Goddard Institute for Space Studies
(2) Reprocessed and edited by:
Brad Staub and Cynthia Rosenzweig
NASA Goddard Institute for Space Studies
ORIGINAL DESIGN
VARIABLES: Dominant FAO soils and related classes: Soil Tvpe. Associated and
Included Soils. Near-Surface Texture (upper 30cm), Slope. Phase. Area. Special
Codes for missing data and conflicting nominal classification (land, land-ice,
water) between Zobler and Matthews.
ORIGIN: Data based on FAO Soils Map of the World (1974), digitized by Zobler (1986);
and Matthews' vegetation data-set (see AO7), with editorial additions and
comparisons by Staub and Rosenzweig.
GED 1.0 Documentation Soil Type, Soil Texture, Surface Slope, and Other Properties
All-2
-------
GEOGRAPHIC REFERENCE: lat/long
GEOGRAPHIC COVERAGE: Global
Maximum Latitude
Minimum Latitude
Maximum Longitude
Minimum Longitude
+90 degrees (N)
-90 degrees (S)
+180 degrees (E)
-180 degrees (W)
GEOGRAPHIC SAMPLING: Characteristic classes for 1-degree grid cell areas
TIME PERIOD: Modern period, circa 196Cs and 7Cs
TEMPORAL SAMPLING: Modern composite
INTEGRATED DATA-SET
DATA-SET CITATION: Staub, B. and C. Rosenzweig. 1992. Global Zobler Soil Type,
Soil Texture, Surface Slope, and Other Properties. Digital Raster Data on a 1-
degree Geographic (lat/long) 180x360 grid. In: Global Ecosystems Database Version
1.0: Disc A. Boulder, CO: NOAA National Geophysical Data Center. 7
independent single-attribute spatial layers on CD-ROM, 0.45 MB. [first published
in 1986]
ANALYSTS): Brad Staub and Cynthia Rosenzweig, NASA/GISS, New York, New York
PROJECTION: Geographic (lat/long), GED window (see User's Guide).
SPATIAL REPRESENTATION: Characteristic classes for 1-degree grid cell areas
TEMPORAL REPRESENTATION: Modern composite
DATA REPRESENTATION: 1-byte integer codes representing characteristic classes
within grid cells; except for Associated and Included Soils, which is stored as 2-
byte integer codes.
LAYERS AND ATTRIBUTES; 7 independent single-attribute spatial layers
COMPRESSED DATA VOLUME: 48,226 bytes
PRIMARY REFERENCES (* reprint on CD-ROM)
* Staub, Brad and Cynthia Rosenzweig. 1986. "Global Digital Data Sets of Soil Type,
Soil Texture, Surface Slope, and Other Properties: Documentation of
Archived Tape Data." NASA Technical Memorandum #100685.
Zobler, L. 1986. "A world soil file for global climate modeling." NASA Technical
Memorandum #87802.
ADDITIONAL REFERENCES
Henderson-Sellers, A., M.F. Wilson, G. Thomas, R.E. Dickinson, 1986. "Current Global
Land Surface Data Sets for Use in Climate-Related Studies." NCAR Technical Note
272+STR.
Matthews, Ev 1983. "Global vegetation and land use: New high resolution databases for
climate studies." Journal of Climatology and Applied Meteorology, vol. 22, pp. €74-487.
GED 1.0 Documentation Soil Type, Soil Textttre, Surface Slope, md Other Praptrtiu
All-3
-------
Matthews, E., 1984. "Vegetation, Land-Use and Seasonal Albedo Data Sets:
Documentation of Archived Data Tape." NASA Technical Memorandum #86107.
Wilson, M.F. and A. Henderson-Sellers, 1985. "A global archive of land cover and soils
data for use in general circulation climate models." Journal of Climatology, vol. 5,
pp. 119-143.
GED 1.0 Documentation Soil Type, Soil Texture, Surface Slope, and Other Properties
All-4
-------
DATA-SET FILES
LOCATION
NAME
NUMBER
TOUL SIZE
Spatial Data:
\GLGEO\RASTER\
SRZAREA.IMG
1
files
64,800
SRZCODE. IMG
1
files
64,800
SRZPHAS.IMG
1
files
64,800
SRZSLOP•IMG
1
files
64,800
SRZSOIL.IMG
1
files
64,800
SRZSUBS.IMG
1
files
129,600
SRZTEXT.IMG
1
files
64,800
Headers:
\GLGEO\META\
SRZAREA.DOC
1
files
992
SRZCODE.DOC
1
files
.1,578
SRZPHAS.DOC
1
files
5,067
SRZSLOP.DOC
1
files
835
SRZSOIL.DOC
1
files
5,332
SRZSUBS.DOC
1
files
7, 985
SRZTEXT.DOC
1
files
884
Palettes:
none
Tim* Series:
none
Volume on Disk:
14
files
541,073
REPRINT FILES
LOCATION
SMC
NUMBER
TOOffiSEE
\DOCUMENT\A11\
SR_01.PCX to SR_17.PCX
17 files
327,164
Volume on Disk: 17 files 327,164
SOURCE EXAMPLE FILES
none
GED 1.0 Documentation Soil Type, Soil Texture, Surftce Slop*, and Other Properties
All-5
-------
FILE DESCRIPTION
DATA ELEMENT: Soil Type
STRUCTURE: Raster Data Files: 1-degree GED 180x360 grid (see User's Guide)
SERIES: none
SPATIAL DATA FILES:
SRZSOIL.DOC
file title
J
Staub and Rosenzweig Zobler Soil Units
data type
;
byte
file type
:
binary
columns
;
360
rows
:
180
ref. system
•
lat/long
ref. units
•
•
deg
unit dist.
J
1.0000000
min. X
•
-180.0000000
max. X
*
180.0000000
min. Y
•
-90.0000000
max. Y
:
90.0000000
pos'n error
•
•
unknown
resolution
•
1.0000000
min. value
:
0
max. value
•
107
value units
•
characteristic classes
value error
•
unknown
flag value
•
none
flag def'n
:
none
legend cats
•
•
108
Legend:
category
0
0
Water
category
1
1
99
Land-Ice
category
2
2
JE
Eutric Fluvisols
category
3
3
JC
Calcaric Fluvisols
category
4
4
JD
Dystric Fluvisols
category
5
5
JT
Thionic Fluvisols
category
6
6
GE
Eutric Gleysols
category
7
7
GC
Calcaric Gleysols
category
8
8
GD
Dystric Gleysols
category
9
9
GM
Mollic Gleysols
category
10
10
GH
Humic Gleysols
category
11
11
GP
Plinthic Gleysols
category
12
12
GX
Gelic Gleysols
category
13
13
RE
Eutric Regosols
category
14
14
RC
Calcaric Regosols
category
15
15
RD
Dystic Regosols
category
16
16
RX
Gelic Regosols
category
17
17
I
Lithosols
category
18
18
KH
Haplic Kastanozems
category
19
19
KK
Calcic Kastanozems
category
20
20
KL
Luvic Kastanozems
GED 1.0 Documentation Soil Type, Soil Textwre, Surface Slope, mi Other Properties All-6
-------
category 21
category 22
category 23
category 24
category 25
category 26
category 27
category 28
category 29
category 30
category 31
category 32
category 33
category 34
category 35
category 36
category 37
category 38
category 39
category 40
category 41
category 42
category 43
category 44
category 45
category 46
category 47
category 48
category 49
category 50
category 51
category 52
category 53
category 54
category 55
category 56
category 57
category 58
category 59
category 60
category 61
category 62
category 63
category 64
category 65
category 66
category 67
category 68
category 69
category 70
category 71
category 72
category 73
category 74
category 75
category 76
category 77
21
CH
Haplic Chernozems
22
CK
Calcic Chernozems
23
CL
Luvic Chernozems
24
CG
Glossic Chernozems
25
QC
Cambic Arenosols
26
QL
Luvic Arenosols
27
QF
Ferralic Arenosols
28
QA
Albic Arenosols
29
E
Rendzinas
30
U
Rankers
31
TO
Ochric Andosols
32
TM
Mollic Andosols
33
TH
Humic Andosols
34
TV
Vitric Andosols
35
VP
Pellic Vertisols
36
VC
Chromic Vertisols
37
HH
Haplic Phaeozems
38
HC
Calcic Phaeozems
39
HL
Luvic Phaeozems
40
HG
Gleyic Phaeozems
41
MO
Orthie Greyzems
42
MG
Gleyic Greyzems
43
ZO
Orthic Solonchaks
44
ZM
Mollic Solonchaks
45
ZT
Takyric Solonchaks
46
ZG
Gleyic Solonchaks
47
SO
Orthic Solonetz
48
SM
Mollic Solonetz
49
SG
Gleyic Solonetz
50
YH
Haplic Yermosols
51
YX
Calcic Yermosols
52
YY
Gypsic Yermosols
53
YL
Luvic Yermosols
54
YT
Takyric Yermosols
55
XH
Haplic Xerosols
56
XK
Calcic Xerosols
57
XY
Gypsic Xerosols
58
XL
Luvic Xerosols
59
BE
Eutric Cambisols
60
BD
Pystric Cambisols
61
BH
Humic Cambisols
62
BG
Gleyic Cambisols
63
BX
Gelic Cambisols
64
BK
Calcic Cambisols
65
BC
Chromic Cambisols
66
BV
Vertic Cambisols
67
BF
Ferralic Cambisols
68
LO
Orthic Luvisols
69
LC
Chromic Luvisols
70
LK
Calcic Luvisols
71
LV
Vertic Luvisols
72
LF
Ferric Luvisols
73
LA
Albic Luvisols
74
LP
Plinthic Luvisols
75
LG
Gleyic Luvisols
76
HE
Eutric Planosols
77
WD
Dystric Planosols
GED1.0 Documentation Soil Typt, Soil Ttxi*rt,$itrf*M Slop*, tndOiktrPnptrti**
All-7
-------
category
78
78
WM
category
79
79
WH
category
80
80
WS
category
81
81
WX
category
82
82
OE
category
83
83
0D
category
84
84
OX
category
85
85
DE
category
86
86
DD
category
87
87
DG
category
88
88
PO
category
89
89
PL
category
90
90
PF
category
91
91
PH
category
92
92
PP
category
93
93
PG
category
94
94
F0
category
95
95
FX
category
96
96
FR
category
97
97
FH
category
98
98
FA
category
99
99
FP
categorylOO
100
AO
categorylOl
101
AF
categoryl02
102
AH
categoryl03
103
AP
category104
104
AG
category 105
105
NE
category106
106
ND
categoryl07
107
NH
Mollic Planosols
Humic Planosols
Solodic Planosols
Gelic Planosols
Eutric Histosols
Dystric Histosols
Gelic Histosols
Eutric Podzoluvisols
Dystric Podzoluvisols
Gleyic Podzoluvisols
Orthic Podzols
Leptiv Podzols
Ferric Podzols
Humic Podzols
Placic Podzols
Gleyic Podzols
Orthic Ferralsols
Xanthic Ferralsols
Rhodic Ferralsols
Humic Ferralsols
Acric Ferralsols
Plinthic Ferralsols
Orthic Acrisols
Ferric Acrisols
Humic Acrisols
Plinthic Acrisols
Gleyic Acrisols
Eutric Nitosols
Dystric Nitosols
Humic Nitosols
NOTES:
1. first column is category number, second is soil abbreviation
2. categories 81 and 90 do not occur
GED IX) Documentation. Soil Type, Soil Texture, Surface Slope, and Other Properties A.ll-8
-------
DATA ELEMENT: Associated and Included Soils
STRUCTURE: Raster Data Files: 1-degree GED 180x360 grid (see User's Guide)
SERIES: none
SPATIAL DATA FILES:
SRZSUBS.DOC
file title
: Staub and
Rosenzweig Zobler Associated and Included
Subsidiary Soil Units
data type
integer
file type
binary
columns
360
rows
180
ref. system
lat/long
ref. units
deg
unit dist.
1.0000000
min. X
-180.0000000
max. X
180.0000000
min. y
-90.0000000
max. Y
90.0000000
pos'n error
unknown
resolution
1.0000000
min. value
0
max, value
278
value units
characteristic
classes
value error
unknown
flag value
none
flag def'n
none
legend cats
279
Legend:
category
0
0
category
1
1
Blank
category
2
2
AF
category
3
3
AFBD
category
4
4
AGFA
category
5
5
AGFO
category
6
6
AO
category
7
7
AOFO
category
8
8
B U
category
9
9
BC
category
10
10
BCBH
category
11
11
BCDD
category
12
12
BCIi
category
13
13
BCLC
category
14
14
BCTV
category
15
15
BCV
category
16
16
BD
category
17
17
BDBH
category
18
18
BDBXDD
category
19
19
BDDD
category
20
20
BDDDPH
category
21
21
BDLOTO
category
22
22
BDRD
category
23
23
BDTO
category
24
24
BDU
category
25
25
BE
GED 1.0 Documentation Soil Type, Soil Texture, Surface Slope, and Other Properties
All-9
-------
category
26
26
BEBH
category
27
27
BEC
category
28
28
BEE
category
29
29
BELC
category
30
30
BELO
category
31
31
BETO
category
32
32
BEU
category
33
33
BF
category
34
34
BH
category
35
35
BH U
category
36
36
BHTV
category
37
37
BHU
category
38
38
BK
category
39
39
BKR
category
40
40
BKRC
category
41
41
BKX
category
42
42
BV
category
43
43
BVLC
category
44
44
BXDD
category
45
45
BXDDOD
category
46
46
BXRC
category
47
47
CH
category
48
48
DD
category
49
49
DDLOTO
category
50
50
DDPH
category
51
51
DDPL
category
52
52
DDRD
category
53
53
E
category
54
54
E BC
category
55
55
FHNETO
category
56
56
PO
category
57
57
FOFX
category
58
58
FOLF
category
59
59
FOND
category
60
60
FP
category
61
61
GE
category
62
62
GX
category
63
63
GXRX
category
64
64
HH
category
65
65
HL
category
66
66
HLKL
category
67
67
JCXK
category
68
68
K E
category
69
69
K
category
70
70
K U
category
71
71
KH
category
72
72
KHJ
category
73
73
KHU
category
74
74
KL
category
75
75
L
category
76
76
L RE
category
77
77
L Q
category
78
78
LA
category
79
79
LABD
category
80
80
LC
category
81
81
LCE
category
82
82
LCRE
GED1.0 Documentation Soil Type, Soil Texture, Surface Slope, and Other Properties All-10
-------
category 83
category 84
category 85
category 86
category 87
category 88
category 89
category 90
category 91
category 92
category 93
category 94
category 95
category 96
category 97
category 98
category 99
category100
categorylOl
categoryl02
categoryl03
category104
category105
categoryl06
categoryl07
categoryl08
categoryl09
categoryllO
categorylll
categoryll2
category 113
categoryll4
categoryll5
category 116
categoryll7
categoryll8
categoryll9
category120
category 121
category122
category123
categoryl24
categoryl25
category126
categoryl27
category128
category129
categoryl30
categoryl31
categoryl32
categoryl33
category 134
categoryl35
category136
categoryl37
categoryl38
categoryl39
83
LCX
84
LF
85
LFNE
86
LFRD
87
LFRE
88
LG
89
LGRE
90
LK
91
LO
92
LOBC
93
MO
94
NE
95
OEPH
96
OEPHU
97
PHU
98
PO
99
POBD
100
POBX
101
POOD
102
POOX
103
Q
104
R B
105
R
106
RB
107
RCX YK
108
RCX
109
RCXK
110
RCYK
111
RCZO
112
RD
113
RDSO
114
RE
115
REBE
116
REQA
117
RERX
118
REXK
119
REYH
120
RX
121
RXBC
122
RXBX
123
RXOX
124
RXX YH
125
TO
126
TV
127
TVOD
128
U
129
V
130
VHU
131
VP
132
X
133
XH
134
XK
135
XKE
136
XKK E
137
XL
138
Y
139
YH
GED1.0 Documentation Soil Type, Soil Texture, Surface Slope, and Other Propertie*
All-11
-------
category140
categoryl41
categoryl42
categoryl43
categoryl44
categoryl45
categoryl46
categoryl47
categoryl48
category149
categorylBQ
categoryl51
categoryl52
categoryl53
categoryl54
categoryl55
category156
categoryl57
category158
categoryl59
categoryl60
categoryl61
categoryl62
categoryl63
categoryl64
categoryl65
categoryl66
categoryl67
categoryl68
categoryl69
categoryl70
categoryl71
categoryl72
categoryl73
categoryl74
categoryl75
category176
categoryl77
categoryl78
category 179
categoryl80
categoryl81
categoryl82
categoryl83
categoryl84
categoryl85
categoryl86
categoryl87
category 188
category189
categoryl90
categoryl91
category192
categoryl93
categoryl94
category195
categoryl96
140 YHRE
141 YHSO
142 YHYK
143 YK
144 YY
145 ZO
146 1
147 10
148 100
149 101
150 102
151 103
152 104
153 105
154 106
155 107
156 108
157 109
158 11
159 110
160 111
161 112
162 115
163 116
164 117
165 118
166 12
167 120
168 122
169 123
170 125
171 126
172 127
173 128
174 129
175 13
176 130
177 131
178 133
179 135
180 136
181 138
182 14
183 142
184 143
185 146
186 15
187 16
188 17
189 177
190 18
191 19
192 2
193 20
194 21
195 22
196 23
GED 1.0 Documentation Soil Type, Soil Texture, Surface Slope, and Other Properties
All-12
-------
categoryl97 : 197
categoryl98 : 198
categoryl99 : 199
category200 : 200
category201 : 201
category202 : 202
category203 : 203
category204 : 204
category205 : 205
category206 : 206
category207 : 207
category208 : 208
category209 : 209
category210 : 210
category211 : 211
category212 : 212
category213 : 213
category214 : 214
category215 : 215
category216 : 216
category217 : 217
category218 : 218
category219 : 219
category220 : 220
category221 : 221
category222 : 222
category223 : 223
category224 : 224
category225 : 225
category226 : 226
category227 : 227
category228 : 228
category229 : 229
category230 : 230
category231 : 231
category232 : 232
category233 ; 233
category234 : 234
category235 : 235
category236 : 236
category237 : 237
category238 : 238
category239 : 239
category240 : 240
category241 : 241
category242 : 242
category243 : 243
category244 : 244
category245 : 245
category246 : 246
category247 : 247
categoiy248 : 248
category249 : 249
category250 : 250
category251 : 251
category252 : 252
category253 : 253
24
25
26
27
28
29
3
30
31
32
33
34
35
36
37
38
39
4
40
41
42
43
44
45
46
47
48
49
5
50
51
52
53
54
55
56
57
58
59
6
60
61
62
63
64
65
66
67
68
69
7
70
71
72
73
74
75
GED 1.0 Documentation. Soil Type, Soil Texttm, Surface Slope, and Other Proptrtiee All-13
-------
category^ 54 : 254 76
category255 : 255 77
category256 : 256 78
category257 : 257 79
category258 : 258 8
category259 : 259 80
category260 : 260 81
category261 : 261 82
category262 : 262 83
category263 : 263 84
category264 : 264 85
category265 : 265 86
category266 : 266 87
category267 : 267 88
category268 : 268 89
category269 : 269 9
category270 : 270 90
category271 : 271 91
category272 : 272 92
category273 : 273 93
category274 : 274 94
category275 : 275 95
category276 : 276 96
category277 : 277 97
category278 : 278 98
NOTES:
1. no data are provided for water areas or Antarctica
2. first column is category number, remaining are codes
3. categories are unique permutations of codes
GEE) 1,0 Documentation Soil Tt/pt, Soil Texture, Surface Slope, and Other Properties Al 1-14
-------
DATA ELEMENT:
Near-Surface Soil Texture
STRUCTURE: Raster Data Files: 1-degree GED 180x360 grid (see User's Guide)
SERIES: none
SPATIAL DATA FILES:
file title
data type
file type
columns
rows
ref. system
ref. units
unit dist.
