United States Office of EPA/620/R-93/008
Environmental Protection Research and Development March1993
Agency Washington, DC 20460
Evaluation of
EMAP-Wetlands
Sampling Design
Using National
Wetlands Inventory
Data
| Environmental Monitoring and
! Assessment Program
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EPA/620/R-93/008
March 1993
EVALUATION OF EMAP-WETLANDS SAMPLING
DESIGN USING NATIONAL WETLANDS INVENTORY
DATA
by
Nancy C. Leibowitz8
Ted L. Ernstb
N. Scott Urquharf
Steve Stehmand
Denis Roose"
"Oregon Division of State Lands, Salem, OR 97310
bManTech Environmental Technology Inc., US EPA Environmental
Research Laboratory, 200 SW 35th Street, Corvallis, OR 97333
C0regon State University, Statistics Department
Corvallis, OR 97331
dSUNY-Environmental Science and Forestry, The
Faculty of Forestry, Syracuse, NY 13210
'The Bionetics Corporation, Vint Hills Farm Station
Warrenton, VA 22186
Project Officer
Spencer A. Peterson
US Environmental Protection Agency
Environmental Research Laboratory
200 SW 35th Street
Corvallis, OR 97333
Printed on Recycled Paper
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DISCLAIMER
The research in this report has been funded by the United States Environmental Protection Agency
(EPA) under Contracts ft 68-C8-0006 to ManTech Environmental Technology, Inc and Contract # 68-
03-3532 to The Bionetics Corporation. Mention of trade names does not constitute endorsement or
recommendation for use.
This document should be cited as:
Leibowitz, N.C., T.L. Ernst, N.S. Urquhart, S. Stehman, D. Roose. 1993. Evaluation of EMAP-Wetlands
Sampling Design Using National Wetlands Inventory Data. EPA/620/R-93/008 U.S.
Environmental Protection Agency, Environmental Research Laboratory, Corvallis, OR.
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Table of Contents
List of Tables ii
List of Figures iii
Acknowledgements iv
Abstract v
Introduction 1
Methods 3
Precision and Accuracy 12
Quality Assurance 12
Results and Discussion 14
Comparison of EMAP and NWI population data 15
Characterization of the area, size, and wetland classes of the three regions 17
Analysis of size classes of the three regions 17
Assessment of EMAP Design 20
Conclusions 32
Literature Cited 34
Appendix A 35
Database 36
Technical Challenges with Polygon Enumerations 36
Appendix B 38
Assigning EMAP Hydrologic Locators 39
Coding Limitations 39
Old NWI Water Regimes 42
NWI Mixed Wetland Classes 42
Other Notes 42
Appendix C 43
Appendix D 56
Appendix E 68
Appendix F 74
Appendix G 82
Appendix H 92
Appendix I 94
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List of Tables
Table 1. Proposed EMAP classification system for reporting wetland condition for the
continental United States and corresponding classes in The Classification of Wetlands
and Deepwater Habitats of the United States (Cowardin et al. 1979) 10
Table 2. EMAP Wetland Code Description 11
Table 3. Percentages of the number and areas of wetlands for each EMAP class for each of
the three regions 17
Table 4. Sample estimates for number and areas of wetlands by EMAP class for the Illinois
region 22
Table 5. Sample estimates for number and areas of wetlands by EMAP class for the
Washington region 24
Table 6. Sample estimates for number and areas of wetlands by EMAP class for the Prairie
Pothole region 26
Table 7. Sample estimates by size class for the Illinois region 28
Table 8. Sample estimates by size class for the Washington region 29
Table 9. Sample estimates by size class for the Prairie Pothole region 30
Table C. Summary of NWI classes mapped to each EMAP class for the Illinois Region 44
Table D. Summary of NWI classes mapped to each EMAP class for the Washington Region . . 57
Table E. Summary of NWI classes mapped to each EMAP class for the Prairie Pothole
Region 69
Table F1. Illinois Region. Percentage of tiles and hexagons included in the study 75
Table F2. Washington Region. Percentage of tiles and hexagons included in the study 78
Table F3. Prairie Pothole Region. Percentage of tiles and hexagons included in the study .... 81
Table G1. Changes in the numbers of wetlands when mapping from the NWI level
classification to the EMAP level classification 83
Table G2. Percentages of the number and areas of wetlands for each EMAP class for each of
the three regions. Values reported are percentages based on raw data values 84
Table G3. Population summary by size for each of the regions. Values reported are
percentages based on raw data values 85
Table G4. Sample estimates for number and areas of wetlands by EMAP class for the Illinois
region 86
Table G5. Sample estimates for number and areas of wetlands by EMAP class for the
Washington region 87
Table G6. Sample estimates for number and areas of wetlands by EMAP class for the Prairie
Pothole region 88
Table G7. Sample estimates by size class for the Illinois region 89
Table G8. Sample estimates by size class for the Washington region 90
Table G9. Sample estimates by size class for the Prairie Pothole region 91
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List of Figures
Figure 1. EMAP Grid (not randomized) for North America. Spacing between points is
approximately 27 km (Overton et al. 1991) 4
Figure 2. Example demonstrating placement of the 640 km2 hexagons over a region {in this
case Illinois and the relationship between the 40 km2 hexagons (hexagon number
8786) and the 640 km2 hexagon (tite number 8786) 5
