EJBD
ARCHIVE
EPA
601-
D-
91-
001
United States Environmental Monitoring TS-AMD-92G03
Environmental Systems Laboratory December 1991
Protection P.O Box 99478
Agency Las Vegas, NV 99193-3478
v>EPA INTERNAL REPORT
GREAT LAKES ECOLOGICAL
PROCESS PILOTS (GLEPP)
Green Bay, Wisconsin
Saginaw Bay, Michigan
*
TECHNICAL WORK PLAN
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Great Lakes Watershed
AVHRR composite
Sept 14 Sept 27, 1990
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001
GREAT LAKES ECOLOGICAL PROCESS PILOTS (GLEPP)
Green Bay, Wisconsin
Saginaw Bay, Michigan
TECHNICAL WORK PLAN
This document Is a preliminary draft. It has
not been formally released by EPA and should
not at this stage be construed to represent
Agency policy. It is being circulated for
comment on Its technical accuracy and policy
ENVIRONMENTAL MONITORING SYSTEMS LABORATORY
OFFICE OF RESEARCH AND DEVELOPMENT
U.S. ENVIRONMENTAL PROTECTION AGENCY
P.O. BOX 93478
LAS VEGAS, NEVADA 89193-3478
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CONTENTS
SUMHARY OBJECTIVE 1
BACKGROUND 2
OBJECTIVE DESCRIPTIONS 4
Ob-iective 1 - Data Collection and Database Development 4
FY91 Data Collection (Green Bay/Saginaw Bay)
FY92 Data Collection (Green Bay)
Digital Data Analysis 8
Landsat Thematic Mapper (TM)
Aircraft Multispectral Scanner (MSS)
Thematic Mapper Simulator (TMS)
FY92 Database Development 10
Bathymetry
Digital Elevation Models (DEM)
Green Bay Database Development
Saginaw Bay Database Development
Objective 2 - Database Evaluation 13
Regulatory Functions
Habitat Inventories
Ecosystem Modeling
Ob-iective 3 - Process Sampling Frame Development 16
Objective 4 - Ecological Process Studies 17
STUDY PARTICIPANTS 21
STUDY SCHEDULE 22
MEETING SCHEDULE/BUDGET 23
APPENDICES
A - Sensor Descriptions 24
B - EPA EMAP-LC Classification Scheme 32
C - GLEPP Distribution List 38
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1. SUMMARY OBJECTIVE
The scope of this project begins with the development of a multi-resolution digital database for
characterization of Green Bay, Wisconsin and Saginaw Bay, Michigan utilizing a multistage remote
sensing approach. The remotely sensed data collected June 1991 is from a combination of sensors
aboard satellite and aircraft platforms. These data will be integrated with available bathymetry,
elevation, and updated USGS National Wetland Inventory (NWI) data into a geographic information
system (CIS). Once compiled, the CIS will be evaluated by several federal and state agencies for
usefulness in regulatory programs, habitat inventories, watershed analyses, and environmental
monitoring programs.
The pilot CIS will also be utilized to develop a sampling frame(s) for freshwater ecosystem process
studies in Green Bay (FY92) and for Saginaw Bay (FY93). The ecological process studies will focus
on origin-transport-fate modeling scenarios by integrating information collected from remote sensing,
in-situ measurements, and existing digital data. Freshwater systems are influenced by terrestrial
upstream processes in the watershed through hydrologic events/processes. Water, sediments, and
dissolved nutrients are transported from the terrestrial ecosystems (origin) to the freshwater system
(fate). The "fate" issue becomes more complex with factors such as wind speed and direction, air
temperature, water temperature, wave height, etc. all playing a role in circulation and mixing patterns.
The objectives of the two pilots (Green Bay and Saginaw Bay) are:
1. FY92 construction of a multi-resolution land cover/land use (LC/LU) and thermal database for
Green Bay and Saginaw Bay (including watershed elements). Participants are EPA Environmental
Monitoring Systems Laboratory-Las Vegas (EMSL-LV), NASA Ames Research Center
(NASA/AMES), and U.S. Army Corps of Engineers-Waterways Experiment Station (WES).
2. FY92 evaluation of the database by federal and state agencies for use in regulatory programs,
habitat inventories, watershed analysis, and environmental monitoring programs. Participants are
EPA's Region 5 (Chicago), the Environmental Research Laboratory-Duluth (ERL-D), and the Great
Lakes National Program Office (GLNPO), USACE, Wisconsin Department of Natural Resources
(WDNR), Michigan Department of Natural Resources (MDNR), USDA Soil Conservation Service -
Wisconsin and Michigan State Offices (SCS-WI, SCS-MI).
3. FY92 use of the multi-resolution database by ecosystem researchers as baseline information in
development of sampling frame(s) for freshwater ecosystem process studies. Participants are EPA's
EMSL-LV, ERL-D and GLNPO, NASA/AMES, and University of Wisconsin-Milwaukee (UW-M).
4. Perform FY93 freshwater ecosystem process studies in Green Bay and Saginaw Bay, using field
measurement and monitoring, remote sensing, and modeling techniques. Participants include EPA's
EMSL-LV, ERL-D, and LLRS (Large Lake Research Station, Grosse He, MI), NASA/AMES,
NOAA Great Lakes Environmental Research Laboratory (GLERL), and Michigan State University
(MSU).
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2. BACKGROUND
The EPA's Environmental Monitoring and Assessment Program (EMAP) is an interagency multimedia
effort to address the condition of the Nation's ecological resources. EMAP objectives are to identify
the associations between human-induced stressors and adverse effects on ecosystems, and to compile
statistical summaries and interpretive reports on the Nations' overall ecological condition to the
Administration and the public. One part of EMAP's focus is to link collection of new environmental
data with existing programs at regional and national scales over a time frame of several decades. The
EMAP-LC (landscape characterization) component is providing the foundation on which to estimate
the current status and trends of ecological resources, in defined regions with known accuracy. Threats
to ecosystems, such as global climate change, acidic deposition, point and nonpoint source pollution,
ozone depletion, and loss of habitat all point to the need to compile a connected nationwide CIS
database. Over time, the EMAP database will expand and be employed to evaluate impacts of policy,
facilitate future planning, and uncover ecosystem trends.
EMAP-LC efforts are currently underway at EMSL-LV for the Chesapeake Bay Watershed and are
tentatively scheduled to start in the Great Lakes Basin in FY93. The product of EMAP-LC is to
generate a land cover/use (LC/LU) database with a minimum map unit of 1 hectare which is derived
from satellite collected remotely sensed data (Landsat TM). EMAP-LC Level 3 is the expected
classification detail obtainable from Landsat Thematic Mapper (TM) imagery being employed in
EMAP-LC. Appendix B contains a description of the EMAP-LC Classification System. This
classification system is the result of cooperative efforts between EPA's EMAP Program and NOAA's
C-MAP Program (Coastwatch).
Geographic areas which contain variable or specialized characteristics often require a higher level of
mapping detail than the EMAP-LC Level 3 product to generate baseline information to adequately
meet the needs of ecological process studies, in particular the narrow coastal wetlands. The level of
detail required for Great Lakes coastal wetland regulation, habitat inventories, nonpoint watershed
analyses, and some ecosystem process studies is approximately 0.2 - 0.4 hectare, much higher than
the EMAP-LC 1 hectare mapping unit.