min. X
max. X
min. Y
max. Y
pos'n error
resolution
min. value
max. value
value units
value error
flag value
flag def'n
legend cats
SRZTEX.DOC
Staub and Rosenzweig Zobler Near-Surface Soil Texture
byte
binary
360
180
lat/long
deg
1.0000000
-180.0000000
180.0000000
-90.0000000
90.0000000
unknown
1.0000000
0
9
characteristic classes
unknown
none
none
10
Legend:
category
0
0
Water
category
1
1
COR
Coarse
category
2
2
MED
Medium
category
3
3
FIN
Fine
category
4
4
CM
Coarse-medium
category
5
5
CF
Coarse-fine
category
6
6
MF
Medium-fine
category
7
7
CMF
Coarse-medium-f ine
category
8
8
ORG
organic
category
9
9
LI
Land Ice
NOTES:
GED 1.0 Documentation Soil Typt,SottTtxt*rt,S*rftu* Slept, tmdOtiurPropcrHt* All-15
-------
DATA ELEMENT: Surface Slope
STRUCTURE: Raster Data Files: 1-degree GED 180x360 grid (see User's Guide)
SERIES: none
SPATIAL DATA FILES:
SRZSLOP.DOC
file title
Staufe and Rosenzweig Zobler Soil Unit Surface Slope
data type
byte
file type
binary
columns
360
rows
180
ref. system
lat/long
ref. units
deg
unit dist.
1.0000000
min. X
-180.0000000
max. X
180.0000000
min. Y
-90.0000000
max. Y
90.0000000
pos'n error
unknown
resolution
1.0000000
min. value
0
max. value
9
value units
classed
value error
unknown
flag value
none
flag def'n
none
legend cats
10
Legend:
category 0 :
0 Water
category 1 :
Class 1
0-8%
category 2 :
Class 2
8-30%
category 3 :
Class 3
> 30%
category 4 :
Class 4
0-30%
category 5 :
Class 5
0-8% > 30%
category 6 :
Class 6
8-30% > 30%
category 7 :
Class 7
0-8% 8-30% > 30%
category 8 :
8 Not Used
category 9 :
9 Land-Ice
NOTES:
GED 1.0 Documentation Soil Type, Soil Texture, Surface Slope, tmd Other Properties All-16
-------
DATA ELEMENT: Soil Phase
STRUCTURE: Raster Data Files: 1-degree GED 180x360 grid (see User's Guide)
SERIES: none
SPATIAL DATA FILES:
SRZPHAS.DOC
file title
Staub and Rosenzweig Zobler Soil Phase Codes
data type
byte
file type
binary
columns
360
rows
180
ref. system
lat/long
ref. units
deg
unit dist.
1.0000000
min. X
-180.0000000
max. X
180.0000000
min. Y
-90.0000000
max. Y
90.0000000
pos'n error
unknown
resolution
1.0000000
min. value
0
max. value
86
value units
permutations of phase codes
value error
unknown
flag value
none
flag def'n
none
legend cats
87
Legend:
category
0
0
category
1
1
Blank
category
2
2
St
G
stony;
glacier (i.e.; land-ice)
category
3
3
St
Pf
stony;
permafrost
category
4
4
St
So
stony;
sodic
category
5
5
St
IP
stony;
intermittent permafrost
category
6
6
St
Pf G
stony;
permafrost glacier (i.e.; land-ice)
category
7
7
St
Pf Po
stony;
permafrost ponded
category
8
8
St
Po
stony;
ponded
category
9
9
St
L
stony;
lithic
category
10
10
St
Pg
stony;
petrogypsic
category
11
11
St
RD
stony;
rock debris
category
12
12
St
?
stony;
27
category
13
13
St
IP G
stony;
intermittent permafrost glacier (i.e.;
land-ice)
category
14
•
•
14
St
DS
stony;
dunes; sand
category
15
•
•
15
St
D
stony;
duripan
category
16
•
•
16
St
D Po
stony;
duripan ponded
category
17
•
•
17
St
C
stony;
cerrado
category
18
i
18
St
L Pc
stony;
lithic petrocalcic
category
19
•
•
19
St
Sa
stony;
saline
category
20
i
20
St
Ph
stony;
phreactic
category
21
*
*
21
St
Pc
stony;
petrocalcic
category
22
•
4
22
St
stony
category
23
1
23
Ph
phreactic
category
24
1
24
Ph
Pf
phreactic; permafrost
GED 1.0 Documentation Soil Type, Soil Texture, Surface Slop*, *nd Other PropertUt Al 1-17
-------
category 25
category 26
category 27
category 28
category 29
category 30
category 31
category 32
25 Ph Po
26 C
27 So Po
28 So DS
29 So
30 L So
31 L Pf
32 L Pf RD G
ponded
category 33
: 33
L Pf
category 34
: 34
L Pf RD
category 35
: 35
L Sa
category 36
: 36
L Pf Po
category 37
: 37
L P
category 38
: 38
L Po
category 39
: 39
L IP
category 40
: 40
L
category 41
: 41
L RD
category 42
: 42
Pf Po
category 43
: 43
Pf
category 44
: 44
Pf G
category 45
: 45
IP Po
category 46
: 46
IP
category 47
: 47
IP G
category 48
: 48
G
category 49
: 49
G St Pf
category 50
: 50
G Pf
category 51
: 51
G RD L Pf
category 52
: 52
G L Pf
category 53
: 53
G L RD Pf
category 54
: 54
G RD Pf
category 55
: 55
Po DS
category 56
: 56
PO
category 57
: 57
Po RD
category 58
: 58
DS
category 59
: 59
DS L
category 60
: 60
RD St
category 61
: 61
RD Pc St
category 62
: 62
RD G
category 63
: 63
RD St DS
category 64
: 64
RD
category 65
j 65
RD DS
category 66
: 66
RD St ?
category 67
s 67
RD DS St
category 68
: 68
?
category 69
: 69
P PO
category 70
: 70
P C
category 71
: 71
P
category 72
: 72
Pf Po
category 73
: 73
Pf
category 74
: 74
Pc Po
category 75
: 75
PC
category 76
: 76
Pg
sand
rock debris
ponded
phreactic;
cerrado
sodic; ponded
sodic; dunes,
sodic
lithic; sodic
lithic; petroferric
lithic; permafrost; rock debris; glacier
(i.e., land-ice)
lithic
lithic
lithic
lithic
lithic
lithic
lithic
lithic
lithic; rock debris
permafrost; ponded
permafrost
permafrost; glacier (i.e., land-ice)
intermittent permafrost; ponded
intermittent permafrost
intermittent permafrost; glacier (i.e.,
land-ice)
land-ice)
land-ice)
land-ice)
land-ice)
permafrost
permafrost;
saline
permafrost;
petric
ponded
intermittent permafrost
glacier (i.e.,
glacier (i.e.,
glacier (i.e.,
glacier (i.e.,
lithic; permafrost
glacier (i.e., land-ice)
glacier (i.e., land-ice)
debris; permafrost
glacier (i.e., land-ice)
permafrost
ponded; dunes, sand
ponded
ponded; rock debris
dunes, sand
dunes, sand;
rock debris;
rock debris;
rock debris;
rock debris;
rock debris
rock debris;
rock debris;
rock debris;
27
petric; ponded
petric; cerrado
petric
petroferric; ponded
petroferric
petrocalcic; ponded
petrocalcic
petrogypsic
stony; permafrost
permafrost
rock debris;
lithic; permafrost
lithic; rock
rock debris;
lithic
stony
petrocalcic; stony
glacier (i.e., land-ice)
stony; dunes, sand
dunes,
stony;
dunes,
sand
27
sand;
stony
GED 1.0 Documentation Soil Type, Soil Texture, Surface Slept, and Other Propertiee
All-18
-------
category
77
:
77
pg
Po
petrogypsic; ponded
category
78
:
78
P
fragipan
category
79
:
79
D
duripan
category
80
:
80
D Po
dur ipan-f—ponded
category
81
•
81
Sa
?
saline; 27
category
82
•
•
82
Sa
DS
saline; dunes, sand
category
83
:
83
Sa
saline
category
84
;
84
Sa
Po
saline; ponded
category
85
•
85
Sa
So
saline; sodic
category
86
•
86
Sa
RD
saline; rock debris
NOTES:
1. no data are provided for water areas or Antarctica
2. category 1 indicates records filled with spaces in the source file
3. categories are unique permutations of phase codes (e.g., 63, 67)
4. Code 27 is undocumented
GED 1.0 Documentation Soil Typ*, Soil Texturt, Surfact Slop*, $md Otktr PrvptrtUa
All-19
-------
DATA ELEMENT: Special Codes
STRUCTURE: Raster Data Files: 1-degree GED 180x360 grid (see User's Guide)
SERIES: none
SPATIAL DATA FILES:
SRZCODE.DOC
file title
Staub and Rosenzweig Zobler Special Codes
data type
byte
file type
binary
columns
360
rows
180
ref. system
lat/long
ref. units
deg
unit dist.
1.0000000
min. X
-180.0000000
max. X
180.0000000
min. Y
-90.0000000
max. Y
90.0000000
pos'n error
unknown
resolution
1.0000000
min. value
0
max. value
11
value units
characteristic classes
value error
unknown
flag value
none
flag def'n
none
legend cats
12
Legend:
category 0
0
category 1
1 Blank
category 2
2 33
category 3
3 44
category 4
4 55 88
category 5
5 55
category 6
6 66
category 7
7 77 88
category 8
8 77
category 9
9 88
category 10
10 88 77
category 11
11 99
Land cell not present on FAO map; classified as
soil; SU, TEX, and SLP fields filled in
Land cell not present on FAO map; classified as
land-ice
Cell classified as soil by Zobler, and as land-ice
by Matthews
Cell classified as land-ice by Zobler, and as
vegetation (soil implied) by Matthews
Slope information missing; SLP field filled in
Texture information missing; TEX field filled in
No soil information present on the map; SU; TEX,
and SLP fields filled in
NOTES:
1. no data are provided for water areas or Antarctica
2. category 1 indicates records filled with spaces in the source file
3. categories are unique permutations of codes
4. first column is category number, remaining columns are codes
> '
GED 1.0 Documentation Soil Type, Soil Texture, Surface Slope, and Other Properties All-20
-------
DATA INTEGRATION AND QUALITY
Mark A. Ohrenschall
NOAA National Geophysical Data Center
Boulder, CO
The Zobler data was in a lat/long projection on a one-degree grid that was compatible
with the GED conventions. The source data consisted of four ASCII files, which were
read and converted to raster data files in the GED format. The first three of these files
(SOIL.USER, TEX.USER, AND SLP.USER) presented no problems in representing the
numerical values exactly. The fourth file (SOILWRLD), however, contained character
string data rather than numerical codes. In the GED (IDRISI 4.0) data structure, these
must be represented as numerical values linked to the character information as a legend
or values file. The following method was employed to translate this file:
A program was written to read SOILWRLD and tabulate each unique occurrence of a
character string for each parameter field, creating a look-up table. Numerical codes were
assigned to each unique string in the look-up tables, which were then used to re-class the
SOILWRLD file.
Other than assigning codes to the SOILWRLD data, no other changes were made in the
original data values. All final data files were inspected for agreement with the original
data.
GED 1.0 Documentation Soil Type, Soil Texture, Surface Slept, and Other Propertie*
All ~21
-------
A12
Webb, Rosensweig, and Levine Global Soil Particle Size
Properties
GED 1.0 Documentation Global Soil Particle Size Properties A12
-------
DATA-SET DESCRIPTION
data-set NAME: Global Soil Particle Size Properties
PRINCIPAL INVESTIGATOR(s): Robert S. Webb, Cynthia E.
Rosenzweig, and Elissa R. Levine
SOURCE
SOURCE DATA CITATION: Webb, R.S., C.E. Rosenzweig, and E.R. Levine. 1991. A
Global Data Set of Soil Particle Size Properties. Digital Raster Data on a 1-degree
Geographic (lat/long) 180x360 grid. New York: NASA Goddard Institute of Space
Studies. 0.51 MB.