The Great Lakes are the largest freshwater lake system in the world and contain approximately one-
fifth of the earth's available fresh surface water. The five Great Lakes - Superior, Michigan, Huron,
Erie, and Ontario - with their interconnecting channels and Lake St. Clair have a total water surface
area of 246,050 sq. kilometers (95,000 sq. miles) and drain a land area of 524,480 sq. kilometers
(202,500 sq. miles). All or part of eight U.S. States and portions of two Canadian provinces drain
into the Great Lakes as the lakes form a series of immense freshwater reservoirs connected by rivers
in a staircase fashion. Figure 1 is a false color composite of the Great Lakes Basin acquired by an
Advanced Very High Resolution Radiometer (AVHRR) aboard one of NOAA's polor orbiting
satellites.
The Great Lakes Basin is an ecologically sensitive area containing a variety of wetlands (palustrine,
riverine, lacustrine) and has over 6,110 kilometers (3,800 mi) of coastline. Erosion potential and
rates are significant along portions of the Great Lakes shoreline, and the topic attracts wide-spread
public attention with land value estimates in these areas exceeding 15 billion dollars (USACE, 1988).
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Great Lakes Watershed
AVHRR composite
Sept 14 Sept 27, 1990
Kilometers
0 100 200 3OO
data provided by EROS Data Center
Mi •
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Erosion rates are influenced by the orientation of the shoreline upon which the forces of nature
impact, bathymetry, and wave hydrodynamics (USAGE, 1988). The National Shoreline Study of
1971 is the last Great Lakes systemwide U.S. shoreline inventory and characterization completed by
the Corps of Engineers.
A need exists to perform a Great Lakes characterization with emphasis toward wetlands, terrestrial
habitats, and freshwater ecosystem processes. Most federal and state agencies in the region have
mapping programs, but are usually specialized and designed to meet specific agency mandates.
Therefore, the problem with the current resource mapping efforts is lack of consistency in terms of:
1) source information, 2) spatial resolution, 3) analysis methodology, 4) classification system, 5)
quality assurance/quality control (QA/QC), 6) thematic and geometric accuracy, 7) database format,
and 8) update schedules. To perform a Great Lakes basin habitat inventory, wetlands mapping, or
freshwater ecosystem modeling with data currently available is not feasible because information and
results from the regional agencies are not comparable or compatible.
3. OBJECTIVE DESCRIPTIONS
OBJECTIVE 1 - DATA COLLECTION AND DATABASE DEVELOPMENT
DATA COLLECTION
FY91 - Green Bay and Saginaw Bay
The remotely sensed data obtained in FY91 for Green Bay and Saginaw Bay are from three sources:
Landsat Thematic Mapper (TM) satellite (25 meter); EPA EMSL-LV (Aerocommander 690) airborne
Multispectral Scanner (MSS) (10 meter); and NASA/AMES (ER-2) airborne Thematic Mapper
Simulator (TMS) (25 meter). Refer to figures 2 and 3 for location, date, and type of data collected
over the pilot locations. See Appendix A for specifications regarding the various platforms and
sensors.
In addition to aircraft and satellite data, limited water quality samples were collected June 1991 in
southern Green Bay (figure 4). The samples were collected by the Green Bay Metropolitan Sewerage
District (GBMSD) as a courtesy to UW-M. The data for each sample include: lat/long via LORAN,
time, station depth, secchi depth, Ph, temperature, conductivity, and dissolved oxygen. GBMSD also
filtered samples for dissolved/total nutrient analysis and chlorophyll determinations. This information
is available through the Center for Great Lakes Studies at the University of Wisconsin- Milwaukee.
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Landsat TM
Path 24/Row 29
25 meter resolution
June 11,1991
EPAMSS/DS-1260
10 Meter Resolution
June 27,1991
NASATMS/DS-1268
25 meter resolution
June 4,1991
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tiesomi-aund
Figure 2. GLEPP Multisensor Data Collection:
Green Bay, Wl
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Landsat TM
Path 21 /Row 30
25 meter resolution
August 9,1991
EPAMSS/DS-1260
10 Meter Resolution
July?, 1991
NASATMS/DS-1268
25 meter resolution
June 4,1991
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Lake
Huron
1165GR91-3amd
Figure 3. GLEPP Multisensor Data Collection:
Saginaw Bay, Ml
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10 15
Figure 4. Map of southern Green Bay showing water quality
sampling locations - June 1991.
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FY92 - Green Bav Only
EPA EMSL-LV aircraft MSS data is scheduled for repeat collection over Green Bay June 3-14,1992.
NASA/AMES aircraft equipped with a Daedalus Airborne Ocean Color Imager (AOCI) will obtain
digital imagery concurrently with EPA data collection. If NASA's Airborne Visible/Infrared Imaging
Spectrometer (AVIRIS) is available, it will also be aboard NASA's aircraft and collect data in 224
spectral bands with 20 meter resolution. Precise flight line configuration and data collection
parameters will be determined at future project coordination meetings. Focus of this acquisition will
be an intensive data collection effort to supplement development of freshwater process modeling
emphasizing origin-transport-fate linkages. The TM and MSS data support terrestrial parameter
identification for origin and transport scenarios, while the AOCI and water quality sampling data
support the aquatic linkages to complete the cycle process.
Water quality data collection will be conducted during the same time period in June 1992.
Participants include the EPA Saginaw Field Office research vessel, the University of Wisconsin-
Milwaukee research vessel, and the County Health Department vessel. Measurements will be
acquired twice daily to record diurnal and circulation effects in the bay, with specific parameters for
sampling include but are not limited to: lat/long via GPS (global positioning system) or LORAN,
time, station depth, secchi depth, Ph, temperature, conductivity, chlorophyll-a, dissolved oxygen, and
selected metals and nutrients. Refer to figure 5 for approximate sampling locations of the three
vessels.
DIGITAL DATA ANALYSIS
LANDSAT Thematic Mapper (TM)
One full scene of digital Landsat TM imagery was acquired for each pilot site and will be mapped by
EPA EMSL-LV for land cover according to EMAP-LC Level 3 classification scheme (Appendix B).
TM data for Green Bay (Path 24/Row 29) was obtained for June 11,1991, and for Saginaw Bay (Path
21/Row 30) for August 9,1991. The TM data is georeferenced by Hughes STX Corporation for the
distributor EOSAT, to within sub-pixel registration accuracy and simultaneously resampled to an
output resolution of 25 meters. Subset areas of the TM scenes based on U.S.G.S. Hydrologic Units
will be extracted and classified initially. Under the Database Evaluation portion of this project
however, the hydrology based subsets will be further reduced to specific counties to coincide with
U.S.G.S. National Wetlands Inventory (NWI) update information. For the Development of Sampling
Fiames portion of GLEPP, the land cover derived from Landsat TM for the available hydrologic units
will be employed. The use of a dataset based on hydrologic boundaries (even if only administrative)
for modeling processes is more sensible, however some areas containing wetland categories will not
be derived from high-resolution aircraft data or NWI update information but rather TM analysis.
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Collection
University of
Wisconsin
Collection Area
SJurgeon
Bay
Lake
Michigan
Green Bay
County
Health
Dept.
Collection
Area
Location
of Study
Area
Sable
Point
Figure 5. Green Bay FY 92 proposed water quality data
collection locations.
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Aircraft Multisoectral Scanner (MSS)
EPA aircraft MSS data collected with simultaneous color-infrared (CIR) photography was obtained
along a portion of the western shoreline of Green Bay on June 27,1991, and along most the shoreline
in Saginaw Bay on July 7,1991. The data collection included the use of a mid-infrared sensor (1.55-
1.75 micrometers), which is extremely useful for vegetation mapping. The resolution of the imagery
is approximately 10 meters with the corresponding CIR photography at a scale of 1:26,000.
The aircraft MSS imagery will be analyzed by USAGE-WES for detailed shoreline wetland delineation
and substrate identification to be used in development of erosion potential factors. The highest level
of classification detail obtainable from the imagery will be mapped at a minimum map unit of
approximately 0.2 hectare and be compatible with the EMAP-LC classification system. See Appendix
B for a description of the EMAP-LC classification, which expands the wetlands category at higher
levels.
Thematic Mapper Simulator (TMS)
NASA/AMES aircraft TMS data were collected with simultaneous color photography across the Green
Bay and Saginaw Bay waterbodies on June 5, 1991. These flights were conducted with a high-gain
thermal band (8.5 -14.0 micrometers) employed to record temperature differences in the water. The
TMS data was obtained with a 25 meter resolution cell. The TMS imagery will be analyzed by
NASA/AMES Ecosystem Science and Technology Branch with emphasis placed on the thermal band
for temperature, sediment plumes, and suspended solids identification. Focus of NASA's overall
participation in GLEPP is to supplement their Freshwater Initiative for modeling freshwater ecosystem
processes, particularly for global (climate) change. NASA's analysis results will also be used to aid
in the development of an open water sampling frame for FY92 Green Bay data collection.
FY92 DATABASE DEVELOPMENT
EPA EMSL-LV and NASA/AMES will coordinate the distribution of the multistage digital data to
the participating evaluators and ecosystem modelers.
Bathymetry
A bathymetric layer in the LC/LU and shoreline wetland CIS would be useful in development of
process models. The National Ocean Service Hydrographic Data Base (NOSHBD) provides extensive
bathymetric data in the Great Lakes. This database includes all depth values obtained during
surveying which produces more detailed bathymetric information than what is obtained through
digitization of published nautical charts.
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Green Bay
NOSHBD bathymetric data has been ordered for Green Bay and will be compiled into a CIS layer
either as contours or cell values.
Saginaw Bay
In 1986, NOS performed a hydrographic survey in Saginaw Bay at the request of MDNR. Five
profiles (transects) were done in the same locations as prior surveys (1930's) with no significant
differences noted in bathymetry. The hydrographic information was digitized and bathymetry created
with a one meter contour interval by MDNR. The Saginaw Bay bathymetry was obtained from
USACE-Detroit in an ARC/Info exchange format (IGDS) and will be available as a line coverage at
1 meter intervals (contours).
Digital Elevation Models (DEM)
Digital elevation files were acquired from the U.S.G.S. for the Green Bay Pilot Site and will be
ordered for the Saginaw Bay site. The data consists of a regular array of elevation values referenced
with a spacing of 3-arc seconds (one degree blocks in a Lat/Lon coordinate system). These data are
not rectangular, but follow the arc of the earth's latitude and longitude lines. Arc/second data are
often referred to by the number of seconds in each pixel. This data is produced by the Defense
Mapping Agency (DMA) from digitization of 1:250,000 topographic maps. Arc/second data used in
conjunction with other image data, such as TM, must be rectified, or projected onto a planar
coordinate system. EMSL-LV has in-house algorithms to project these files into UTM coordinates.
Several parameters can then be generated from DEM data after such transformations, e.g., contours,
slope, aspect. These data layers are useful in modeling flow direction.
Green Bay Database Development
A four county area (Oconto, Brown, Calumet, and western Manitowoc) will be mapped to EMAP-LC
Level 3 from Landsat TM data with a minimum map unit of approximately one hectare. See figure
6 for map location of the Green Bay database evaluation pilot site. This land cover will be coupled
with a higher resolution shoreline wetland component (0.2 ha.) for portions of Brown and Oconto
counties derived from EPA EMSL-LV Aircraft MSS imagery processed by US ACE-WES. Updated
NWI data (ARC/INFO format) is to be provided to EMSL-LV for three counties (excluding Oconto
which is unavailable until FY93) by WDNR under an Interagency Agreement (IAG) with EPA Region
5. Green Bay historical (1982) and recent (1990) wetland extent, as mapped by the State of
Wisconsin for the NWI, will be obtained for available counties and used to evaluate the MSS detailed
wetland delineation. Data processing of the TM and aircraft MSS began October 1991 and is
scheduled for completion by February 1992. The distribution of the Green Bay CIS is expected in
late April 1992 with EPA EMSL-LV and NASA-AMES coordinating the effort.
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sconsm
1165GR91-6amd
Figure 6. Green Bay study area undergoing land cover mapping.
Detailed shoreline wetlands mapping in Oconto and Brown Counties.
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Saeinaw Bav Database Development
A three county area (Bay, Saginaw, and western Tuscola) will be mapped similarly to Green Bay at
a EMAP-LC Level 3 with incorporation of the higher resolution MSS wetland data processed by
USACE-WES. See figure 7 for map location of the Saginaw pilot site. Updated NWI data
(ARC/INFO format) will be provided for the three county area by the U.S. Fish and Wildlife Service
(USFWS) Region 3. Data processing (TM, MSS, NWI) is scheduled to begin March 1992 and be
completed by May 1992. This pilot may be expanded to include 85% of the Saginaw Bay Watershed
(6,000 sq. mi.) with Landsat TM imagery as the source information for deriving land cover. If the
expanded area is included for characterization, the delivery date of the database will be adjusted
accordingly.
OBJECTIVE 2 - DATABASE EVALUATION
The multi-resolution LC/LU, detailed wetlands, and thermal database will be evaluated for usefulness
in several federal and state programs. Focus will be placed on regulatory functions, habitat
inventories, and watershed non-point pollution monitoring.
Clean Water Act. Section 404:
Lead Investigators:
Doug Ehorn, EPA Region 5
Mark Graves USACE-WES
Participants:
Ronald Erickson, USF&WS Region 3
Scott Housman/Lois Stoerzer, WDNR
Federal and state agencies charged with enforcement of Section 404 of the Clean Water Act, which
authorizes the discharge of dredged or fill materials into the waters of the United States, are
responsible for making jurisdictional determinations of wetlands and issuance/denial of permits.
Typically these agencies rely on aerial photography and site visits to perform their evaluations, which
can create a backlog of permittees' who must wait for an official response to find out if the site
contains wetlands, and if so, what type of changes or mediation is acceptable. A basin-wide database
containing timely and consistent wetlands information, compiled from high resolution remotely sensed
data, would have incalculable use not only for federal and state regulators, but also local zoning
commissions and the public (realtors, commercial and private properties, etc.)
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Michigan
UMOmi-Thnd
Figure. 7. Saginaw Bay study area undergoing land cover and
detailed shoreline wetlands mapping.
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Clean Water Act. Section 303:
Lead Investigator:
Thomas Davenport, EPA Region 5
Participants:
William Richardson, EPA LLRL
Section 303 addresses water quality standards and implementation plans. NPDES (National Pollutant
Discharge Elimination System) is structured for point source discharges with TMDL (Total Maximum
Daily Loads) identified. However, the pilot study locations are located within freshwater bay
watersheds which need database support for development of spatial non-point pollution models. The
CIS would support these efforts by supplying data layers for bathymetry, LC/LU, detailed wetlands,
and thermal patterns. The CIS provides basic information layers in which additional information,
particularly land cover and digital elevation, could support a non-point source modeling effort in the
watersheds. The use of land cover as an indicator for origin of certain types of toxins (pesticides,
nutrients, etc.), can be coupled with transport models that include other components such as digital
elevation, soils, climatic data, and hydrologic routing to quantify the sediment and nutrient loadings
occurring in these bays.