CONTRIBUTOR(s): Dr. Robert S. Webb
NOAA Paleoclimatology Program
National Geophysical Data Center
325 Broadway
Boulder, CO 80303 USA
DISTRIBUTOR(s): NASA/GISS
VINTAGE: circa 1980's
LINEAGE:
(1) Principal Investigators: R.S. Webb, C.E. Rosenzweig, and E.R. Levine
NASA Goddard Institute for Space Studies
(2) R.S. Webb
NOAA National Geophysical Data Center
ORIGINAL DESIGN
VARIABLES:
Zobler Soil Classes
Continental Classes
Combined Zobler and Continental Classes (spatial layer for horizon data)
Potential Storage of Water in Soil Profile
Potential Storage of Water in Root Zone
Soil Water Model II
Soil Profile Thickness
Texture-based Potential Storage of Water
Depth of 15 horizons (meters)
Amount of sand, silt, and clay in 15 horizons
ORIGIN: FAO/UNESCO Soil Map of the World (1974) - see Chapter A16X
GEOGRAPHIC REFERENCE: lat/long
GED 1.0 Documentation Global Soil Particle Size Properties
A12-2
-------
GEOGRAPHIC COVERAGE:
Maximum Latitude
Minimum Latitude
Maximum Longitude
Minimum Longitude
Global
+90 degrees (N)
-90 degrees (S)
+180 degrees (E)
-180 degrees (W)
GEOGRAPHIC SAMPLING: Characteristic Classes and Values for 1-degree grid cells
TIME PERIOD: Modern, circa 1971-1981
TEMPORAL SAMPLING: Modern composite
INTEGRATED DATA-SET
DATA-SET CITATION: Webb, Robert S., Cynthia E. Rosenzweig, and Elissa R. Levine.
1992. A Global Data Set of Soil Particle Size Properties. Digital Raster Data on a 1-
degree Geographic (lat/long) 180x360 grid. In: Global Ecosystems Database Version
1.0: Disc A. Boulder, CO: NOAA National Geophysical Data Center. 2
independent and one derived spatial layer with 65 attributes, on CD-ROM, 16.5
MB. [first published in 1991]
ANALYST(s): Robert S. Webb
PROJECTION: Geographic (lat/long), GED window (see User's Guide).
SPATIAL REPRESENTATION: Characteristic classes and values within 1-degree grid
cdls.
TEMPORAL REPRESENTATION: Modern composite
DATA REPRESENTATION:
Zobler Soil Classes 1-byte integer class codes
Continental Classes 1-byte integer class codes
Combined Zobler and Continental Classes 2-byte integer class codes
(spatial layer for horizon data)
Potential Storage of Water in Soil Profile 2-byte integers (mm)
Potential Storage of Water in Root Zone 2-byte integers (mm)
Soil Water Model II 2-byte integers (mm)
Soil Profile Thickness 2-byte integers (cm)
Texture-based Potential Storage of Water 2-byte integers (mm)
Depth of 15 horizons (meters) 4-byte real (meters +/- .001)
Amount of sand, silt, and day in 15 4-byte real (% +/- .001)
horizons
LAYERS AND ATTRIBUTES: 2 independent and 1 derived spatial layers with 65
attribute layers (stored as raster data files).
COMPRESSED DATA VOLUME: 602,458 bytes
PRIMARY REFERENCES (* reprint on CD-ROM)
* Webb, Robert S., Cynthia E. Rosenzweig, and Elissa R. Levine, 1991. A Global
Data Set of Soil Particle Size Properties. NASA Technical Memorandum 4286.
GED 1.0 Documentation Global Soil Particle Size Properties
A12-3
-------
ADDITIONAL REFERENCES
Abramopoulos, F., Rosenzweig, C., and Choudhury, B., 1988. Improved Ground
Hydrology Calculations for Global Climate Models (GCMS): Soil Water
Movement and Evaporation. Journal of Climate, 1,921-941.
Bouwman, A.F., Fung, I.Y., Matthews, E.E., and John, J.G., 1991. Global model of Nitrous
Oxides production from natural soils. Global Biogeochemical Cycles,submitted.
Buol, S.W., Hole, F.DV McCracken, R.J., 1973. Soil Genesis and Classification. The Iowa
State University Press, Ames, Iowa.
Delworth, T.L., and Manage, S., 1988. The influence of potential evaporation of the
variabilities of simulated soil wetness and climate. Journal of Climate, 1, 523-547.
FAO-UNESCO, 1971-1981. Soil Map of the World, 1:5,000,000, Volumnes H-X. UNESCO,
Paris.
Hansen, J., Russell, G., Rind, D., Stone, P., Laos, A., Lebedeff, S., Reudy, R., and Travis,
L., 1983. Efficient three-dimensional global models for climate studies. Monthly
Weather Review, 111, 609-662.
Henderson-Sellers, A., Wilson, M.F., Thomas, R., and Dickinson, R.E., 1986. Current
Global Land-Surface Data Sets for Use in Climate-Related Studies.
NCARTechnical Note NCAR/TN-272+STR.
Kellog, W.W., and Zhao, Z.C., 1988. Sensitivity of soil moisture to doubling of carbon
dioxide in climate modeling experiments, I, North America. Journal of Climate, 1,
348-366.
Matthews, E., 1984. Prescription of Land-Surface Boundary Conditions in GISS GCM II:
A simple method based on high-resolution vegetation data bases. NASA
Technical Memorandum #86096.
Matthews, E., 1983. Global Vegetation and land use: New high-resolution data bases for
climate studies. Journal of Climate and Applied Meteorology, 22,474-487.
Petersen, G.W., Cunningham, R.L. Matelski, R.P., 1968. Available moisture within
selected Pennsylvania soil series. Pennsylvania State University Agronomy Series
#3, 21pp.
Rind, D., 1988. The Doubled C02 Climate and the Sensitivity of the Modeled Hydrologic
Cycle. Journal of Geophysical Research, 93 (D5), 5386-5412.
Rind, D., Goldberg, R., Hansen, J., Rosenzweig, C., and Ruedy, R., 1990. Potential
evapotranspiration and the likelihood of future drought. Journal of Geophysical
Research, 95 (D7), 9983-10004.
Soil Science Society of America, 1987. Glossary of Soil Science Terms. Soil Science
Society of America. Madison, WI.
Webb, R.S., 1990. Late Quaternary Water-Level Fluctuations in the Northeaastern Unites
States. Brown University Ph.D. thesis, Providence, RI.
Zobler, L., 1986. A World Soil FUe for Global Climate Modeling. NASA Technical
Memorandum #87802.
GED1.0 Documentation Global Soil Particle Site Propertiea
A12-4
-------
DATA-SET FILES
LOCATION
NAME
NUMBER
TOONa SQSB
Spatial Datai
\GLGEO\RASTER\
WRCONT,IMG
1 file
64,800
WRMODII.IMG
1 file
129,600
WRPROF.IMG
1 file
129,600
WRROOT.IMG
1 file
129,600
WRSOIL.IMG
1 file
129,600
WRTEXT.IMG
1 file
129,600
WRZSOIL.IMG
1 file
64,800
WRCLA01.IMG
to
WRCLA15.IMG
15 files
259,200
WRDEP01.IMG
to
WRDEP15.IMG
15 files
259,200
WRSANO1.IMG
to
WRSAN15.IMG
15 files
259,200
WRSIL01.IMG
to
WRSIL15.IMG
15 files
259,200
Headers t
\GLGEO\META\
WRCONT.DOC
1 file
1,026
WRMODII.DOC
1 file
497
WRPROF.DOC
1 file
521
WRROOT.DOC
1 file
518
WRSOIL.DOC
1 file
500
WRTEXT.DOC
1 file
519
WRZSOIL.DOC
1 file
5,703
WRCLA01.DOC
to
WRCLA15.DOC
1$ files
8,226
WRDEP01.DOC
to
WRDEP15.DOC
15 files
8,226
WRSANO1.DOC
to
WRSAN15.DOC
15 files
8,226
WRSIL01.DOC
to
WRSIL15.DOC
15 files
8,226
Palettest
none
Tim* Series*
none
Volume on Disk:
134 files
16,371,788
REPRINT FILES
LOCATION
MAMa
NOMBBR
nan. scsb
\DOCUMENT\A12\
WR_01.PCX to LC1_37.PCX
37 files
1,270,334
WR_##X.PCX
5 files
470,703
Volume on Dick:
42 files
1,741,037
SOURCE EXAMPLE FILES
none
GED 1.0 Documentation Global Soil Particle Size ProptrHet
A12-5
-------
FILE DESCRIPTION
DATA ELEMENT: Continent Codes
STRUCTURE: Raster Data Files: 1-degree GED 180x360 grid (see User's Guide)
SERIES: none
SPATIAL DATA FILES:
WRCONT.DOC
file title
: Webb et
al. Continent Codes from the FAO/UNESCO Soil Map
of the
World
data type
: byte
file type
: binary
columns
: 360
rows
: 180
ref. system
: lat/long
ref. units
: deg
unit dist.
: 1.0000000
min. X
: -180.0000000
max. X
: 180.0000000
min. Y
: -90.0000000
max. Y
: 90.0000000
pos'n error
: unknown
resolution
: 1.0000000
min. value
: 0
max. value
: 10
value units
: classes
value error
: unknown
flag value
: none
flag def'n
: none
legend cats
: 11
Legend:
category 0 :
0 OCEAN
category 1 :
1 not used
category 2 :
2 N (NAM)
NAMERICA
category 3 :
3 C (MCA)
MEXICEAM
category 4 :
4 S (SAM)
SAMER1CA
category 5 :
5 E (EUR)
EUROPE
category 6 :
6 A (AFR)
AFRICA
category 7 :
7 I (SCA)
SCASIA
category 8 :
8 U (NCA)
NCASIA
category 9 :
9 E (SEA)
SEASIA
category 10 :
10 T (AUS)
AUSTRALI
NOTES:
1. Continent codes correspond to volume numbers of the FAO/UNESCO
2. SoU Map of the World (1971-81).
GED IX) Documentation Global Soil Particle Size ProptrtUt
A12-6
-------
DATA ELEMENT: Zobler Soil Type
STRUCTURE: Raster Data Files: 1-degree GED 180x360 grid (see User's Guide)
SERIES: none
SPATIAL DATA FILES:
WRZSOIL.DOC
file title
: Webb et al Soil Particle Size Properties Zobler Soil Types
data type
: byte
file type
j binary
columns
: 360
rows
: 180
ref. system
: lat/long
ref. units
: deg
unit dist.
: 1.0000000
min. X
: -180.0000000
max. X
: 180.0000000
min. Y
: -90.0000000
max. Y
: 90.0000000
pos'n error
: unknown
resolution
: 1.0000000
min. value
: 0
max. value
: 107
value units
: classes
value error
; unknown
flag value
: none
flag def'n
: none
legend cats
: 108
Legend:
category
0
0
WATER
WATER/OCEAN/LAKE
category
1
1
AP
FERRIC ACRISOL
category
2 : 2
AG
GLEYIC ACRISOL
category
3
3
AH
HUMIC ACRISOL
category
4
4
AO
ORTHIC ACRISOL
category
5
5
AP
PLINTHIC ACRISOL
category
6
6
BC
CHROMIC CAMBISOL
category
7
7
6D
DYSTRIC CAMBISOL
category
8
8
BE
EUTRIC CAMBISOL
category
9
9
BF
FERRALIC CAMBISOL
category
10
10
BG
GLEYIC CAMBISOL
category
11
11
BH
HUMIC CAMBISOL
category
12
12
BX
CALCIC CAMBISOL
category
13
13
BV
VERTIC CAMBISOL
category
14
14
BX
GELIC CAMBISOL
category
15
15
CG
GLOSSIC CHERNOZEM
category
16 : 16
CH
HAPLIC CHERNOZEM
category
17
17
CK
CALCIC CHERNOZEM
category
18
18
CL
LUVIC CHERNOZEM
category
19
19
DD
DYSTRIC PODZOLUVISOL
category
20
20
DE
EUTRIC PODZOLUVI SOL
category
21
21
DG
GLEYIC PODZOLUVISOL
category
22
22
E
RENDZINA
category
23
23
FA
ACRIC FERRALSOL
category
24
24
FH
HUMIC FERRALSOL
category
25
25
FO
ORTHIC FERRALSOL
GED 1.0 Documentation Glob*! Soil Particle Sizt Proptrtit*
A12-7
-------
category
26 ;
26
FP
PLINTHIC FERRALSOL
category
27 :
27
FR
RHODIC FERRALSOL
category
28 :
28
FX
XANTHIC FERRALSOL
category
29 :
29
GC
CALCARIC GLEYSOL
category
30 :
30
GD
DYSTRIC GLEYSOL
category
31 :
31
GE
EUTRIC GLEYSOL
category
32 :
32
GH
HUMIC GLEYSOL
category
33 :
33
GM
MOLLIC GLEYSOL
category
34 :
34
GP
PLINTHIC GLEYSOL
category
35 :
35
GX
GELIC GLEYSOL
category
36 :
36
HC
CALCARIC PHAEOZEM
category
37 :
37
HG
GLEYIC PHAEOZEM
category
38 :
38
HH
HAPLIC PHAEOZEM
category
39 :
39
HL
LUVIC PHAEOZEM
category
40 ;
40
I
LITHOSOL
category
41 :
41
JC
CALCARIC FLUVISOL
category
42 :
42
JD
DYSTRIC FLUVISOL
category
43 :
43
JE
EUTRIC FLUVISOL
category
44 :
44
JT
THIONIC FLUVISOL
category
45 :
45
KH
HAPLIC KASTANOZEM
category
46 :
46
KK
CALCIC KASTANOZEM
category
47 :
47
KL
LUVIC KASTANOZEM
category
48 :
48
LA
ALBIC LUVISOL
category
49 :
49
LC
CHROMIC LUVISOL
category
50 :
50
LF
FERRIC LUVISOL
category
51 :
51
LG
GLEYIC LUVISOL
category
52 :
52
LK
CALCIC LUVISOL
category
53 :
53
LO
ORTHIC LUVISOL
category
54 :
54
LP
PLINTHIC LUVISOL
category
55 :
55
LV
VERTIC LUVISOL
category 56 :
56
MG
GLEYIC GREYZEM
category
57 :
57
MO
ORTHIC GREYZEM
category
58 :
58
ND
DYSTRIC NITOSOL
category
59 s
59
NE
EUTRIC NITOSOL
category
60 :
60
NH
HUMIC NITOSOL
category
61 :
61
OD
DYSTRIC HISTOSOL
category
62 :
62
OB
EUTRIC HISTOSOL
category
63 :
63
OX
GELIC HISTOSOL
category
64 :
64
PF
FERRIC PODZOL
category
65 :
65
PG
GLEYIC PODZOL
category
66 :
66
PH
HUMIC PODZOL
category
67 :
67
PL
LEPTIC PODZOL
category
68 :
68
PO
ORTHIC PODZOL
category
69 :
69
PP
PLACIC PODZOL
category
70 :
70
QA
ALBIC ARENOSOL
category
71 :
71
QC
CAMBIC ARENOSOL
category
72 :
72
QF
FERRALIC ARENOSOL
category
73 :
73
QL
LUVIC ARENOSOL
category
74 :
74
RC
CALCARIC REGOSOL
category
75 s
75
RD
DYSTRIC REGOSOL
category
76 :
76
RE
EUTRIC REGOSOL
category
77 :
77
RX
GELIC REGOSOL
category
78 :
78
SG
GLEYIC SOLONETZ
category
79 :
79
SM
MOLLIC SOLONETZ
category 80 :
80
SO
ORTHIC SOLONETZ
category
81 :
81
TH
HUMIC ANDOSOL
category
82 :
82
TM
MOLLIC ANDOSOL
GED1.0 Documentation Global Soil Particle Size Properties
A12-8
-------
category
83
83
TO
OCHRIC ANDOSOL
category
84
84
TV
VITRIC ANDOSOL
category
85
85
U
RANKER
category
86
86
VC
CHROMIC VERTISOL
category
87
87
VP
PELLIC VERTISOL
category
88
88
WD
DYSTRIC PLANOSOL
category
89
89
WE
EUTRIC PLANOSOL
category
90
90
WH
HUMIC PLANOSOL
category
91
91
WM
MOLLIC PLANOSOL
category
92
92
WS
SOLODIC PLANOSOL
category
93
93
WX
GELIC PLANOSOL
category
94
94
XH
HAPLIC XEROSOL
category
95
95
XK
CALCIC XEROSOL
category
96
96
XL
LUVIC XEROSOL
category
97
97
XY
GYPSIC XEROSOL
category
98
98
YH
HAPLIC YERMOSOL
category
99
99
YK
CALCIC YERMOSOL
category100
100
YL
LUVIC YERMOSOL
categorylOl
101
YT
TAKYRIC YERMOSOL
category102
102
YY
GYPSIC YERMOSOL
categoryl03
103
ZG
GLEYIC SOLONCHAK
categoryl04
104
ZM
MOLLIC SOLONCHAK
category 105
105
ZO
ORTHIC SOLONCHAK
categoryl06
106
ZT
TAKYRIC SOLONCHAK
categoryl07
107
ICE
GLACIER/ICE
NOTES:
GED1.0 Documentation Global Soil Particle Sixt ProperUet
A12-9
-------
DATA ELEMENT: Potential Storage of Water in Soil Profile
STRUCTURE: Raster Data Files: 1-degree GED 180x360 grid (see User's Guide)
SERIES: none
SPATIAL DATA FILES:
WRPROF.DOC
file title
Webb et al Potential Storage of Water in Soil Profile (mm)
data type
:
integer
file type
:
binary
columns
•
360
rows
180
ref. system
:
lat/long
ref. units
deg
unit dist.
1.0000000
min. X
-180.0000000
max. X
180.0000000
min. Y
*
-90.0000000
max. Y
90.0000000
pos'n error
;
unknown
resolution
1.0000000
min. value
0
max. value
:
4432
value units
:
millimeters
value error
;
unknown
flag value
;
1
flag def'n
•
ice
legend cats
•
•
0
NOTES:
GED 1.0 Documentation Global Soil Particle Size Propertitt
A12-10
-------
DATA ELEMENT: Potential Storage of Water in Root Zone
STRUCTURE: Raster Data Files: 1-degree GED 180x360 grid (see User's Guide)
SERIES: none
SPATIAL DATA FILES:
WRROOT.DOC
file title
Webb et al Potential Storage of Water in Root Zone (nun)
data type
integer
file type
binary
columns
360
rows
180
ref. system
lat/long
ref. -units
deg
unit dist.
1.0000000
min. X
-180.0000000
max. X
180.0000000
min. Y
-90.0000000
max. Y
90.0000000
pos'n error
unknown
resolution
1.0000000
min. value
0
max. value
1700
value units
millimeters
value error
unknown
flag value
1
flag def'n
ice
legend cats
: 0
NOTES:
GED 1.0 Documentation Global Soil Pertieli Size Properties
A12-11
-------
DATA ELEMENT: Soil Water Model II
STRUCTURE: Raster Data Files: 1-degree GED 180x360 grid (see User's Guide)
SERIES: none
SPATIAL DATA FILES:
WRMODD.DOC
file title
Webb et al Model II Soil Water (mm)
data type
integer
file type
binary
columns
360
rows
180
ref. system
lat/long
ref. units
deg
unit dist.
1.0000000
min. X
-180.0000000
max. X
180.0000000
min. Y
-90.0000000
max. Y
90.0000000
pos'n error
unknown
resolution
1.0000000
min. value
0
max. value
650
value units
millimeters
value error
unknown
flag value
1
flag def'n
ice
legend cats
0
NOTES:
GED 1.0 Documentation Global Soil Particle Site Properties
A12-12
-------
DATA ELEMENT: Soil Profile Thickness
STRUCTURE: Raster Data Files: 1-degree GED 180x360 grid (see User's Guide)
SERIES: none
SPATIAL DATA FILES:
WRSOIL.DOC
file title
Webb et al Soil Profile Thickness (cm)
data type
integer
file type
binary
columns
360
rows
180
ref. system
1at/long
ref. units
deg
unit dist.
1.0000000
min. X
-180.0000000
max. X
180.0000000
min. Y
-90.0000000
max. Y
90.0000000
pos'n error
unknown
resolution
1.0000000
min. value
0
max. value
800
value units
centimeters
value error
unknown
flag value
1
flag def'n
ice
legend cats
0
NOTES:
GED1.0 Documentation Global Soil Particle Size Proptrti**
A12-13
-------
DATA ELEMENT: Texture-based Potential Storage of Water
STRUCTURE: Raster Data Files: 1-degree GED 180x360 grid (see User's Guide)
SERIES: none
SPATIAL DATA FILES:
WRTEXT.DOC
file title
Webb et al Texture-Based Potential Storage of Water (mm)
data type
integer
file type
binary
columns
360
rows
180
ref. system
lat/long
ref. units
deg
unit dist.
1.0000000
min. X
-180.0000000
max. X
180.0000000
min. Y
-90.0000000
max. Y
90.0000000
pos'n error
unknown
resolution
1.0000000
min. value
0
max. value
2160
value units
millimeters
value error
unknown
flag value
1
flag def'n
ice
legend cats
0
NOTES:
GED 1.0 Documentation Global Soil Particle Size Properties
A12-14
-------
DATA ELEMENT: Depth of Horizon
STRUCTURE: Raster Data Files: 1-degree GED 180x360 grid (see User's Guide)
SERIES: none
SPATIAL DATA FILES:
WRDEP01.DOC
file title
Webb et al Soil Particle Size Properties: depth for
horizon 1
data type
real
file type
binary
columns
360
rows
180
ref. system
lat/long
ref. units
deg
unit dist.
1.0000000
min. X
-180.0000000
max. X
180.0000000
min. Y
-90.0000000
max. Y
90.0000000
pos'n error
unknown
resolution
1.0000000
min. value
0.0000000
max. value
0.1400000
value units
meters
value error
unknown
flag value
-1.0000000
flag def'n
end of record for soil type
legend cats
0
File Series Parameters:
File
Horizon
Minimum
Maximum
WRDEP01
1
0.0000000
0.1400000
WRDEPQ2
2
0.0000000
3.5999999
WRDEP03
3
0.0000000
1.0500000
WRDEP04
4
0.0000000
3.5999999
WRDEP05
5
0.0000000
3.5999999
WRDEP06
6
0.0000000
5.0000000
WRDEP07
7
0.0000000
8.0000000
WRDEP08
8
0.0000000
7.0000000
WRDEP09
9
0.0000000
3.5999999
WRDEP10
10
0.0000000
3.0230000
WRDEP11
11
0.0000000
3.0480001
WRDEP12
12
0.0000000
3.5309999
WRDEP13
13
0.0000000
2.7000000
WRDEP14
14
0.0000000
2.2300000
WRDEP15
15
0.0000000
2.4600000
NOTES:
GED 1.0 Documentation Global Soil Purticle Size Properties
A12-15
-------
DATA ELEMENT: Amount of Clay in Horizon
STRUCTURE: Raster Data Files: 1-degree GED 180x360 grid (see User's Guide)
SERIES: none
SPATIAL DATA FILES:
WRCLA01.DOC
file title :
Webb et al Soil Particle Size Properties: clay in horizon 1
data type :
real
file type :
binary
columns :
360
rows :
180
ref. system :
lat/long
ref. units :
deg
unit dist. :
1.0000000
min. X :
-180.0000000
max. X :
180.0000000
min. Y
-90.0000000
max. Y :
90.0000000
pos'n error :
unknown
resolution :
1.0000000
min. value :
0.0000000
max. value :
0.7700000
value units :
proportional
value
value error :
unknown
flag value :
-1.0000000
flag def'n :
missing soil
type
legend cats :
0
File Series Parameters:
Pile
Horizon
Minimum
Maximum
WRCLA01
1
0.0000000
0.7700000
WRCLA02
2
0.0000000
0.8400000
WRCLA03
3
0.0000000
0.9180000
WRCLA04
4
0.0000000
0.9300000
WRCLA05
5
0.0000000
0.9140000
WRCLA0 6
6
0.0000000
0.9180000
WRCLA07
7
0.0000000
0.7500000
WRCLA08
8
0.0000000
Oi6400000
WRCLA09
9
0.0000000
0.6800000
WRCLA10
10
0.0000000
0.7500000
WRCLA^l
11
0.0000000
0.7600000
WRCLA12
12
0.0000000
0.7800000
WRCLA13
13
0.0000000
0.3780000
WRCLA14
14
0.0000000
0.3620000
WRCLA15
15
0.0000000
0.0000000
NOTES:
GED 1.0 Documentation Global Soil Particle Size Propertiet
A12-16
-------
DATA ELEMENT; Amount of Sand In Horizon
STRUCTURE: Raster Data Piles: 1-degree GED 180x360 grid (see User's Guide)
SERIES: none
SPATIAL DATA FILES:
WRSAN01.DOC
file title
: Webb et al Soil Particle Size Properties: sand in horizon 1
data type
: real
file type
: binary
columns
: 360
rows
: 180
ref. system
: lat/long
ref. units
: deg
unit dist.
: 1.0000000
min. X
: -180.0000000
max. X
: 180.0000000
min. Y
: -90.0000000
max. Y
: 90.0000000
pos'n error
: unknown
resolution
: 1.0000000
min. value
: 0.0000000
max. value
: 0.9800000
value units
: proportional
value
value error
: unknown
flag value
: -1.0000000
flag def'n
: missing soil
type
legend cats
: 0
File Series Parameters:
Horizon
Minimum
Maximum
WRSAN01
1
0.0000000
0.9800000
WRSAN02
2
0.0000000
0.9900000
WRSAN03
3
0.0000000
0.9840000
WRSAN04
4
0.0000000
0.9900000
WRSAN05
5
0.0000000
0.9880000
WRSAN06
6
0.0000000
0.9900000
WRSAN07
7
0.0000000
0.9920000
WRSAN08
8
0.0000000
0.9920000
WRSAN09
9
0.0000000
0.9910000
WRSAN10
10
0.0000000
0.9960000
WRSAN11
11
0.0000000
0.4600000
WRSAN12
12
0.0000000
0.5400000
WRSAN13
13
0.0000000
0.3360000
WRSAN14
14
0.0000000
0.3400000
WRSAN15
15
0.0000000
0.0000000
NOTES:
GED 1j0 Documentation Global Soil Purticb Six* Proptrtim
A12-17
-------
DATA ELEMENT: Amount of Silt in Horizon
STRUCTURE: Raster Data Files: 1-degree GED 180x360 grid (see User's Guide)
SERIES: none
SPATIAL DATA FILES:
WRSILOLDOC
file title
: Webb et al Soil Particle Size Properties: silt in horizon 1
data type
: real
file type
; binary
columns
; 360
rows
: 180
ref. system
: lat/long
ref. units
; deg
unit dist.
: 1.0000000
min. X
: -180.0000000
max. X
; 180.0000000
min. Y
: -90.0000000
max. Y
: 90.0000000
pos'n error
i unknown
resolution
: 1.0000000
min. value
: 0.0000000
max. value
: 0.8670000
value units
: proportional
value
value error
: unknown
flag value
: -1.0000000
flag def'n
: missing soil
type
legend cats
: 0
File Series Parameters:
File
Horizon
Minimum
Maximum
WRSIL01
1
0.0000000
0.8670000
WRSIL02
2
0.0000000
0.8770000
WRSIL03
3
0.0000000
0.8830000
WRSIL04
4
0.0000000
0.8300000
WRSIL05
5
0.0000000
0.8580000
WRSIL06
6
0.0000000
0.7840000
WRSIL07
7
0.0000000
0.8970000
WRSIL08
8
0.0000000
0.7900000
WRSIL09
9
0.0000000
0.7980000
WRS1L10
10
0.0000000
0.8690000
WRSILll
11
0.0000000
0.6990000
VJRSIL12
12
0.0000000
0.7210000
WRSIL13
13
0.0000000
0.7240000
WRS1L14
14
0.0000000
0.7140000
WRSIL15
15
0.0000000
0.0000000
NOTES:
GED 1.0 Documentation Global Soil Particle Size Propertiet
A12-18
-------
DATA INTEGRATION AND QUALITY
Mark Ohrenschall, NOAA/NESDIS
National Geophysical Data Center
Boulder, CO
The following is an excerpt from documentation provided by Robert S. Webb. This selection
refers to a data file containing depth and soil particle size information. Note that references
to 106 entries in the data array (corresponding to Zobler soil types) is a typographical error,
and the correct figure is 107.
The data has been organized as four 106x10x15 [sic] dimensioned real*4
arrays: depth, sand, silt, and clay. The first dimension (106) [sic] corresponds
to the sequence number of the soil types in Zobler's (1986) World Soil Data
File. The second dimension (10) corresponds to the volume numbers of the
nine major continental divisions in FAO/UNESCO Soil Map of the World,
Vols. 2-10 (1971-81). The third dimension (IS) corresponds to the individual
horizons with data for each soil type from the Morphological, Chemical and
Physical Properties Appendix in each of the nine volumes of die
FAO/UNESCO Soil Map of the World (1971-81). The data in the sand, silt,
and clay arrays are stored as proportional values for each soil horizon. The
arbitrary particle size distribution summing to 100 percent included for
Histosols (entries 61-63 in first dimension of each array) should not be used.
Instead, values reflecting the physical properties of organic soils and
appropriate for specific research objectives should be inserted.
The data in the depth array are scaled in meters with the first value being 0m
depth for each soil type and the subsequent values the contact depths of
contiguous horizons. By definition the depth array contains one extra value for
the third dimension corresponding to the bottom depth of the lowest horizon
for each soil type. Within die data set, no soil type had more than 14 soil
horizons. In cases when the number of horizons in a soil type was less than
14, we used -1.0 values to flag the end of record of each soil type. For
example, a soil type with 10 horizons has 10 data entries in the sand, silt, and
clay arrays, 11 data entries for the depth array, and -1.0 values for entries 11 -
IS in each array (entries 12 -15 for the depth array).
Some technical notes are given regarding the 107x10x15 data array for those interested:
GED 1.0 Documentation Global Soil ParticU Size Propertie
A12-19
-------
1) A code for ocdan was added to the group of nine continent codes, thus accounting for the
10 elements of the second dimension of the data array. The data array for all soil horizons
for all soil types for this continent code was zero-filled.
2) The data array was an ASCII text file with four columns of numbers, each column
corresponding to one of die four variables, namely depth, sand, silt, or clay. Thus each array
element was actually a line of text containing four data values for the four variables.
3) The ordering of the array elements into the (one-dimensional) data file was such that the
107 soil types vary slowest, the 10 continent codes vary faster, and the 15 soil horizons vary
fastest. In other words, if an element's position in die array is given by the indices (ijJO
where 1 <= i <= 107,1 <= j <=10, and 1 <= k <= 15 then the position of that element in the
data file is given by ((i - 1) *15 *10) + ((j -1) * 15) + k = ((i - 1) * 10 + j - 1) * 15 + k.
The first stage in producing the IDRISI format for the data array was to separate the data by
variable (depth, sand, silt, and clay) and by horizon number (one through 15) into 60 attribute
values files. Each attribute values file would be composed of feature identification codes
corresponding to each of the 107 soil types for each of the 10 continent codes (explained
below), with each feature i.d. being paired with a data value. The data value for each feature
i.d. was read from the appropriate position in the data array (given above). In other words,
the first and second dimensions of the data array were merged into a single dimension with
107 * 10 = 1070 elements, and the third and fourth dimensions (the fourth dimension is the
variable) were also merged into a single dimension with 15 * 4 = 60 dements. Here the
elements of the first merged dimension are "continental soil type" (the feature i.d.'s) and data
value pairs , and the elements of the second merged dimension are attribute values files,
named after variable and soil horizon.