Habitat Inventories
Lead Investigator:
Steve Hedtke, EPA ERL-D
Participants:
Frank Horvath, MDNR
EPA's 5 Year Strategic Plan for the Great Lakes is identifying new habitat evaluation goals and have
been given a priority equal to traditional toxics control. While expanding its role in habitat
inventories, EPA recognizes the need to coordinate efforts with other agencies in collection of habitat
variable information. Terrestrial habitat inventories have not historically received the same attention
as water and wetland habitats, but the linkages between all three need to be addressed to quantify the
effects of terrestrial disturbances, i.e., fire, landslides, erosion, deforestation, and agricultural,
industrial and domestic pollution.
Non-point Source Watershed Modeling
Lead Investigator:
Robert Beltran, EPA GLNPO
Participants:
William Richardson, EPA LLRL
A basin-wide monitoring plan is being developed by EPA's Great Lakes National Program Office
(GLNPO) utilizing results from the Green Bay Mass Balance Study (GBMBS) conducted 1989-91.
The GBMBS focused the efforts of several federal agencies and the States of Wisconsin and Michigan
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to develop an extensive ambient water column, sediment, and loadings database for lower Green Bay
and significant tributaries. This data collection effort looked at conventual parameters as well as
others such as PCB, dieldrin, metals, nutrients, and chlorophyll-a, for the basis of developing a mass
balance model. The GBMBS database will be available to GLEPP modelers during summer 1992,
and should be in an ARC/Info compatible format. The GLNPO monitoring plan is a multi-agency
effort in FY92 to outline a basinwide core monitoring program to enable regional agencies to avoid
unneeded monitoring exercises by identifying more useful schedules and protocols. Future freshwater
ecosystem process studies may wish to incorporate the key parameters identified and collected by this
effort.
Non-point Source Toxics Modeling
Lead Investigator:
Thomas Davenport, EPA Region 5
Participants:
William Richardson, EPA LLRL
Water quality data collection in Green Bay in FY92 will acquire selected toxins samples for this
effort. The field collected data will help validate results obtained in modeling efforts for non-point
source identification. Because the origin of nutrients and contaminants are strongly influenced by the
land cover/use in the surrounding watershed, determination of whether relationships exist between
toxic compounds and productivity is necessary to model the aquatic ecosystem. This type of
information would be useful in understanding the degree to which photosynthesis is inhibited in areas
where high concentrations of toxic compounds are present.
OBJECTIVE 3 - DEVELOP SAMPLING FRAME(S) FROM BASELINE DATA
The TM landcover, MSS detailed wetlands, TMS thermal, elevation, and bathymetry data layers will
be utilized through CIS to develop a sampling frame(s) and perform initial modeling simulations.
A need exists to refine those remote sensing capabilities which are suited or designed to obtain
measurements in aquatic systems, lakes, rivers, and coastal zones/bays. The greater spectral
variability of upwelling radiance from freshwater systems, as well as the often short-lived duration
of many of the key phenomena, must be factored into the future design of aircraft and sensors.
Defining the key parameters believed to be part of the radiance signal and radiative transfer theory
involves separating them into those which involve radiance interactions in the surface waters and those
which describe the scattering and additive path radiance in the atmosphere. The two components,
surface and atmospheric effects, require sensors and calibration refinements to adequately quantify
the imagery that is digitally obtained.
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Efforts should also be made to acquire data from emerging new high spectral resolution systems to
supplement aquatic ecosystem studies in order to identify current capabilities and to specify future
sensing requirements. Existing aircraft sensors, such as NASA's AOCI and AVIRIS systems, EPA's
MSS and fluorescence imaging systems, as well as commercial satellite data, require further
investigations focused at incorporating a combination of experimental sampling techniques to derive
reliable relationships.
OBJECTIVE 4 - PERFORM FRESHWATER ECOSYSTEM PROCESS STUDIES
Freshwater ecosystem process studies will be performed in Green Bay, Wisconsin and Saginaw Bay,
Michigan, in FY92 and FY93 respectively. Simultaneous collection of satellite, aircraft, and field
data is scheduled for June 3-14, 1992 in Green Bay, Wisconsin. The location and parameters for
water quality sampling by EPA, UW-M, and the Wisconsin Department of Health will be optimized
under the Sampling Frame Development Objective.
The GLEPP studies will focus on origin-transport-fate of nutrients and toxins as related to
chlorophyll-a productivity within the bays. In-situ sampling parameters will include but are not
limited to: thermal measurement, suspended solids, turbidity, dissolved organic material (DOM),
chlorophyll-a, nitrogen, phosphorus, plankton counts, and selected metals.
The development of aquatic process models explicitly driven by variables derived from remotely
sensed data need to couple the physical circulation processes with biological processes such as
photosynthesis, nutrient cycling, and sedimentation. Existing models should be explored which have
both a three dimensional capability and a time resolution that is appropriate to remote observation of
key variables.
Aquatic process models need to be coupled with terrestrial ecosystem processes, i.e., origin-transport-
fate. NASA-AMES has developed coupled models which describe the carbon, nitrogen, and water
interactions in forest ecosystems using remotely sensed data and has tested them for several years on
a regional scale. These forest processes have then been coupled to hydrologic models which describe
the downslope movement of soil moisture, giving predictions of the disturbed soil moisture and
hydrographs of forested watersheds. NASA has plans to couple these models with geochemical
models to predict water yield from catchments and stream chemistry. Eventually, these models could
be tied to the aquatic process models developed in GLEPP, and be applied to regional studies to
describe interactions between terrestrial processes such as land-cover change and the effects on the
downstream receiving aquatic systems.
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The following subheadings identify proposed areas under investigation for ecosystem process
modeling. The lead investigator(s) and participants are listed.
Aquatic Process Modeling
Lead Investigator:
Arthur Brooks and David Bolgrien, UW-Milwaukee
Participants: EPA's GLNPO, ERL-D, LLRS, NASA-AMES, NOAA GLERL
The aquatic process modeling will be based on chlorophyll-a concentrations as a surrogate measure
of productivity. Planning and preliminary ecosystem process modeling activities would utilize the
compiled baseline CIS data in development of an appropriate sampling frame(s). The pilot study
databases in CIS form will facilitate sample frame development for spatial modeling efforts.
To obtain an understanding of freshwater processes, such as nutrient mixing, thermal stratification,
and sedimentation, a mixture of field measurement and monitoring, remotely sensed data, and
predictive simulation is required. Important processes occurring in aquatic environments such as
nutrient cycling and productivity, support using in-situ monitoring/measurement and remote sensing
of key waterbody parameters in which to drive the mechanistic models.
Water Surface Temperature Mapping
Lead Investigator:
George Leshkevich, NOAA-GLERL
Participants:
David Bolgrien, UW-Milwaukee Center for Great Lakes Study
Emphasis is directed toward the daily and diurnal spatial dynamics of temperature and turbidity within
Green Bay. The NOAA Great Lakes Environmental Research Laboratory (GLERL) as part of the
Agency's COASTWATCH Program provides daily color coded temperature maps derived from
AVHRR for the Great Lakes. GLEPP participants can utilize NOAA's database which contains in
addition to twice-daily AVHRR processed temperature maps; visible/infrared information for snow/ice
delineation and lake buoy information. These data are mapped to a Mercator projection and
resampled to a 512 X 512 pixel grid. NOAA provides access to the data via INTERNET or phone
modem and supplies public domain processing software for PC or Macintosh platforms.
The findings within this effort will help direct the methods employed to study thermal dynamics in
greater detail from the higher spectral/spatial/temporal resolution data being acquired by EMSL-LV
and NASA-AMES.
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Water Quality Data Collection
Lead Investigator:
Wayne Willford, EPA Region 5
Participants:
UW-CGLS, Arthur Brooks (chlorophyll-A, plankton counts)
NASA/AMES, David Peterson (suspended sediments, light transmission)
NASA/AMES, Roy Armstrong (DOM using AVIRIS)
EPA-EMSL, Ross Lunetta (coordination)
Field data to be collected includes:
Nutrients: dissolved/total nutrient analysiswhich includes but is not limited to: chlorophyll, total
organic carbon, bicarbonate, sulfate, nitrite, nitrate, silica, and chloride.
Toxics: suite of toxic compounds to be determined by EPA Region 5.
Physical: geographic location, surface temperature, sechhi depth, current velocity, turbidity, total
suspended solids, and Ph.
The high spectral resolution AVIRIS imagery (if collected June 1992) will be analyzed in coastal
waters, particularly near river plumes, to resolve the dissolved organic material (DOM) signal from
upwelling spectral radiance.
Water Circulation Modeling
Lead Investigator:
Allen Bratkovich, NOAA-GLERL
Participants:
U-W Milwaukee, Arthur Brooks and David Bolgrien
Hydrodynamic studies are important for modeling the mixing and transport processes of the pilot sites,
Green Bay and Saginaw Bay. The shallow depths and constricted nature of the sites reduce mixing
and exchange with the main lake body. The use of temperature and current data allows for these bays
to be subdivided into smaller units which may serve different functions. Circulation patterns help
provide for better modeling of the transport, dispersal, and fate of terrestrial inputs and resulting
water quality trends in different locations.
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Freshwater Wetland Stress Detection
Lead Investigator:
Roy Armstrong.NASA-Ames (AVIRIS)
Participants:
US ACE-WES, Mark Graves (aircraft MSS)
UW-Green Bay, Tom Erdman (wetlands ground truth)
High-spectral resolution data has been used successfully to assess plant canopy biochemical
constituents (e.g. nitrogen and chlorophyll) and trace metal stress. Airborne and satellite high-spectral
resolution sensors could play a significant role as monitoring tools in years to come. The existing
remote sensing data, acquired in June 1991, will be used to select the study areas based on the large-
scale patterns of temperature and turbidity. Development of spectral indices to quantify the response
of wetland vegetation to both positive (sewage effluent) and negative (heavy metal toxicity) stresses
could provide a mechanism for the early detection of wetland vegetation response to environmental
stress and for identifying nonpoint pollution sources.
Should AVIRIS data be collection June 1992, further study of the response of wetland vegetation to
point and non-point source pollution using high spectral resolution data (223 bands) could begin.
AVIRIS data would be acquired over known pollution sources as well as over areas showing strong
gradients in water temperature and turbidity.
Light Attenuation in Freshwater Bays
Lead Investigator:
Karen Lee, EPA EMSL-LV
Participants:
Mike Spanner, NASA Ames
Environmental perturbations, resulting in reduction of light availability for plant photosynthesis, have
been related to several marine aquatic plant declines. Agriculture and urbanization practices leading
to changes in sediment runoff and nutrient loadings, alters water quality which affects the abundance
of aquatic plants. Models have been developed in marine environments which relate instantaneous
photosynthetic responses to light availability and provides a means of relating changes in light
attenuation in the water to changes in seagrass productivity and depth penetration. The light available
to plants for photosynthesis (Photosynthetically Active Radiation is 400-700 nanometers) is
approximately the visible wavelengths. Typically secchi disk is used to estimate light attenuation in
clear waters, however with the availability of photoelectric light meters, these measurements of
underwater light fields in turbid or anaerobic waters become more accurate than Secchi depth.
Conversion factors between Secchi depth and a light attenuation coefficient (k) were originally
developed for clear ocean waters and more recently formulated for various estuaries. Organic detritus
can attenuate light both as paniculate and dissolved matter resulting in Secchi depth measurements
for these portions of the water column becoming suspect. Simultaneous measurements of Secchi depth
and light attenuation need to be performed for unique waterbodies in order to develop accurate
conversion factors. Minimum light requirements for particular aquatic plants can be determined ere
the maximum depth limit and light attenuation coefficient are measured simultaneously.
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GREAT LAKES ECOLOGICAL PROCESS PILOTS
Study Participants
Project Leads:
Co-Principal Investigator EPA/EMSL:
Co-Principal Investigator NASA/AMES:
Ross Lunetta
David Peterson
Ecological Process Research:
Co-Investigator UW/GLRI:
Co-Investigator NOAA/GLERL:
Co-Investigator NOAA/GLERL:
Co-Investigator EPA EMSL-LV:
Co-Investigator NASA/Ames:
Co-Investigator NASA/Ames:
Arthur Brooks/David Bolgrien
George Leshkevich
Allen Bratkovich
Karen Lee
Roy Armstrong
Mike Spanner
Regulatory, Watershed Analysis, & Environmental Monitoring:
Lead Investigator EPA Region 5:
Lead Investigator EPA Region 5:
Lead Investigator EPA/ERL-D:
Lead Investigator EPA/LLRS:
Lead Investigator EPA/GLNPO:
Lead Investigator USACE/WES:
Lead Investigator USFWS Region 3:
Lead Investigator MDNR:
Lead Investigator WDNR:
Lead Investigator MSU:
Doug Ehorn
Thomas Davenport
Steve Hedtke
William Richardson
Robert Beltran
Mark Graves
Ronald Erickson
Frank Horvath
Scott Housman/Lois Stoerzer
Jon Bartholic
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GREAT LAKES ECOLOGICAL PROCESS PILOTS
Meeting Schedule
2/92 Ecological Process Research Investigators Coordination
EPA EMSL-Las Vegas Executive Conference Room
February 5, 1992 8:30 - 4:00
February 6, 1992 8:30 - 12:00
Optional Spatial Analysis Laboratory Tour 1:30 - 3:00
MEETING AGENDA
* Review FY91 data collection results
* Review ecological process study topics
* Formalize investigator research roles
4/92 Green Bay Ecological Process Research Coordination
* Establish final FY92 data collection logistics
* Meeting location - TBD
5/92 Regulatory, Watershed Analysis & Environmental Monitoring
Investigators Coordination
* Present Green Bay LC/LU database to investigators
* Formalize investigator evaluation topics
* Establish evaluation reporting objectives
* Meeting location - Chicago: Region 5 or GLNPO
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GREAT LAKES ECOLOGICAL PROCESS PILOTS
Study Schedule
6/91 Remote sensing data collected: Green Bay and Saginaw Bay.
EPA Aero-690: Daedalus 1260 MSS (10 m)/9" CIR (1:26,000)
NASA ER-2: Daedalus 1268 MSS (25 m)
1/92 Green Bay LC/LU, detailed shoreline wetlands, and thermal
analysis complete.
4/92 Green Bay LU/LU database available for regulatory, habitat,
watershed, and environmental monitoring evaluations.
4/92 Green Bay ecological process sampling frame development.
6/92 Green Bay ecological process study data collection.
6/92 Saginaw Bay LC/LU database available for evaluation.
6/93 Saginaw Bay ecological process study data collection.