The second stage in producing the IDRISI format was to create the spatial map associated
with the attribute values files. This spatial map would be the feature definition file that uses
the continental soil types as links between the data values and geographic locations. Since
the soil types and the continental divisions are already spatially defined it only remained to
produce the map of continental soil types. This was done by overlaying the map of continent
codes (WRCONT) multiplied by 1000 with the map of soil types (WRZSOL) via addition1.
Both the original continent codes and the original soil types can be recovered from this map,
the continent code by performing integer division by 1000, and the soil type by taking the
continental soil type modulo 1000.
'This was done by running the IDRISI module SCALAR on WRCONT, choosing the
multiply option and specifying 1000, creating a temporary file, for example WRCONTE4. Then
the IDRISI module OVERLAY was run cm this file and on WRZSOIL, choosing the addition
option and thus creating the feature definition file, for example WRCZSOL, An algebraic
notation for this series of operations would be:
WRCZSOL « WRCONTE4 + WRZSOIL, where WRCONTE4 » 1000 * WRCONT, or
WRCZSOL = (1000 * WRCONT) + WRZSOIL.
GED 1.0 Documentation GMmt Soil PmrtkU Six* Proptrtie$
A12-2Q
-------
The final stage in producing the IDRISI format was to produce 60 separate raster grids from
the 60 attribute values files and the single feature definition file. This was done by running
the IDRISI module ASSIGN on the feature definition file and on each of the 60 attribute
values files. The ASSIGN module creates an output grid from an input grid and an attribute
values file, using the input grid (whose cells take on feature i.d.'s as values) to define the
locations of the data values found in the attribute values file. Hie appropriate data values are
taken from die attribute values file according to the feature i.d.'s paired with each data value.
Thus if a cell in the input grid has a value p and the attribute values file has a feature i.d. and
data value pair (p,z) then die cell with the corresponding position in the output grid will take
on the value z. Note that feature i.d.'s in attribute values files must be unique, but feature
i.d.'s in the feature definition file may occur multiple times.
GED 1.0 Documentation GMmt Soil PgrticU Six* ProptrHn
A12-21
-------
A13
FNOC Elevation, Terrain, and Surface Characteristics
OBD 1.0 Documentation Etamthm, Ttmto, u4 Swrftux ChurtuHrixtkt
A13
-------
DATA-SET DESCRIPTION
DATA-SET NAME: Elevation, Terrain, and Surface Characteristics
PRINCIPAL INVESTIGATORS): Leo Clarke
US Navy Fleet Numerical
Oceanographic Center
SQVRCE
SOURCE DATA CITATION: Fleet Numeric Oceanographic Center. 1985.10-minute
Global Elevation, Terrain, and Surface Characteristics (re-processed by NCAR and
NGDC). Digital Raster Data on a 1-degree Geographic (lat/long) 180x360 grid.
NOAA National Geophysical Data Center. 9 files on 9-track tape or 2 floppy
disks in compressed format, 28 MB. [first published in 1981]
CONTRIBUTORS): Leo Clarke
U.S. Navy, Fleet Numerical Oceanographic Center
Monterey, CA 93943 USA
DISTRIBUTORS): NGDC/WDC-A
VINTAGE: circa 1960's
LINEAGE:
(1) Principal Investigator (digitizing from maps):
Leo Clarke
US Navy Fleet Numerical Oceanographic Center
(2) Reprocessed with corrections to elevation values:
Dennis Joseph
National Center for Atmospheric Research
(3) Error flags, corrections, and re-structuring (1985):
John J. Kineman
NOAA National Geophysical Data Center
Boulder, CO
ORIGINAL DESIGN
VARIABLES:
(1) Elevation: Maximum, minimum, mode (+/- 30 ft)
(2) Urban and Water Coven Percent areal coverage (+/-1)
(3) Primary. Secondary, and Ocean Types: Characteristic class
(4) Number and direction of ridges: Count +/- 1, direction +/- 10.
ORIGIN: Digitized from ONC charts and other maps as available.
GEOGRAPHIC REFERENCE: lat/long
GED 1.0 Documentation Elevation, Terrain, and Surface Characteristic* A13-2
-------
GEOGRAPHIC COVERAGE: Global
Maximum Latitude
Minimum Latitude
Maximum Longitude
Minimum Longitude
+90 degrees (N)
-90 degrees (S)
+180 degrees (E)
-180 degrees (W)
GEOGRAPHIC SAMPLING: Spatial statistics (Mode, Maximum/ and Minimum) and
characteristic classes for 10-minute grid cells.
TIME PERIOD: Modern composite, circa 1970/s
TEMPORAL SAMPLING: Modern Composite
INTEGRATED DATA-SET
DATA-SET CITATION: FNOC. 1992. FNOC/NCAR Global Elevation, Terrain, and
Surface Characteristics. Digital Raster Data on a 10-minute Geographic (lat/long)
1080x2160 grid. In: Global Ecosystems Database Version W: Disc A. Boulder, CO:
NOAA National Geophysical Data Center. 10 independent single-attribute spatial
layere on CD-ROM, 28 MB. [firet published in 1981]
ANALYST(s): John J. Kineman
PROJECTION: Geographic (lat/long), GED window (see User's Guide).
SPATIAL REPRESENTATION: Spatial statistics (Mode, Maximum, Minimum, and
percent coverage) and characteristic classes for 10-minute grid cells.
TEMPORAL REPRESENTATION: Modern Composite
DATA REPRESENTATION:
(1) Elevation (Maximum, minimum, mode): 2-byte integers, representing meters
above sea level, rounded to nearest 10 meters.
(2) Urban and Water Cover: 1-byte integers, representing percent areal cover (+/- 1%)
(3) Primary, Secondary Types, and Ocean/Land Mask: 1-byte integers representing
characteristic classes.
(4) Number of ridees: 1-byte integers representing count +/- 1
(5) Direction of ridges: 1-byte integers representing direction East of True North,
rounded to nearest 10 degrees.
LAYERS AND ATTRIBUTES: 9 independent single-attribute spatial layers
COMPRESSED DATA VOLUME: 2,036,120 bytes
PRIMARY REFERENCES (* reprint on CD-ROM)
Cuming, Michael J. arid Barbara A. Hawldns, 1981. TERDAT: The FNOC System for
Terrain Data Extraction and Processing." Technical report MH Project M-254
(Second Edition). Prepared for Fleet Numerical Oceanography Center (Monterey,
CA). Published by Meteorology International Incorporated. (*see excerpt, below).
ADDITIONAL REFERENCES none
GED 1.0 Documentation A13-3
-------
DATA-SET FILES
LOCATION
Spatial Data»
\GLGEO\RASTER\
KMdtra t
\GLGEO\META\
Palattaai
Tina Sariaas
Voluma on Disk.:
NAMK
NUMBER
TXJOSj £028
FNOCAZM.IMG
1 file
2,332,800
FNOCMAX.IMG
1 file
4,665,600
FNOCMIN.IMG
1 file
4,665,600
FNOCMOD.IMG
1 file
4,665,600
FNOCOCM.IMG
1 file
2,332,800
FNOCPT.IMG
1 file
2,332,800
FNOCRDG.IMG
1 file
2,332,800
FNOCST.IMG
1 file
2,332,800
FNOCURB.IMG
1 file
2,332,800
FNOCWAT.IMG
1 file
2,332,800
FNOCAZM.DOC
1 file
1,026
FNOCMAX.DOC
1 file
512
FNOCMIN.DOC
1 file
512
FNOCMOD.DOC
1 file
510
FNOCOCM.DOC
1 file
561
FNOCPT.DOC
1 file
3,532
FNOCRDG.DOC
1 file
512
FNOCST.DOC
1 file
3,555
FNOCURB.DOC
1 file
537
FNOCWAT.DOC
1 file
538
none
none
20 files
30,338,195
REPRINT FILES
none
SOURCE EXAMPLE FILES
none
GED 1.0 Documentation BlnatUm, Ttmin, ami Surfact CharacterisUct
A13-4
-------
FILE DESCRIPTION
DATA ELEMENT: Elevation
STRUCTURE: Raster nested-grid: 10 arc-minutes (see User's Guide)
SERIES: Elevation statistics
SPATIAL DATA FILES:
FNOCMOD.DOC
file title
Navy Terrain Data—Modal Elevation (meters)
data type
integer
file type
binary
columns
2160
rows
1080
ref. system
lat/long
ref. units
deg
unit dist.
1.0000000
min. X
-180.0000000
max. X
180.0000000
min. Y
-90.0000000
max. Y
90.0000000
pos'n error
unknown
resolution
0.1666667
min. value
-120
max. value
7830
value units
meters
value error
unknown
flag value
none
flag def'n
none
legend cats
0
File Series Parameters:
£ile VARIABLE Mptfoap
FNOCMOD Modal Elevation -120 7830
FNOCMAX Maximum Elevation -120 8840
FNOCMIN Minimum Elevation -240 6100
NOTES:
1. Datum shifts of 20m or more are obvioius in flat areas, especially in Africa and
South America.
2. Many artifacts have been noted in various locations
GED 1.0 Documentation Etomtien, Tmrato, and Swfte* ClmracMria6ct
A13-5
-------
DATA ELEMENT: Primary and Secondary Surface Type
STRUCTURE: Raster Data Files: 10-minutes 1080x2160 GED grid (see User's Guide)
SERIES: Primary arid Secondary classes
SPATIAL DATA FILES:
FNOCPT.DOC
file title :
Navy Terrain Data—Primary Surface Type Codes
data type :
byte
file type
binary
columns :
2160
rows
1080
ref. system :
lat/long
ref. units
deg
unit dist. :
1.0000000
min. X
-180.0000000
max. X :
180.0000000
min. Y :
-90.0000000
max. Y :
90.0000000
pos'n error :
unknown
resolution :
0.1666667
min. value :
0
max. value :
62
value units :
characteristic classes
value error :
unknown
flag value :
99
flag def'n :
flag value 99 indicates bad or missing data
legend cats :
10
File Series Parameters:
File VARIABLE Minimum Maximum
FNOCPT Primary Surface Type 0 62
FNOCST Secondary Surface Type 0 31
legend:
category
0 :
0
salt/lake
category
1 i
1
Flat
category
2 :
2
Desert
category
3 :
3
Marsh
category
4 :
4
Lake/Atol
category
5 :
5
Valley/Be
category
6 :
6
Xso Mount
category
7 :
7
Low Mount
category
8 :
8
Ave Mount
category
9 :
9
Rug Mount
category 31 :
31
Ocean
category
62 :
62
Ocean
salt or lake bed
flat or relatively flat
desert (or, for high latitudes, glaciers or
permanent ice)
marsh
lake country or atoll
major valleys or river beds
isolated mountains, ridge or peak
low mountains or hills
average mountains
extremely rugged mountains
Ocean (Primary Type)
Ocean (Secondary Type)
NOTES:
1. Bad or missing data flagged as 99
2. These data are known to have many errors in land values, especially in the
southern hemisphere.
OED 1.0 Documentation Bkntkm, Ttrratm, and Swfac* ClwacttritHct
A13-6
-------
DATA ELEMENT: Ocean/Land Mask
STRUCTURE: Raster Data Files: 10-minutes 1080x2160 GED grid (see User's Guide)
SERIES: none
SPATIAL DATA FILES:
FNOCOCMDOC
file title
: Ocean Mask (produced from Navy Terrain data)
data type
: byte
file type
: binary
columns
: 2160
rows
: 1080
ref. system
: lat/long
ref. units
: deg
unit dist.
: 1.0000000
rain. X
: -180.0000000
max. X
: 180.0000000
rain. Y
: -90.0000000
max. Y
: 90.0000000
pos'n error
: unknown
resolution
: 0.1666667
rain, value
: 0
max. value
: 1
value units
: characteristic classes
value error
: unknown
flag value
: none
flag def'n
: none
legend cats
: 2
Legend:
category 0 : 0 Ocean
category 1 : 1 Land
NOTES:
1. This layer was derived from other variables in the original FNOC data-set to
provide a convenient ocean/land mask for display and processing uses. It was
also included here as a source data-set for coastline corrections made to the Olson
WE1.4D (see Chapter A05).
2. Land appears to have been given priority to ocean values, thus enlarging some
land areas and reducing lakes (e.g., the Black Sea).
GED 1.0 Documentation Ekftton, Tfcmrfs, amiSmfitetChmwdtHnkt
A13-7
-------
DATA ELEMENT: Number of Ridges
STRUCTURE: Raster Data Files: 10-minutes 1080x2160 GED grid (see User's Guide)
SERIES: none
SPATIAL DATA FILES:
file title
data type
file type
columns
rows
ref. system
ref. units
unit dist.
min. X
max. X
min. Y
max. Y
pos'n error
resolution
min. value
max. value
value units
value error
flag value
flag def'n
legend cats
FNOCRDG.DOC
Navy Terrain Data—Number of Significant Ridges
byte
binary
2160
1080
lat/long
deg
1.0000000
-180.0000000
180.0000000
-90.0000000
90.0000000
unknown
0.1666667
0
63
counts, 0-63
unknown
none
none
0
NOTES:
(1) These data are known to have many layers.
OED 1.0 Documentation Elevation, Terrain, and Surface Characteristics
A13-8
-------
DATA ELEMENT: Direction of Ridges
STRUCTURE: Raster Data Files: 10-minutes 1080x2160 GED grid (see User's Guide)
SERIES; none
SPATIAL DATA FILES:
FNOCAZMDOC
file title : Navy Terrain Data—Direction of Ridges (degrees X 10)
data type : byte
file type : binary
columns : 2160
rows : 1080
ref. system : lat/long
ref. units : deg
unit dist. : 1.0000000
min. X : -180.0000000
max. X : 180.0000000
min. Y : -90.0000000
max. Y : 90.0000000
pos'n error s unknown
resolution : 0.1666667
min. value : 0
max. value : 18
value units : degrees X 10
value error : untaiown
flag value ; none
flag def'n : none
legend cats : 19
Legend:
category 0
category 1
category 2
category 3
category 4
category 5
category 6
category 7
category 8
category 9
category 10
category 11
category 12
category 13
category 14
category 15
category 16
category 17
category 18
0 deg.
1 10 deg.
2 20 deg.
3 30 deg.
4 40 deg.
5 50 deg.
6 60 deg.
7 70 deg.
8 80 deg.
9 90 deg.
10 100 deg.
11 110 deg.
12 120 deg.
13 130 deg.
14 140 deg.
15 150 deg.
16 160 deg.
17 170 deg.
18 180 deg.
NOTES:
1. These data are known to have many errors
GED 1.0 Documentation Elevation, Terrain, and Surface Characteristic*
A13-9
-------
DATA ELEMENT: Water and Urban Cover
STRUCTURE: Raster Data Files: 10-minutes 1080x2160 GED grid (see User's Guide)
SERIES: water and urban
SPATIAL DATA FILES:
FNOCWAT.DOC
file title
: Navy Terrain Data—Percent Water Cover
data type
: byte
file type
: binary
columns
: 2160
rows
: 1080
ref. system
: lat/long
ref. units
: deg
unit dist.
: 1.0000000
min. X
: -180.0000000
max. X
: 180.0000000
min. Y
: -90.0000000
max. Y
: 90.0000000
pos'n error
: unknown
resolution
: 0.1666667
min. value
: 0
max. value
: 100
value units
: percent
value error
: unknown
flag value
: 255
flag def'n
: flag value 255 indicates bad or missing data
legend cats
: 0
File Series:
EU& Variable
FNOCWAT
FNOCURB
Water Cover
Urban Cover
Minimum
0
0
Maximum
100
98
NOTES:
1. These data are known to have many errors
GED 1.0 Documentation Ekvutkm, Ttmt^utiSurftu* OmmcttrMa
A13-10
-------
DATA INTEGRATION AND QUALITY
John ]. Kineman
National Geophysical Data Center
Boulder, CO
SUMMARY
The Navy Fleet Numerical Oceanography Center (NFNOC) began creating the original
10-minute terrain data set in the mid 1960's. Work extended into the early 1970's. The
main sources for the data were the TJ.S. Department of Defense Operational Navigation
Charts (ONC), scale 1:1,000,000. For certain regions ONC charts were not available; for
such areas selected charts from the Jet Navigation Charts and World Aeronautical Charts
were used. The charts were hand read out to forms by employees, and then read by
optical character reader to tape. The values were estimates from contour lines. Isometric
graphs were made for quality control, checking terrain features. Later, other errors were
corrected by the National Center for Atmospheric Research in Boulder, Colorado.