FY92 Project Budget
EPA EMSL-LV $ 10OK
EPA ERL-D 10OK
EPA Region 5 100K
NASA/AMES In-kind
USACE-WES 3OK
$ 330K
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APPENDIX A
SENSOR / PLATFORM DESCRIPTIONS
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NOAA SATELLITES
NOAA currently has three operational polar-orbiting weather
satellites (NOAA-10, NOAA-11 and NOAA-12) which each carry (among
other sensors) the Advanced Very High Resolution Radiometer
(AVHRR). The polar-orbiting satellites are in a sun synchronous
orbit at an altitude of approximately 1500 km. Each satellite
passes over a given area twice daily. The AVHRR scans a swath
width of approximately 2700 km on the earth;s surface beneath the
satellite in five radiometric bands, one visible (0.58-0.68 nm) ,
one reflected infrared (0.725-1.0 nm), and three thermal infrared
(3.55-3.93, 10.3-11.3, and 11.5-12.5 nm) . The AVHRR data are
processed at two resolutions, 4 km Global Area Coverage (GAC) and
1 km Local Area Coverage (LAC) and High Resolution Picture
Transmission (HRPT). These data are transmitted from satellite
receiving stations to NESDIS facilities where they are calibrated,
earth located, quality controlled, and made available in a form
called AVHRR Level IB. The LAC data are used for Great Lakes
Coastwatch imagery.
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LANDSAT SATELLITES
EOSAT Company
4300 Forbes Blvd.
Lanham, MD 20706
1-800-344-9933
Data Characteristics of LANDSAT 4 and 5
As a result of the Land Remote Sensing Commercialization Act of
1984, Landsat data are currently acquired, processed, and
distributed by EOSAT Company under a cooperative agreement with
NOAA and the USGS. Users must sign a form when acquiring data
stating they will not copy or distribute the data without
authorization from EOSAT.
Radiometric: Data are scaled to pixel dynamic ranges of 0-256 for
TM and 0-127 for MSS, and compensated for detector gain and offset
changes.
Geometric: Data are compensated for earth rotation, spacecraft
altitude, attitude and sensor variations. (Note: data is not
rectified to a coordinate system, geocoded products are available) .
Scale/Resolution:
TM approximately 30 meters with thermal band 6 at 120 meters
MSS approximately 80 meters
Spectral Sensitivity of the TM and MSS Sensors
TM data - 7 bands wavelength
Band 1 - blue 0.45-0.52
Band 2 - green 0.52-0.60
Band 3 - red 0.63-0.69
Band 4 - near IR 0.76-0.90
Band 5 - near IR 1.55-1.75
Band 6 - thermal IR 10.4-12.5
Band 7 - mid IR 2.08-2.35
micrometers
MSS data - 4 bands
Band 1
Band 2
Band 3
Band 4
green
red
near IR
near IR
wavelength
0.5-0.6 micrometers
0.6-0.7
0.7-0.8
0.8-1.1
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EPA-BNVTRONMENTAL MONITORING SYSTEMS LABORATORY
AIRBORNE MULTISPECTRAL SCANNER (MSB)
Environmental Monitoring Systems Laboratory, Las Vegas (EMSL-LV)
Ross S. Lunetta, Remote Sensing Manager
(702) 798-2175
EMSL-LVs scanner system is a Daedalus Enterprises Model 1260
instrument. This system uses a rotating mirror to direct radiated
energy from a spot on the Earth's surface onto sensing detectors.
Energy is focused on sensors with a telescope assembly, and is
split into spectral components by a prism and a dichroic mirror.
The Daedalus 1260 is an 11-band system with a sensitivity range
from 0.3 to 14 micrometers (ultraviolet though thermal infrared).
In addition, simultaneous aerial photography can be collected with
a Wild RC-8 metric mapping camera.
Geometric control is greatly improved over past missions (FY91)
with the use of Global Positioning System (GPS) technology, with
a single receiver (autonomous mode) RMS accuracies of fixes are
approximately 25 meters unless the Air Force invokes intentional
system degradations called "selective availability" (SA), in which
case accuracies degrade to approximately 100 meters. However, if
a second GPS receiver simultaneously acquires data at a known
location, then "differential corrections" can be applied that
improve accuracies to approximately 5 meters, whether SA is in
effect or not. GPS fixes are acquired by an onboard GPS receiver
and logged on a small computer. The fixes include latitude,
longitude, and altitude information which is made more accurate
later when differential corrections are applied. The fixes also
include precise information about the clock time when the fixes
were taken. This is critical because it takes time for the
receiver to report its fix to the computer, and the aircraft has
moved an appreciable distance in that time. The recorded times are
used later during data reduction. The sequence of precise times
and positions from the GPS fixes, and the scan line time are used
to interpolate scan-center position and heading. This allows
accurate compensation for changes in heading, mispositioning left
or right of the scan line, and changes in altitude. In addition to
knowing aircraft position, heading and altitude, scan line by scan
line, it is important to understand the terrain below. Height
above terrain is critical to scanner geometry, as is variation in
terrain elevation across the scan line. Digital elevation models
(DEM) from the USGS are placed into mosaics covering the mission
area, and are used by the geometric correction software.
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EPA-BNVIRONMENTAL MONITORING SYSTEMS LABORATORY
AIRBORNE MULTISPECTRAL SCANNER (MSB)
Spectral Sensitivity of the Daedalus DS-1260
Channel 1
Channel 2
Channel 3
Channel 4
Channel 5
Channel 6
Channel 7
Channel 8
Channel 9
Channel 10
Near Ultraviolet
Blue
Blue
Green
Green
Red
Red
Near Infrared
Near Infrared
Mid Infrared
0.38-0.42 micrometers
0.42-0.45
0.45-0.50
0.50-0.55
0.55-0.60
0.60-0.65
0.65-0.79
0.80-0.89
0.92-1.10
1.50-1.75
Either one of two thermal detectors can be employed
Channel 11 Thermal Infrared (InSb) 3.00-5.00 or
8.00-14.0
(MCT)
MSS sensor/aircraft parameters
IFOV
Ground resolution
Total scan angle
Pixels/scanline
Scan rate
2.5 mrad
Approximately 2.2 m per 1000 m of AGL
90 degrees (45 each side of nadir)
715 (740 following rectification)
10, 20, 40, or 100 scans/sec
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NASA AMES RESEARCH CENTER
MOFFET FIELD, CALIFORNIA
The Airborne Science and Applications Program (ASAP) is supported
by three ER-2 high altitude Earth Resources Survey aircraft. These
aircraft are operated by the High Altitude Missions Branch at NASA
Ames Research Center. The ER-2's are used as readily deployable
high altitude sensor platforms to collect remote sensing and in
situ data on earth resources, celestial phenomena, atmospheric
dynamics, and oceanic processes. Additionally, these aircraft are
used for electronic sensor research and development and satellite
investigative support. High resolution mapping cameras and digital
multispectral imaging sensors are used in a variety of
configurations in the ER-2s four pressurized equipment
compartments.
Daedalus Thematic Mapper Simulator - TMS
The TMS simulates the performance of the Landsat 4 and 5 earth
resource satellites by replicating the spectral characteristics of
the seven Landsat Thematic Mapper (TM) bands. Four additional
spectral bands of discrete wavelengths are also acquired by the TMS
while TM band 6 (thermal data) is acquired as two bands in low gain
and high gain settings.