Source data from NCAR were stored in binary compressed format This was converted
at NGDC to an ASCII format for products distributed on tape with latitude/lpngitude
encoding, grouped in 5-degree squares. A series of quality checks were performed on
the data in 1985 to test for internal consistency between the various parameters.
Numerous errors were noted, especially in the southern hemisphere. Some of the errors
could be corrected by comparison between data layers. Others were flagged with a bad-
data code. Errors that could not be detected by comparing the fields were not tested for.
These data were later converted to a raster data file by mapping the lat/long coordinates
into the corresponding 10-minute grid and separating the variables into individual
spatial layers. The resulting files are provided here, with the addition of an "ocean
mask" file produced from a combination of variables in the FNOC data-set. This
land/ocean mask is provided for convenience in masking other data for display, but also
for use in evaluating results of ocean masking in the Olson data-sets (Chapter A05).
Users should take special caution in using these data, as many errors have been noted.
The most commonly used portion of the data-set is the elevation values, and there has
been progress in improving the other values. New source tapes were obtained in the
hopes that some of the errors were introduced during if s long lineage and could be
removed by comparison with the originals; however this approach has not proven to be
feasible due to uncertainties in the source tapes.
Several efforts are underway to obtain improved topography and to derive corrections
from other data. An improved version of the 10-minute data is expected for the next
CD-ROM (Disc B).
GED 1.0 Documentation ElmatUnt, Ttrnin, and Surface ChtmuterUtict
AIM!
-------
COMPILATION OF EXISTING DOCUMENTATION
BACKGROUND
The 10-minute Terrain data set distributed by NGDC was originally produced by the U.S.
Navy, Fleet Numerical Oceanography Center in Monterey, CA. The data were then
transferred to the National Center for Atmospheric Research (NCAR) in Boulder, CO
(Dennis Josephs), where some corrections were made in the elevation values. NCAR was
then the source of NGDC's version. Various quality checks were run on the data at NGDC
in 1986, revealing numerous errors (about 16,000), mostly in the Southern Hemisphere and
mostly in the attribute fields. A second version of the data set was then sent from NCAR.
The new version had fewer errors (about 9,000), still mostly in the attribute values for the
Southern Hemisphere. These errors resulted from 10 automated tests, as listed below:
1)
Range (from max and min) excludes mode
2)
Sea height and type mismatch (between elevation and primary or secondary
type code)
3)
Ridge azimuth out of limit (i.e. < 0 or > 18)
4)
Number of Ridges out of limits
5)
Secondary type undefined
6)
Primary type undefined
7)
% water out of limits
8)
% urban out of limits
9)
Max/min out of limit (exceeds lowest and highest known elevations on earth).
10)
Sea type-code discrepancy (between primary and secondary type codes)
* summaries of these error checks are available from NGDC
In the case of elevation data, corrections were made based on other data sources, but in the
case of the attribute fields, data errors that had no obvious correction were flagged (all bits
on = nine's in the NGDC ASCII format, or 255 in the current one-byte integer format) to
indicate bad data.
Attempts were made to retrieve original or near-original copies of the data set to see if
errors may have been introduced during processing at one or more locations. After several
years, an "original" tape emerged from Mr. Leo Clark at the Navy FNOC. Other copies were
also obtained from varioius sources. NGDC will continue to evaluate the various versions,
and plans to produce an up-dated version the 10-minute data set using all the latest
information and reference to other data. Meanwhile, we are convinced that the data
represented here, although known to have numerous errors, is the "best available" version
for now.
The appendices (A and B) contain information from existing documentation of the previous
GED 1.0 Documentation Elevation, Terrain, and Surface Characteristics
A13-12
-------
(source) versions of the data set, eliminating tape and other format descriptions that are
irrelevant to the current data structure and format (described elsewhere in this manual).
DESCRIPTION OF VARIABLES:
Significant Ridges:
Subjective estimate of number of ridges and their orientation in tens of
degrees (00-18).
Terrain Elevation:
Elevation in meters (converted from original elevation in 100's of feet,
rounded to the nearest 30 meters). Ocean are coded as zero elevation,
however not all zero values indicate ocean. Refer to the Primary or Secondary
terrain characteristics (or the special Ocean mask, which was created from the
Primary terrain characteristics code 62). Inland water bodies are coded with
the elevation of the water surface (except in minimum field where it is always
zero), except when the water body is below sea level, in which case the
surface elevation is used (another exception to this is the Caspian Sea, which
is coded as zero).
Characteristics of the Terrain (Primary and Secondary):
0 : salt or lake bed.
1 : flat or relatively flat.
2 : desert (or, for latitudes greater than 70N, glaciers or permanent
ice).
3 : marsh.
4 : lake country or atoll.
5 major valleys or river beds.
6 isolated mountains, ridge or peak.
7 : low mountains or hills.
8 : average mountains.
9 : extremely rugged mountains.
[31] : Ocean (used in Secondary type only)
[62] : Ocean (used in Primary type only)
Percentage of Water.
For ocean areas at sea level the value is 100, for all other areas the range is 00
to 99 (large lakes or inland seas will not be coded as 100).
Percentage of Urban Development:
Not updated (reflects highly subjective judgements from the maps used).
GED 1.0 Documentation Elevation/ Terrain, and Surface Characteristics
A1343
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APPENDIX A
EXCERPTS FROM NCAR DOCUMENTATION PACKAGE:
"Data Format for Global 10-Minute Elevation Data from the U.S. Navy"
Dennis Joseph
NCAR, Data Support Section
April 1982/ update Dec 1984
Global elevation data at a resolution of 10-minutes were prepared by the Navy Fleet
Numerical Oceanography Center at Monterey. For each 10X10 minute area, the set includes
modal elevation, minimum elevation, maximum elevation, orientation of ridges, terrain
characteristics, and urban development. This is archived by the NCAR Data Support Section
(DSS) in a packed binary format. Parameters available are identical to those described in
documents by Meteorological International, Inc. and the Fleet Numerical Oceanography
Center, but the DSS has made some [format] changes to the set. The information content
of the original set has been preserved entirely. Each 64 bit group [in the NCAR/DSS data
set] has the following format:
Bits
Code
Description
1-6
RR
Estimate of the number of significant ridges
7-12
DD
General direction of ridges
13-21
HMO
Terrain elevation - Modal height.
22-30
HHI
Terrain elevation - Maximum height.
31-39
NLO [HLO]
Terrain elevation - Minimum height.
40-45
CI
Primary characteristics of terrain.
46-50
C2
Secondaiy characteristics of the terrain.
51-57
WWW
Percentage of water surface.
58-64
URB
Percentage of urban development.
General Information:
The modal terrain height has been contoured at NCAR, and major problems
identified in these plots have been corrected by the Navy. Distribution summaries of all
parameters indicate that there are still some invalid elevation values and unexplained code
values, especially in the terrain characteristics field. As of this data no further information
is available on these problems. Occasional occurrences of full range values (all bits on) are
assumed to indicate missing data.
The data distribution summaries showed a strong tendency for elevation values to cluster
around multiples of 500 feet. This is probably due to the contour intervals in the original
GED 1.0 Documentation Elevation, Terrain, and Surface Ckaracteriatia
A13-14
-------
The data distribution summaries showed a strong tendency for elevation values to cluster
around multiples of 500 feet. This is probably due to the contour intervals in the original
maps or to some other characteristic in the method of reading map values.
The true resolution of the data is reduced to 20 minutes poleward of 70 degrees latitude, but
data values are still present for each 10 minute [cell]. More information on the original data
format, the sources of the data, the methods of reading the data, and the routines designed
for the Navy to read the original format is available in documentation by the Fleet
Numerical Oceanography Center and Meteorology International Inc.
General Information Update - DEC 1984:
Various users have noted a large number of bad data points in the minimum elevations.
A few bad points in the modal and maximum elevations have also been identified. An
attempt has been made to remove these bad points and replace them with estimated values.
The minimum values from a previous edition of the data were found to have many fewer
problems and these values were used for all minimum elevations north of 30 South. Checks
for unreasonable values and gradients were run and comparisons of min, mode, and max
were made. The results of these tests were manually inspected and were estimates seemed
better than the original values, they were inserted in the set. Checks were run on the
minimum, modal, and maximum elevation only. No checks were run on the other
parameters.
There are most likely still some erroneous values in the set, but most of the totally
unreasonable values have been removed. Note that the minimum elevations are coded as
zero for all water surfaces regardless of the true elevation of the water surface (even when
this surface is below sea level). In some areas the elevation values are constant over one
degree areas indicating that the resolution is not truly 10 minutes in those areas. In general,
the modal elevations seem to be more reliable than the minimum or maximum.
This corrected set will be the primary archive set, and the uncorrected earlier versions are
available on request.
Roughness computations;
Stephano Tibaldi, European Center for Medium Range Weather Forecasting, has used these
elevations to compute estimates of surface roughness. His method for computing roughness
length (Z) over a user-defined area containing multiple 10' [cells] is given on the following
page. Note that his relative maxima are determined by examining the 8 surrounding [cells].
When looking at data which are poleward of 70 degrees, use every other point to
compensate for true resolution of 20/.
GED 1.0 Documentation Elevation, Terrain, and Surface Characteristics
A13-15
-------
Formula to compute the roughness length Z0
Z =
where:
\
\
|(5>/?-(S>A)2)
t (hr*rpr^
f, *
jy - number of relative ht maxima in the user-defined
grid square
p = surface area of the user-defined grid square
nj - number of significant ridges in the 10' grid square
= mean height in the 10' grid square
hj0** - maximum height in the 10" grid square
jj mitt _ minimum height in the 10" grid square
ft - surface area of the 10' grid square
pt - proportion of the user-defined grid square occupied
by the im 10' grid square
GED 1.0 Documentation Elevation, Terrain, and Surface Characteristics
A13-16
-------
APPENDIX B
EXCERPT FROM NAVY/FNOC DOCUMENTATION:
Cuming, Michael J. and Barbara A. Hawkins, 1981. "TERDAT: The FNOC System for
Terrain Data Extraction and Processing." Technical report Mil Project M-254
(Second Edition). Prepared for Fleet Numerical Oceanography Center (Monterey,
CA). Published by Meteorology International Incorporated. (*see excerpt, below).
THE FNOC TERRAIN DATA SET
The terrain Parameters:
Terrain parameters, listed below, have been extracted from charts and recorded for all 10-
minute latitude by 10-minute longitude arras covering the globe. (This work was begun by
FNOC in the mid-1960's.) The basic charts used were the U.S. Department of Defense
Operational Navigation Charts (ONC), scale 1:10s. For certain regions ONC charts were not
available; for such areas selected charts from the Jet Navigation charts (JN) and World
Aeronautical Charts were used.
The following terrain parameters are available for each lO'xlO' area:
Code Description
RR The estimated number of significant ridges.
DD General orientation of ridges in tens of degrees (0->18).
HMO Terrain elevation - modal height (see NOTE 1).
HHI Terrain elevation ~ maximum height (see NOTE 1).
HLO Terrain elevation ~ minimum height (see NOTE 1)
CI Primary characteristics of the terrain (see NOTE" 2).
C2 Secondary characteristics of the terrain (see NOTE 2).
WWW Percentage of water surface.
UKB Percentage of urban development (see NOTE 4).
NOTES:
1. The most frequently occurring height (HMO) was estimated from contour
lines. Elevations are coded as positive numbers in hundreds of feet. For
example, 1000 ft. is coded as 010; the maximum value of HHI (Mount Everest,
29028 ft) is coded as 290. To avoid negative codings, elevations below sea-
OED 1.0 Documentation Elevation, Terrain, and Surface Characteristics
A13-17
-------
minimum value of HLO (Dead Sea, -1299 ft) is coded as 413.
2. The code for cl and c2 is:
0 — salt or lake bed.
1 — flat or relatively flat.
2 — desert (or, for latitudes greater than 70N, glaciers or permanent
ice).
3 — marsh.
4 - lake country or atoll.
5 - major valleys or river beds.
6 - isolated mountains, ridge or peak.
7 — low mountains or hills. •
8 — average mountains.
9 - extremely rugged mountains.
3. For open sea points, all terrain parameters are set to zero.
4. The Terrain Data Set has not been updated to reflect changes in the
percentage of urban development, in addition the determination of certain
terrain parameters-e.g., RR and DD~is highly subjective.
GED 1.0 Documentation Elevation, Terrain, and Surface Characteristic*
A13-18
-------
A14
Pospeschil Micro World Data Bank II
GED1.0 Documentation Micro World Data Bank H
A14
-------
DATA-SET DESCRIPTION
DATA-SET NAME: Micro World Data Bank II
PRINCIPAL iNVESTiGATOR(s): U.S. Central Intelligence Agency
SOURCE
SOURCE DATA CITATION: Pospeschil, F (analyst). 1988. Micro World Databank II
(MWDB-II): Coastlines, Country Boundaries, Islands, Lakes, and Rivers. Digital vector
data at 1-minute resolution. Bellevue, NB: MicroDoc, Inc. Compressed format on
1 floppy disk, 2.5 MB.
CONTRIBUTOR(s): WDB-II: U.S. National Technical Information Service (NTIS)
MWDB-II Fred Pospeschil
DISTRIBUTOR(s): WDB-II: U.S. National Technical Information Service (NTIS)
Washington D.C. USA
MWDB-n Fred Pospeschil
MicroDoc Inc.
3108 Jackson Street
Bellevue, Nebraska 68005 USA
VINTAGE: unknown
LINEAGE:
(1) CIA World Data Bank n
(2) Generalized to 1-minute by US Air Force
(3 ) Distributed as "Share-ware" by:
Fred Pospeschil
MicroDoc, Inc.
3108 Jackson Street
Bellevue, Nebraska 68005 USA
ORIGINAL DESIGN
VARIABLES: Un-labeled vector boundaries, representing: Coastlines, Islands, National
(Country) borders, State borders (USA), Rivers, and Lakes at 1-minute resolution.
ORIGIN: Originally digitized from maps, primarily ONC Charts.
GEOGRAPHIC REFERENCE: lat/long
GEOGRAPHIC COVERAGE:
Maximum Latitude
Minimum Latitude
Maximum Longitude
Minimum Longitude
Global
+90 degrees (N)
-90 degrees (S)
+180 degrees (E)
-180 degrees (W)
GED 1.0 Documentation Micro World Data Batik. U
A14-2
-------
GEOGRAPHIC SAMPLING: 1-minute point locations
TIME PERIOD: circa 1970's and 80's
TEMPORAL SAMPLING: Composite of modern map data
INTEGRATED DATA-SET
DATA-SET CITATION: Pospeschil, F. 1992. Micro World Databank II (MWDB-H):
Coastlines, Country Boundaries, Islands, Lakes, and Rivers. Digital vector data at 1-
minute resolution. In: Global Ecosystems Database Version 1.0: Disc A. Boulder, CO:
NOAA National Geophysical Data Center. 6 independent single-attribute spatial
layers on CD-ROM, 2.5 MB. [first published in 1988]
ANALYST(s): Fred Pospeschil, MicroDoc Inc.
PROJECTION: Geographic (lat/long), GED window (see User's Guide).
SPATIAL REPRESENTATION: point locations for boundaries, rounded to 1-minute in
latitude and longitude.