TMS Spectral Sensitivity
Daedalus Channel
1 Blue
2 Blue
3 Green
4 Red
5 Red
6 Near Infrared
7 Near Infrared
8 Near Infrared
9 Near Infrared
10 Mid Infrared
11 Thermal Infrared
12 Thermal Infrared
TM Band
1
2
5
7
6 low gain
6 high gain
Wavelength
0.42-0.45 micrometers
0.45-0.52
0.52-0.60
0.60-0.62
0.63-0.69
0.69-0.75
0.76-0.90
0.91-1.05
1.55-1.75
2.08-2.35
8.50-14.0
8.50-14.0
TMS sensor/aircraft parameters
IFOV
Ground resolution
Total scan angle
Swath width
Pixels/scanline
Scan rate
Aircraft velocity
1.3 mrad
81 ft (25 m at 65,000 ft)
43 degrees
8.3 n. mi. (15.4 km at 65,000 ft)
716 (750 following rectification)
12.5 scans/sec
400 kts (206 m/sec)
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NASA AMES RESEARCH CENTER
NOFFET FIELD, CALIFORNIA
Daedalus Airborne Ocean Color Imaaer fAOCIl
The NASA Daedalus multispectral scanner also can be configured as
an Airborne Ocean Imager (AOCI) simulating the spectral
characteristics of the proposed second generation instrument to
follow the Coastal Zone Color Scanner (CZCS) on board the Nimbus
satellite. Designed for high altitude oceanographic remote
sensing, the AOCI provides 10-bit digitization of eight bands of
the visible spectrum with two additional bands of 8-bit
digitization in the near and thermal infrared portions of the
spectrum. Flown at 65,000 feet aboard the ER-2 aircraft, the AOCI
provides a readily deployable platform for study of coastal,
estuarine, and oceanic processes.
AOCI Spectral Sensitivity
Daedalus Channel
1 Blue
2 Blue
3 Green
4 Green
5 Red
6 Red
7 Infrared
8 Reflected Infrared
9 Reflected Infrared
10 Thermal Infrared
Wavelength
0.436-0.455 micrometers
0.481-0.501
0.511-0.531
0.554-0.575
0.610-0.631
0.655-0.676
0.741-0.800
0.831-0.897
0.989-1.054
8.423-12.279
AOCI sensor/aircraft parameters
IFOV
Ground resolution
Total scan angle
Swath width
Pixels/scanline
Scan rate
Aircraft velocity
2.5 mrad
163 ft (50 m at 65,000 ft)
85 degrees
18 n. mi. (33.3 km at 65,000 ft)
716 (750 following rectification)
6.25 scans/sec
390 kts (200 m/sec)
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NASA AMES RESEARCH CENTER
MOFFET FIELD, CALIFORNIA
Airborne Visible and Infrared Imaging Spectrometer - AVIRIS
The Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) is
the second the series of imaging spectrometers instruments
developed at the Jet Propulsion Laboratory (JPL) for earth remote
sensing. This instrument uses scanning optics and four-line arrays
of detectors to image a 614 pixel swath width simultaneously in 224
contiguous spectral bands (0.4-2.4 micrometers). All AVIRIS data
Is decommutated and archived at JPL and not currently available for
public distribution. For further information contact Rob Greene at
Jet Propulsion Laboratory, 4800 Oak Grove Drive, MS 11-116,
Pasadena, CA 91109-8099.
AVIRIS Spectral Sensitivity
Spectrometer
l
2
3
4
Wavelength Range
(micrometers)
0.41-0.70
0.68-1.27
1.25-1.86
1.84-2.45
# of bands
31
63
63
63
Sampling Interval
(nanometers)
9.4
9.4
9.7
9.7
AVIRIS sensor/aircraft parameters
IFOV
GIFOV (at 20 km)
FOV
GFOV (at 20 km)
Spectral coverage
Number of spectral bands
Digitization
Data Rate
1.0 mrad
20 meters
30 degrees
11 km
0.41-2.45 micrometers
224
10 bits
17 MBPS
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APPENDIX B
EMAP Landscape Characterization
Chesapeake Bay Pilot Project
Classification System
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EMAP Landscape Characterization
Chesapeake Bay Pilot Project
Classification System
In today's complex world, legislators, planners, and State and
local governmental officials need to know the extent of land cover
and land use. This knowledge helps them make informed decisions
about the management and use of land resources. To do this,
officials require an ecologically oriented land cover
classification system progresses strictly from land cover in the
lower levels to integrating land cover and land use in the higher
levels. This classification system must be consistent with the
needs of several different levels of government agencies.
An ecologically oriented classification system was developed for
use in current land cover mapping projects of several government
agencies. The classification scheme was developed by the
Environmental Protection Agency's (EPA's) Environmental Monitoring
Systems Laboratory - Las Vegas, Nevada (EMSL-LV); United States
Geological Survey (USGS); United States Fish and Wildlife Service -
National Wetlands Inventory (USFWS-NWI); National Oceanic and
Atmospheric Administration (NOAA); NOAA - National Marine Fisheries
Service (NMFS); University of Delaware; Oak Ridge National
Laboratory; Salisbury State University; and the Florida Department
of Natural Resources.
This classification system is appropriate for ecological
monitoring; it fulfills the needs of the various agencies involved
in the decision making process regarding land cover and land use
issues. This ecologically oriented classification system contains
major portions of or completely encompasses several existing
nationwide classification systems.
The classification system developed is different from the
hierarchial structure of existing systems. The existing systems
contain different levels of data, with each higher level containing
a greater amount of land cover and land use detail expanding
eventually to specific species or usage.
The classification system imitates the hierarchial structure of
other classification systems. The classification system is
ecologically oriented, progressing from land cover on the lower
levels to land use on the higher levels. Each level depends on the
ability of the remote sensing sensors in existence today to
distinguish land cover classes. The lower levels in the
classification system correspond to information that can be
obtained from satellite imagery. The higher levels correspond to
information that can be obtained from aerial photography and field
work. The user may add classes to the higher levels in the system,
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i.e., Level 5, or may completely add a new higher level depending
on the user's needs. The information in the higher levels can
easily be aggregated down to a lower less detailed level. Each
successive level of data in the classification system contains more
detailed information than the one below it. Although different
remote sensing platforms helped in the creation of the
classification scheme, the sensors can not be mutually and
exclusively be assigned to a particular level in the scheme.
Level One in the classification system is an organizational level
that helps orient the user to begin the classification of a
particular area of interest. The Level Two categories would be the
first categories added into a classification system database.
Level Two roughly corresponds to information that can be collected
from the NOAA - Advanced Very High Resolution Radiometer (AVHRR)
satellite. This satellite acquires ground coverage at a resolution
of l.l kilometers at the nadir and has five spectral bands.
The information contained in Level Three of the classification
system roughly corresponds to the information that is obtained from
the Landsat Thematic Mapper (TM) satellite. This satellite has a
ground resolution of 28.5 meters and seven spectral bands. Level
Four in the classification system, represents the level of
information that can be determined with the French Systeme Pour
1'Observation de la Terre, SPOT, satellite. The satellite has a 10
meter ground resolution in panchromatic and 20 meters for multi-
spectral (4 bands) acquisitions. spot is also capable of
collecting stereo pairs of imagery. Level Five in the
classification system contains all the information collected from
the use of aerial photography, and through the inclusion of other
ancillary data layers.