TEMPORAL REPRESENTATION: Composite of modern data
DATA REPRESENTATION: Point locations represented in minutes of latitude and
longitude, originating from the Greenwich Meridian and Equator. Values east of
Greenwich are positive, West are negative. Values North of the Equator are
positive, South are negative.
LAYERS AND ATTRIBUTES: 6 independent single-attribute spatial layers attributes
COMPRESSED DATA VOLUME: 772,786 bytes
PRIMARY REFERENCES (* reprint on CD-ROM)
* Pospeschil, F. —. Micro World Data Bank II (MWDB-H). Unpublished
documentation. Bellvue, WA: Micro Doc. 8p.
ADDITIONAL REFERENCES
none
GED 1.0 Documentation Micro World Data Bank U
A14-3
-------
DATA-SET FILES
LOCATION
NAME
NUMBER
TODVL SXZB
Spatial Data:
\GLGEO\RASTER\
MWCOAST.VEC
1
files
857,929
MWISLAND.VEC
1
files
404,436
MWLAKE.VEC
1
files
172,371
MWNATION.VEC
1
files
243,608
MWRIVER.VEC
1
files
315,677
MWSTATE.VEC
1
files
27,680
Headersi
\GLGEO\META\
MWCOAST.DVC
1
files
402
MWISLAND.DVC
1
files
403
MWLAKE.DVC
1
files
401
MWNATION.DVC
1
files
405
MWRIVER.DVC
1
files
402
MWSTATE.DVC
1
files
402
Palettes:
none
Tine Series:
none
Volume on Disk:
12
files
2,024,116
REPRINT FILES
LOCATION
HAMB
NUMBER
m sob
\ DOCUMENT \A14 \
MW_01.PCX to MW_08.PCX
8
files
242,478
Volume on Disk:
8
files
242,478
SOURCE EXAMPLE FILES
none
GED 1.0 Documentation Micro World Data Bank U
A14-4
-------
FILE DESCRIPTION
DATA ELEMENT: Vector Boundaries
STRUCTURE: Vector data file: 1-minute resolution (see User's Guide)
SERIES; Feature files
SPATIAL DATA FILES:
file title
id type
file type
object type
ref. system
ref. units
unit dist.
min. X
max. X
min. Y
max. Y
pos'n error
resolution
comment
MWCOAST.DVC
Micro World Data Bank II Coasts
integer
ascii
line
lat/long
deg
0.0166667
-10800.0000000
10800.0000000
-5400.0000000
5400.0000000
unknown
0.0166667
rounded to 1-minute from World Data Bank II
File Series Parameters:
File Description
MWCOAST
MWISLAND
MWNAHON
MWSTATE
MWRIVER
MWLAKE
Coastlines
Island boundaries
National (Country) borders
State borders (USA)
Rivers
Lake boundaries
NOTES:
(1) Coastline artifacts have been noted in various locations
(2) Political boundaries have not been up-dated since the original compilation
GED 1.0 Documentation Micro World Data bank U
A14-5
-------
DATA INTEGRATION AND QUALITY
Fred Pospeschil
MicroDoc Inc.
John J. Kineman (ed.)
NOAA National Geophysical Data Center
Boulder, CO
INTRODUCTION
The full WDB-II is a digitial map data base produced by the Central Intelligence Agency
(CIA) and distributed by the National Technical Information Service (NTIS), U.S.
Department of Commerce, 5285 Port Royal Road, Springfield, VA, 22161. In it's original
form, Micro WDB-II is a highly compressed version of WDB-II which is suitable for use
on micro computers and was put in this configuration by Micro Doc. Before describing
Micro WDB-II a few words should be said about the source file - WDB-II. The following
paragraphs are paraphrased from the NHS overview of WDB-II.
WDB-II is a digitial representation of the world coastlines and boundaries
suitable for use in automated mapping systems. It contains approximately
six million discrete geographic points and was digitized using all available
sources of information. Map scales used range from 1:750,000 to 1:4,000,000
with a nominal scale of 1:3,000,000. These points are grouped by and
identified as describing (1) coast lines, (2) country boundaries, (3) state
boundaries (USA only), (4) islands, (5) lakes, and (6) rivers. Each of these
groupings is further broken down into features and subordinate
classifications/ranks. These ranks are hierarchically structured, and are also
used for plotting symbol definition.
WDB-II, as provided by NTIS, is in a 20 character format on five 9 track
EBCDIC one-half inch magnetic tapes. This data base consists of two types
of records, one for the line segment identifier data, and the other for the
latitude and longitude values of each discrete point making up the line
segment. In this format latitude and longitude values are recorded only as
integers in degrees, minutes, and seconds. WDB-II is available for $660.00
(Order Number PB-271 874 SET/HBG).
Clearly, WDB-II is an excellent data source when making large (4x6 foot) plots on a
mainframe or minicomputer. It is, however, somewhat large (150 - 200 megabytes) for
use on microcomputers. Even on the larger commercial online graphics systems, many
GED 1.0 Documentation Micro World Data Bank II
A14-6
-------
points have to be filtered out before generating displays. For this reason many people
have spent considerable time over the past to filter and compress this data into a form
which could be used in desktop computers. To these people we wish to express our
appreciation - particularly Antonio Riveria who provided Micro Doc with the latest
download of the file.
BACKGROUND
The present version began as a three megabyte ASCII text file which contained some
179,000 points selected from all six of the line types described above. This file was then
converted into a sixteen bit integer format which reduced the size to just over one
megabyte. Since this was still a little large for most five inch disk formats the file was
divided into six files - one for each of the six line types. The coast line file was further
divided into two files as it was over 400 KB. With this processing completed the file was
configured such that it could be readily moved to most desk top microcomputers using
the MSDOS disk format.
The MWDB-n distributed by Micro Doc allows the user to extract 5 levels of detail from
the database for each line type. Each level of detail retains the same number of line
segments, but generalized to a different number of points per segment.
INTEGRATION
For use in the Global Ecosystems Database, the most detailed level of MWDB-II was
chosen and is represented in the six vector data-sets included on the CD-ROM. These
files were created by first extracting the highest level of detail from MWDB-II using the
Micro Doc software, then reformatting the resulting vector files for use in the GED. The
Geographic Information Structure of the GED eliminates the need for imbedded line type
codes (each type becomes a separate overlay) and detail level selection (most GIS have
functions for generalizing lines). Without generalizing or windowing the vector files,
however, some plots may be slow (e.g., the coastline file, MWCOAST).
The following table shows the number of points which are in each file and for the full
level of detail (i.e., all points in MWDB-II) used in the GED. It also shows the number of
line segments in each file. File sizes were given in the File Description section, earlier in
this Chapter.
GED 1.0 Documentation Micro World Data Bank XT
A14-7
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Micro WDB-fl File Composition - detail level 1 (all points)
Detail
COASTCOUNTRY
STATE
ISLAND
LAKE
RIVER
Total
Points
75175
22359
2259
35171
15118
28194
179331
Lines
208
301
111
1AA
JTI
103
196
1263
"This product contains/uses data and/or code placed in the public domain by Fred
Pospeschil and Antonio Riveria. Original coordinate data was created by the Central
Intelligence Agency."
GED 1.0 Documentation Micro World Data Bonk U
A14-8
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A15X
Edwards Global Gridded Elevation and Bathymetry
GED 1.0 Documentation. GUM Griddtd Elevation mud BMtkymftry
A15X
-------
DATA-SET DESCRIPTION
DATA-SET NAME: Global Gridded Elevation and Bathymetry
PRINCIPAL INVESTIGATOR(s): Margaret Edwards
SOURCE
SOURCE DATA CITATION: Edwards, M.0.1989. Global Gridded Elevation and
Bathymetry (ET0P05). Digital raster data on a 5-minute Geographic (lat/long)
2160x4320 (centroid-registered) grid. 9-track tape. Boulder, CO: NOAA National
Geophysical Data Center. 18.6 MB.
CONTRIBUTOR(s): Dr. Margaret Edwards
Department of Earth and Planetary Sciences
Washington University, Campus Box 1169
One Brookings Drive
Saint, Louis, Missouri 63130-4899
DISTRIBUTOR(s): NGDC/Marine Geology and Geophysics Division
VINTAGE: circa 1960's
LINEAGE:
(1) 5-minute dataset Integrated from best available 5 and 10-minute digital sources:
Margaret Edwards
Washington University
Earth and Planetary Remote Sensing Laboratoiy
St. Louis, MO
(2) Corrections, distributed as "ET0P05"
Peter W. Sloss
NOAA National Geophysical Data Center
Boulder, CO
ORIGINAL DESIGN
VARIABLES: Elevation and bathymetry (meters). 10-minute data were expressed to
nearest 30 feet, 5-minute data expressed to nearest meter.
ORIGIN: Integrated from best available 5- and 10- minute digital sources: (1) US Navy
Fleet Numeric Oceanographic Center Montery, CA (10-minute), (2) US Defense
Mapping Agency (5-minute for USA, Europe, Japan, and Korea), (3) US Naval
Oceanographic Observatory (4) Bureau of Mineral Resources of Australia, and
Department of Scientific and Industrial Research of New Zealand (5-,minute).
GEOGRAPHIC REFERENCE: lat/long, with origin at the Greenwich Meridian
GED 1.0 Documentation Global Gridded Elevation and Bathymetry
A15X-2
-------
GEOGRAPHIC COVERAGE:
Maximum Latitude
Minimum Latitude
Maximum Longitude
Minimum Longitude
Global
+90 degrees (N)
-90 degrees (S)
+360 degrees (E)
0 degrees (E)
GEOGRAPHIC SAMPLING: 10-minute (modal elevation) and 5-minute (average
elevation) grid cell values integrated into one 5-minute grid. 5-minute data are
used for land data in Europe, Japan, Korea, United States, and Australia. 10-
minute data are used for land data elsewhere. 5-minute data were used for all
ocean areas.
TIME PERIOD: Modern composite, circa 1950's-1970's
TEMPORAL SAMPLING: Composite of available information.
INTEGRATED DATA-SET
DATA-SET CITATION: NOAA/NGDC. 1992. Integrated Global Elevation and Bathymetry.
Digital Data. NOAA/NGDC/WDC-A, Boulder, Colorado. Digital raster data on a
5-minute Geographic (lat/long) 2160x4320 grid. In: Global Ecosystems Database
Version 1.0: Disc A. Boulder, CO: NOAA National Geophysical Data Center. 1
independent single-attribute spatial layer on CD-ROM. 18.6 MB. [first published
in 1989]
ANALYSTS): Peter Sloss, NGDC
PROJECTION: Geographic (lat/long), GED window (see User's Guide).
SPATIAL REPRESENTATION: 10-minute (modal elevation) and 5-minute (average
elevation) grid cell values integrated onto a 5-minute grid.
TEMPORAL REPRESENTATION: Modern Composite
DATA REPRESENTATION: 2-byte integers representing elevation and bathymetiy in
meters above or below sea-level. Expressed to nearest meter.
LAYERS AND ATTRIBUTES: 1 independent single-attribute spatial layer.
COMPRESSED DATA VOLUME: 17,359,125 bytes
PRIMARY REFERENCES (* reprint on CD-ROM)
* Edwards, Margaret Helen, 1986. "Digital Image Processing of Local and Global
Bathymetric Data." Master's Thesis. Washington University, Department of
Earth and Planetary Sciences, St. Louis, Missouri, 106p.
Haxby, W. F., et al, 1983. "Digital Images of Combined Oceanic and Continental
Data Sets and Their Use in Tectonic Studies." EOS Transactions of the
American Geophysical Union, vol. 64, no. 52, pp. 995-1004.
ADDITIONAL REFERENCES
none
GED 1.0 Documentation Global Gridded Elevation and Bathymetry
A15X-3
-------
DATA-SET FILES (experimental)
LOCATION
KAMK
NUMBER
TOTKCj SEE
Spatial Data:
\SOURCE\RASTER\
Headersi
\SOURCE\META\
Palettes:
Tims Series:
ET0P05.IMG
ET0P05,DOC
none
none
1 files
1 files
18,662,400
509
Volume on Disk:
2 files
18,662,909
REPRINT FILES
LOCATION
HAMH
NUMBER
innc. sizB
\DOCUMENT\A15X\
ETOP_01.PCX to ETOP_24.PCX
ETOP_# #X.PCX
24 files
5 files
586,087
313,996
Volume on Disk:
29 files
900,083
SOURCE EXAMPLE
FILES
none
GED 1.0 Documentation Global Gridded Elevation and Bathymetry A15X-4
-------
FILE DESCRIPTION
DATA ELEMENT (experimental); Elevation and Bathymetry
STRUCTURE; Raster Data File: 5-minute 2160x4320 GED grid (see User's Guide)
SERIES: none
SPATIAL DATA FILES:
ETOP05.DOC
file title
Global Elevation and Bathymetry (meters)
data type
integer
file type
binary
columns
4320
rows
2160
re£. system
lat/long
ref. units
deg
unit dist.
1.0000000
min. X
-180.0000000
max. X
180.0000000
min. Y
-90.0000000
max. Y
90.0000000
pos'n error
unknown
resolution
0.0833333
min. value
-10376
max. value
7833
value units
meters
value error
unknown
flag value
none
flag def'n
none
legend cats
0
NOTES:
(1) The bathymetry data conform to a centroid-registered grid with upper-left cell
centered on 90 degrees (N) and -180 degrees (W). The last row (90 degrees South)
is missing and there is no redundant column at 180 degrees (E).
(2) Land data are shifted generally to the West by 5 to 10 minutes (e.g., 5-minutes in
Hawaii and Japan, 10-minutes in Africa), however shorelines are governed by the
bathymetric data, which seems to be given priority.
(3) Data come from mixed sources.
(4) There is an erroneous line in the Antarctic region at about 81 degree S. beginning
at the Greenwich Meridian and continuing East.
(5) Effective resolution in some areas is a poor as 1-degree (e.g., China and Mongolia)
due to sparse data on the original maps that were digitized.
(6) Many discontinuities appear in the land data over South America, Asia, and
Africa, originating with the FNOC terrain data.
GED 1.0 Documentation Global Gridded Elevatim and Bathymetry
A15X-5
-------
DATA INTEGRATION AND QUALITY
Peter W. Sloss and John J. Kineman
NOAA National Geophysical Data Center
Boulder, CO
ET0P05 combines the data-set DBDB5 (5-minute grid of worldwide bathymetry) and
additional data which constitute a 5-minute grid of worldwide topography. These data
were provided as a 5-minute centroid-registered grid with last row (-90 degrees) missing
and no replication of the column at the Greenwich Meridian at the eastern edge of the
grid. Processing involved separating the grid into two halves at Greenwich, and then re-
assembling a grid originating at the International Date Line. Conversion to Idrisi format
was trivial, requiring only the creation of a header (.DOC) file.
No interpolation was done to register the grid to the GED convention (i.e., to correct for
the 2.5 minute offset of the centroid-registered grid) because of non-uniform registration
in the original data-set itself, between the bathymetric data and land. While the
bathymetric data appear to conform to the stated centroid-registered convention, with the
north-most row centered on +90 degrees and the west-most column centered on -180
degrees, the land data show mis-registrations of from one to two pixels (i.e., from 5 to 10
minutes).
All ocean depth data are -1 meter or deeper, and these bathymetric data were apparently
given priority over land data (shorelines are thus indicated by the -1 meter contour).
This, plus the 1 to 2 pixel internal mis-registration of land data, may create abrupt
transitions on western coasts compared to eastern coasts, which may pick up zero values
from the ocean areas in the underlying terrain data-sets. This can be observed especially
in islands or coasts with sharp relief, such as the Hawaiian Islands (Mauna Loa is offset
by at least 5-minutes to the West).
CAUTION: These data should not be used for overlay with other data at full resolution
without first correcting the registration errors for the region of interest (especially
distinguishing between land and bathymetry). However, since this represents the best
publicly available land and bathymetric data-set, it has been popular for use with coarser
scale models, or for regional studies where the registration shifts can be corrected.
An improved version of this data-set is being produced at NGDC. The current data are
provided for experimental use (e.g., registration corrections and aggregation to coarser
scale), and to provide a link with prior uses of ET0P05.