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Upland
1.0 Developed
a
3D
2.0 Cultivated Land
EMAP - CHESAPEAKE BAY CLASSIFICATION SYSTEM
(Modification of NOAA CoastWatch Land Cover Classification)
11-21-91
Level 3
New Scheme
Level 4
LevelS
1.1 Solid Cover (High Intensity) 1.11 Residential
1.12 Commercial
1.13 Industrial
1.14 Transportation, Communications, & Utilities
1.2 Mixed Pixels (Low Intensity) 1.21 Residential
1.22 Commercial
1.23 Industrial
1.24 Transportation, Communications, & Utilities
1.25 Rural Development
2.1 Woody
2.2 Herbaceous
2.11 Orchards/Groves
2.12 Vine/Bush
2.21 Cropland
2.211 Row Crop
2.212 Cover Crop
G
39
3.0 Herbaceous (Grassland)
3.1 Herbaceous
3.11 Unmanaged
3.12 Managed
3.111 Rangeland
3.121 Groomed (yards, cemeteries, parks, etc.)
3.122 Ungroomed (ski areas, roadsides, etc.)
3.123 Pasture
4.0 Woody
4.1 Deciduous
4.2 Mixed
4.3 Evergreen
4.11 Forest
4.12 Shrub
4.21 Forest
4.22 Shrub
4.31 Forest
4.32 Shrub
4.33 Succulent
-------
Level 1 Level 2
5.0 Exposed Land
Levei3
S.I Soil
5.2 Sand
5.3 Rock
5.4 Evaporite Deposits
Level 4
5.11 Soil
5.21 Sand
5.31 Solid
5.32 Unconsolidated
5.41 Evaporite Deposits
LevdS
5.211 Beaches
5.212 Sand Dunes
5.213 Other Sandy Areas
5.311 Natural
5.312 Quarries/Mines
5.321 Natural
5.322 Quarries/Mines
6.0 Snow & Ice
6.1 Snow & Ice
Wetland
7.0 Woody Wetland
8.0 Herbaceous Wetland
7.1 Deciduous
7.2 Mixed
7.3 Evergreen
8.1 Herbaceous
6.11 Snow
6.12 Ice
6.13 Glacier
7.11 Saltwater Forest
7.12 Freshwater Forest
7.13 Saltwater Scrub/Shrub
7.14 Freshwater Scrub/Shrub
7.21 Saltwater Forest
7.22 Freshwater Forest
7.23 Saltwater Scrub/Shrub
7.24 Freshwater Scrub/Shrub
7.31 Saltwater Forest
7.32 Freshwater Forest
7.33 Saltwater Scrub/Shrub
7.34 Freshwater Scrub/Shrub
8.11 Emergent (Marsh)
8.12 Aquatic Bed
O
33
9.0 Non-Vegetated Wetland 9.1 Non-Vegetated
9.11 Non-Vegetated
-------
Level 1 Level 2 Level 3 Level 4 Level S
Water and Submerged Land
10.0 Water 10.1 Shallow Water 10.10 Saltwater Hard Bottom *
10.11 Saltwater Rock Bottom *
10.12 Saltwater Unconsolidated Bottom *
10.13 Saltwater Aquatic Vegetation *
10.14 Saltwater Reef *
10.15 Saltwater Shellfish Bed *
10.16 Freshwater Hard Bottom *
10.17 Freshwater Rock Bottom *
10.18 Freshwater Unconsolidated Bottom *
10.19 Freshwater Aquatic Vegetation *
10.2 Deepwater 10.20 Saltwater Hard Bottom *
10.21 Saltwater Rock Bottom *
10.22 Saltwater Unconsolidated Bottom *
10.23 Saltwater Aquatic Vegetation *
10.24 Saltwater Reef *
10.25 Saltwater Shellfish Bed *
10.26 Freshwater Hard Bottom *
10.27 Freshwater Rock Bottom *
10.28 Freshwater Unconsolidated Bottom *
10.29 Freshwater Aquatic Vegetation *
NOTE: * Marine, Estuarine. Lacustrine, Palustrine, and Riverine are Modifiers of the Water categories.
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D&AFT
GLEPP Technical Work Plan Distribution List
Joseph Abe
John Anagnost
Ray Armstrong
Jon Bartholic
Dick Bauer
Robert Beltran
Matt Bills
Lou Blume
Allen Bratkovick
John Brazner
Arthur Brooks/Dave Bolgrien
Dale Bryson
Earl Cosby
Ron Carlson
Ford Cross
Tom Davenport
Tudor Davies
Jerome Dobson
Doug Ehorn
Chris Elvidge
Tom Erdman
Ron Erickson
Randolph Ferguson
Jim Galloway
Roger Gauthier
Jim Giattina
I.W. Ginsberg
Mark Graves
Chris Grundler
F. Henry Habict II
Steve Hedtke
Mason Hewitt
Homer Hilner
Ken Holtje
Frank Horvath
Scott Housman/Lois stoerzer
Eric Hyatt
Lucinda Johnson
Bruce Jones
Bill Keith
Frederic Kopfler
Rick Kutz
George Leshkevich
Thomas Lillesand
Thomas Mace
Ann Maclean
Jeanette Marsh
John Meagher
Gene Meier
Romy Myszka
Bruce Newton
EPA OPPE
EPA Region 5 (312)886-0143
NASA AMES
MSU IWR (517)353-3742
EPA Region 5 (312)353-2000
EPA GLNPO (312)353-0826
EPA OMMSQA
EPA Region 5 (312)353-6148
NOAA GLERL
UW Limnology (608)262-3088
UW CGLS (414)649-3028
EPA Region 5 (312)353-2147
WI SCS (608)264-5341
EPA ERL-D (FTS)780-5523
NOAA Coastwatch (919)728-3595
EPA Region 5 (312)353-2000
EPA OWP
Oak Ridge Nat'l Lab
EPA Region 5 (312)353-2308
EPA OEPER
UW Green Bay (414)465-2713
FWS Region 3 (FTS)725-3417
NOAA Coastwatch (919)728-5523
USAGE Detroit (313)226-6760
USAGE Detroit (313)226-3054
EPA GLNPO (312)353-2000
ERIM (313)994-1200
USAGE WES (601)634-2557
EPA GLNPO (312)353-2117
EPA Deputy Administrator
EPA ERL-D (FTS)780-5610
EPA EMSL-LV (702)798-2377
MI SCS
USFS (FTS)362-4125
MDNR (517)373-3457
WDNR (608)226-8852
EPA AREAL-ORD (919)541-0673
UM NRRI (218)720-4251
EPA EMSL-LV (702)798-2671
EPA OMMSQA
EPA GMPO (FTS)494-2712
EPA OMMSQA
NOAA GLERL (313)668-2265
UW Madison
EPA ORIM
MTU Houghton (906)487-2030
EPA Region 5 (301)353-2000
EPA OWD
EPA EMSL-LV (702)798-2235
EPA GLNPO (301)353-8034
EPA AWPD (FTS)382-7074
38
DRAFT
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DRAFT
Doug Norton
Thomas Parris
John Paul
Gareth Pearson
Dave Peterson
Ann Pilli
Pranas Pranckevicius
Jack Puzak
Bill Richardson
Courtney Riordan
Dave Rockwell
N. Philip Ross
Bill Sanvilie
Steve Schilling
John Schneider
Barbara Scudder
Terry Slonecker
Janet Smith
Mike Spanner
Bill Steltz
Nelson Thomas
Gil Veith
Wayne Willford
Bob Worrest
Robert Wrigley
Bill Wyland
EPA EPIC (FTS)557-3110
CIESIN (202)775-6608
EPA ERL-N (FTS)838-6037
EPA EMSL-LV
NASA AMES (FTS)464-5899
EPA ERL-D
EPA GLNPO (312)353-3437
EPA OMMSQA
EPA LLRS (FTS)378-7611
EPA OEPER
EPA GLNPO
EPA OPPE
EPA ERL-D (FTS)780-5723
EPA OIRM
EPA Region 5 (312)353-2000
USGS Madison (608)274-3535
EPA EPIC (FTS)557-3110
USFWS Green Bay
NASA AMES (FTS)464-3620
EPA OMMSQA
EPA ERL-D
EPA ERL-D
EPA GLNPO (312)353-1369
EPA OEPER
NASA AMES
FWS NWI (FTS)921-2201
39
DRAFT
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