GED 1.0 Documentation Global Gridded Elevation and Bathymetry
A15X-6
-------
A16X
UNEP/GRID Gridded FAO/UNESCO Soil Units
GED1.0 Documentation Gridded FAO/UNESCO Soil Unit*
A16X
-------
DATA-SET DESCRIPTION
DATA-SET NAME: Gridded FAO/UNESCO Soil Units
PRINCIPAL INVESTIGATORS): FAO/UNESCO
SOURCE
SOURCE DATA CITATION: UNEP/GRID. 1986. FAO Soil Map of the World in
digital form. Digital Raster Data on a 2-minute Geographic (lat/long) 5400x10800
grid. Carouge, Switzerland: UNEP/GRID. 1 file on 9-track tape, 58.3 MB.
CONTRIBUTOR(s): FAO/UNESCO
DISTRIBUTOR(s): GRID/Geneva
VINTAGE: circa 1970's
LINEAGE:
(1) Original investigation: FAO/UNESCO
(2) Digitizing: ESRI (FAO contract)
380 New York Street
Redlands, CA 92373
(3) Reprocessed: UNEP/GRID
6 rue de la Gabelle
1227 Carouge Switzerland
ORIGINAL DESIGN
VARIABLES:
soil classes
ORIGIN:
GEOGRAPHIC REFERENCE: lat/long
GEOGRAPHIC COVERAGE: Global
Maximum Latitude : +90 degrees (N)
Minimum Latitude -90 degrees (S)
Maximum Longitude : +180 degrees (E)
Minimum Longitude : -180 degrees (W)
GEOGRAPHIC SAMPLING: 1:5,000,000 printed map 2-min raster grid sampled from
vector polygon data
TIME PERIOD: prior to 1974
TEMPORAL SAMPLING: none Muli-year composite
GED1.0 Documentation Gridded FAO/UNESCO Soil Unit*
A16X-2
-------
INTEGRATED DATA-SET
DATA-SET CITATION: UNEP/GRID. 1992. Global Gridded FAO/UNESCO Soil Units.
Digital Raster Data on a 2-minute Geographic (lat/long) 10800x5400 grid. In:
Global Ecosystems Database Version 1.0: Disc A. Boulder, CO NOAA National
Geophysical Data Center. 1 single-attribute spatial layer on CD-ROM, 58.3 MB.
[first published in 1984]
ANALYSTS): Lloyd MacGregor, UNEP/GRID
PROJECTION: Geographic (lat/long), GED window (see User's Guide).
SPATIAL REPRESENTATION: Dominant classes within 2-minute grid cells
TEMPORAL REPRESENTATION: Composite of most recent data.
DATA REPRESENTATION: 1-byte integers representing characteristic classes
LAYERS AND ATTRIBUTES: 1 single-attribute spatial layer
COMPRESSED DATA VOLUME: 1,298,699 bytes
PRIMARY REFERENCES (* reprint on CD-ROM)
* Unpublished documentation from GRID/Geneva.
FAO/UNESCO. 1974. Soil Map of the World, ISflOOflOO: 10 volumes. UNESCO,
Paris.
ADDITIONAL REFERENCES
ESRI. 1984. UNEP/FAO World and Africa GIS Data Base: Final Report. Redlands,
CA: Environmental Systems Research Institute Inc. 500+pp.
Also see Chapters A06, A07, A08, A10, All, and A12
GED 1.0 Documentation GMitd FAO/UNESCO Soil Vbdu
A16X-3
-------
DATA-SET FILES (experimental)
LOCATION
NAME
NUMBER
Tami> sezb
Spatial Data:
\SOURCE\RASTER\
Headers;
\SOURCE\META\
Palettes t
\SOURCE\META\
Time Series:
FAOSOIL.IMG
FAOSOIL.DOC
FAOSOIL8.PAL
none
1 files
1 files
1 file
58,320,000
6,254
4,352
Volume on Disk:
3 files
58,330,606
REPRINT FILES
LOCATION
NAME
NUMBER
TUQKi SOS
\DOCUMENT\A16X\
FAO_01.PCX to FAO_02.PCX
2 files
95,172
Volume on Disk:
2 files
95,172
SOURCE EXAMPLE FILES
none
GED1.0 Documentation Gridded FAO/UNESCO Soil Unit* A16X-4
-------
FILE DESCRIPTION
DATA ELEMENT (experimental): GRIDDED FAO/UNESCO SOIL
UNITS
STRUCTURE: Raster Data File: 2-minute 10800x5400 grid (see User's Guide)
SERIES: none
SPATIAL DATA FILES:
FAOSOIL.DOC
file title
UNEP/GRID Gridded FAO/UNESCO Soil Units
data type
byte
file type
binary
columns
10800
rows
5400
ref. system
lat/long
ref. units
deg
unit dist.
1.0000000
min. X
-180.0000000
max. X
180.0000000
min. Y
-90.0000000
max. Y
90.0000000
pos'n error
unknown
resolution
0.0333333
min. value
0
max. value
133
value units
characteristic classes
value error
unknown
flag value
none
flag def'n
none
legend cats
134
Legend:
category
0
0
Ocean
category
1
1
A
Acrisols
category
2
2
Af
Ferric Acrisols
category
3
3
Ag
Gleyic Acrisols
category
4
4
Ah
Humic Acrisols
category
5
5
Ao
Orthic Acrisols
category
6
6
Ap
Plinthic Acrisols
category
7
7
B
Cambisols
category
8
8
Be
Chromic Cambisols
category
9
9
Bd
Dystric Cambisols
category
10
10
Be
Eutric Cambisols
category
11
11
Bf
Ferralic Cambisols
category
12
12
Bg
Gleyic Cambisols
category
13
13
Bh
Humic Cambisols
category
14
14
Bk
Calcic Cambisols
category
15
15
Bv
Vertic Cambisols
category
16
16
BX
Gelic Cambisols
category
17
17
c
Chernozems
category
18
18
eg
Glossic Chernozems
category
19
19
Ch
Haplic Chernozems
category
20
20
ck
Calcic Chernozems
category
21
21
Cl
Luvic Chernozems
GED1.0 Documentation Gridded FAOfUNESCO Soil Units
A16X-5
-------
category
22
22
D
category
23
23
Dd
category
24
24
De
category
25
25
Dg
category
26
26
E
category
27
27
F
category
28
28
Fa
category
29
29
Fh
category
30
30
Fo
category
31
31
Fp
category
32
32
Fr
category
33
33
Fx
category
34
34
G
category
35
35
Gc
category
36
36
Gd
category
37
37
Ge
category
38
38
Gh
category
39
39
Gm
category
40
40
Gp
category
41
41
GX
category
42
42
H
category
43
43
He
category
44
44
Hg
category
45
45
Hh
category
46
46
Hi
category
47
47
I
category
48
48
J
category
49
49
Jc
category
50
50
Jd
category
51
51
Je
category
52
52
Jt
category
53
53
K
category
54
54
Kh
category
55
55
Kk
category
56
56
K1
category
57
57
L
category
58
58
La
category
59
59
Lc
category
60
60
Lf
category
61
61
Lg
category
62
62
Lk
category
63
63
Lo
category
64
64
Lp
category
65
65
Lv
category
66
66
M
category
67
67
Mg
category
68
68
Mo
category
69
69
N
category
70
70
Nd
category
71
71
Ne
category
72
72
Nh
category 73
73
0
category
74
74
Od
category
75
75
Oe
category 76
76
Ox
category
77
77
P
category
78
78
Pf
Podzoluvisols
Dystric Podzoluvisols
Eutric Podzoluvisols
Gleyic Podzoluvisols
Rendzinas
Ferralsols
Acric Ferralsols
Humic Ferralsols
Orthic Ferralsols
Plinthic Ferralsols
Khodic Ferralsols
Xanthic Ferralsols
Gleysols
Calcaric Gleysols
Dystric Gleysols
Eutric Gleysols
Humic Gleysols
Mollic Gleysols
Plinthic Gleysols
Gelic Gleysols
Phaeozems
Calcaric Phaeozems
Gleyic Phaeozems
Haplic Phaeozems
Luvic Phaeozems
Lithosols
Fluvisols
Calcaric Fluvisols
Dystric Fluvisols
Eutric Fluvisols
Thionic Fluvisols
Kastanozems
Haplic Kastanozems
Calcic Kastanozems
Luvic Kastanozems
Luvisols
Albic Luvisols
Chromic Luvisols
Ferric Luvisols
Gleyic Luvisols
Calcic Luvisols
Orthic Luvisols
Plinthic Luvisols
Vertic Luvisols
Greyzems
Gleyic Greyzems
Orthic Gleyzems
Nitosols
Dystric Nitosols
Eutric Nitosols
Humic Nitosols
Histosols
Dystric Histosols
Eutric Histosols
Gelic Histosols
Podzols
Ferric Podzols
GED1.0 Documentation GrUdei FAO/UNESCO Soil IM*
A16X-6
-------
category
79
79
Pg
Gleyic Podzols
category
80
80
Ph
Humic Podzols
category
81
81
PI
Leptic Podzols
category
82
82
Po
Orthic Podzols
category
83
83
Pp
Placic Podzols
category
84
84
Q
Arenosols
category
85
85
Qa
Albic Arenosols
category
86
86
Qc
Cambic Arenosols
category
87
87
Qf
Ferralic Arenosols
category
88
88
Q1
Luvic Arenosols
category
89
89
R
Regosols
category
90
90
Rc
Calcaric Regosols
category
91
91
Rd
Dystric Regosols
category
92
92
Re
Eutric Regosols
category
93
93
Rx
Gelic Regosols
category
94
94
S
Solonetz
category
95
95
Sg
Gleyic Solonetz
category
96
96
Sm
Mollic Solonetz
category
97
97
So
Orthic Solonetz
category
98
98
T
Andosols
category
99
99
Th
Humic Andosols
categorylOO
100
Tm
Mollic Andosols
categorylOl
101
To
Ochric Andosols
categoryl02
102
Tv
Vitric Andosols
categoryl03
103
U
Rankers
category!. 04
104
V
Vertisols
categoryl05
105
Vc
Chromic Vertisols
categoryl06
106
vp
Pellic Vertisols
categoryl07
107
W
Planosols
categoryl08
108
Wd
Dystric Planosols
category 109
109
We
Eutric Planosols
category 110
110
Wh
Humic Planosols
categorylll
111
Wm
Mollic Planosols
categoryll2
112
Ws
Solodic Planosols
categoryll3
113
wx
Gelic Planosols
category114
114
X
Xerosols
categoryll5
115
Xh
Haplic Xerosols
categoryll6
116
Xk
Calcic Xerosols
categoryll7
117
XI
Luvic Xerosols
categoryll8
118
Xy
Gypsic Xerosols
categoryll9
119
Y
Yermosols
category 120
120
Yh
Haplic Yermosols
categoryl21
121
Yk
Calcic Yermosols
categoryl22
122
Yl
Luvic Yermosols
categoryl23
123
Yt
Takyric Yermosols
category124
124
Yy
Gypsic Yermosols
categoryl25
125
z
Solonchaks
categoryl26
126
zg
Gleyic Solonchaks
category127
127
Zm
Mollic Solonchaks
categoryl28
128
Zo
Orthic Solonchaks
category129
129
zt
Takyric Solonchaks
categoryl30
130
RO
Rock
category131
131
SA
Salt
category 132
132
WA
Water
category133
133
--
no name
GBD1.0 Documentation GrUUUd TAO/UNESCO Soil Unit*
A16X-7
-------
NOTES:
1. This data-set was created at UNEP/GRID by rasterizing a vector version of the
FAO/UNESCO soils. The UNFAO is in the process of revising the data, and an
updated version of the vector data will be released when available.
2. This 2-minute data-set does not easily match the GED convention of "nested-
grids." For this reason, and because it is a provisional data-set, it is placed in the
"SOURCE" directory on the GED CD-ROM. The FAO/UNESCO soils data have
been used as a basis for many of the other data-sets in the GED, however, this
version of the FAO soils is provided only for intercomparison - the other data
were not derived from this data-set.
3. A revised classification has been produced (FAO, 1988 revised legend for the Soil
Map of the World) but was not available for this report. A revised version of this
data-set may be available from the International Soil Reference and Information
Center (ISRIC), The Netherlands; from FAO, Rome; or through the WISE project
(World Inventory on Soil Emissions).
GED 1.0 Documentation Gridded FAO/UNESCO Soil Units
A16X-8
-------
DATA INTEGRATION AND QUALITY
John J. Kineman (ed.)
NOAA National Geophysical Data Center
Boulder, CO
BACKGROUND
This data-set was produced at UNEP/GRID (Geneva) by rasterizing on a 2-minute grid
from a vector GIS (Arc/Info) version of the 1973 FAO/UNESCO Soil Map of the World
at 1:5,000,000 scale, produced by ESRI of Redlands CA. This work was completed in
1984 as part of an FAO/UNEP Desertification and Mapping Project (ESRI, 1984). The
Arc/Info version of the FAO Soil Map of the World was used as the base map for this
project. The original FAO Soil Map was produced on 18 map sheets with varying
projections. The digitized (vector) version was thus broken into regions with different
projections. One of these projections did not have an inverse transformation (Miller
Oblate Stereographic Projection for Africa), so it has been difficult to assemble a digital
version of this data-set onto a uniform (i.e., lajt/long) global grid.
Some modifications were made to the original data in the production of this version at
UNEP/GRID, including conversion from a 106 category legend to 133 categories.
Although the documentation provided with the data refers only to Africa, it is assumed
to be relevant to the global data-set. For more information on content of the data-set, see
the scanned documentation on the CD-ROM (DOCUMENT/A16X).
PROCESSING
Projection transformations were performed at UNEP/GRID (Geneva) to produce a global
data-set in lat/long projection, which was then rasterized. The exact methods used have
not been published, except for the informal documentation sent from GRID, which
appears in the scanned documentation on disc (DOCUMENT/A16X/FAO_#.PCX).
Nevertheless, it is likely that a revised version of this data-set will be produced in the
near future, through various cooperative efforts. FAO (Rome) has developed a revised
classification for the map, and recommends that the older version (the one supplied here)
be abandoned in favor of the newer classification (which, reportedly, does not change the
underlying spatial units). Meanwhile, however, versions of the ESRI digital version have
been disseminated to many research groups and individuals, and the information has
worked its way into the literature in significant ways. Many of the soils and vegetation
data-sets included in the Global Ecosystems Database were based on the current version
of the FAO Soils Map of the World (see Additional References for specific Chapters).
GED1.0 Documentation Gridded FAO/UNESCO Soil Unit*
A16X-9
-------
Because documentation is limited for this version of the data-set, and because the 2-
minute grid-cell size is not compatible with the adopted GED "nested-grid" convention, it
is listed here as an experimental data-set in transition. On the other hand, the extensive
use of the FAO Soils Map (vector version) and the future need for comparison with
revised versions, indicates the need for distribution at this stage, in a form that can be
easily compared to it's derivative data-sets, other data-sets, and subsequent versions.
This UNEP raster version meets this need, since it is in a convenient form for
intercomparison (except for the grid size), although there are questions of how
representative it may be of the original data.
No attempt was made to further process the data except to bring it into the GED format
for experimental use, and to create a color palette conforming to the information
contained in the UNEP/GRID documentation. It conforms to the GED window and
registration convention (i.e., edge-registered cells windowed between poles and with the
International Date Line at the eastern and western edges of the grid). The 2-minute grid
cell is an even multiple of 10-minutes and 30-minutes and 1-degree, thus affording easy
comparison with the other data-sets in the GED that are based on the FAO Soils data. It
is not directly comparable with 5-minute grids, however, which will likely be the
preferred alternative in the "nested-grid" structure (see User's Guide).
GED 1.0 Documentation Gridded FAO/umsco Soil Unit*
~U.S. GOVERNMENT PRINTING OFFICE:1995-673-018/00077
A16X-10
------- |