Figure 3. Illinois project area showing the location of the hexagons and ecoregions (Omernik
1987) 7
Figure 4. Washington project area showing the location of the hexagons and ecoregions
(Omernik 1987) 8
Figure 5. Prairie Pothole region project area showing the location of the hexagons and
ecoregions (Mann 1 974) 9
Figure 6. Comparison of the relative differences in wetland polygon numbers and mean areas
of wetland polygons between the NW! level classification and the EMAP level
classification 16
Figure 7. Population summary based on percentage of the number of wetlands in each
region 18
Figure 8. Population summary based on percentage of wetlands surface area in each region . . 19
Figure 9. Scatter plot for the Illinois region relating relative differences, a measure of
accuracy, and CVs, a measure of precision 23
Figure 10. Scatter plot for the Washington region relating relative differences, a measure of
accuracy, and CVs, a measure of precision 25
Figure 11. Scatter plot for the Prairie Pothole region relating relative differences, a measure
of accuracy, and CVs, a measure of precision 27
Figure 12. Comparison of the relative differences between the true population value and the
estimated value for wetland numbers and surface area for several size classes in the
3 regions 31
figure A. Wetlands can be cut by the tile structure in various ways, creating an unpredictable
number of polygons 37
Figure B1. Relationship between a hexagon sampling area, its tile and window 40
figure B2. Non-network topology can not distinguish among the situations above 41
HI
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ACKNOWLEDGEMENTS
This project is the result of the combined efforts of many people. The authors would like to sincerely
thank Tony Olson and Doug Norton for financial support, Don Woodard for assignment of staff and a
U.S. Fish and Wildlife Service's National Wetlands Inventory (NWI) computer to this effort, Dan
Bigelow for help in reformatting the data. Bill Wilen, Tom Dahl, Ron Erickson, Howard Bowers, and
Chuck Elliott for providing an accurate NWI perspective, Ann Hairston for technical editing, Mark
Josselyn from the Illinois Natural History Survey for data preparation and conversion to ARC/lnfo and
Kristina Miller and Brenda Huntley for preparing the figures. The authors greatly benefitted from the
critical reviews of Phil Larsen, Tom Dahl, John Montanari and, Deborah Coffey.
IV
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ABSTRACT
The U.S. Environmental Protection Agency initiated the Environmental Monitoring and Assessment
Program (EMAP)-Wetlands {Leibowitz et al. 1991) to monitor the current status and long-term trends
in the condition of the nation's wetlands. To support this effort, an EMAP classification system was
devised by aggregating subclasses of the U.S. Fish and Wildlife Service's National Wetlands Inventory
(NWI) classification system (Cowardin et al. 1 979) to: 1) provide fewer classes per region allowing for
adequate sample sizes per class and, 2) establish distinct boundaries between other EMAP resource
groups. Aggregation of the NWI classification to the EMAP classification system was based on
dominant vegetation cover, flooding regimes, dominant water source, adjacency to rivers and lakes,
and other relevant information. This study evaluates the EMAP classification system and sampling
design using NWI digital wetlands data for portions of Illinois, Washington, North Dakota and South
Dakota. A comparison of the EMAP classification to the NWI classification and evaluation of the EMAP
sampling design were conducted relative to numbers of wetlands, total areas, average areas, and
common versus rare classes. As expected, the EMAP aggregation of NWI data resulted in fewer
wetland polygons, each with larger areas, but did not alter the number of wetlands or the total wetland
area in each region. Summary statistics based on comparisons of the sampling estimates to true
population parameters demonstrated the effectiveness of the EMAP sampling design with the exception
of rare wetland classes. Rare EMAP classes (e.g., saturated palustrine emergents, saturated emergents
along rivers, and saturated forested/scrub-shrub wetlands along rivers), estuarine emergents (e.g.,
coastal salt mashes) and large wetlands (> 50 ha) were usually poorly estimated, but the EMAP design
is readily adapted to provide better estimates for these categories.
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INTRODUCTION
The United States Environmental Protection Agency (EPA) initiated the Environmental Monitoring and
Assessment Program (EMAP)-Wetlands program (Leibowitz et al. 1991) to provide quantitative
assessments of status and trends in the condition of the nation's wetlands on both regional and
national scales. Program objectives include the following:
Estimate the current status, trends and changes in selected indicators of the condition of the
Nation's ecological resources on a regional basis with known confidence.
Estimate the geographic coverage and extent of the Nation's ecological resources with known
confidence.
Seek associations between selected indicators of natural and anthropogenic stresses and
indicators of the condition of ecological resources.
Provide annual statistical summaries and periodic assessments of the Nation's ecological
resources.
EMAP-Wetlands will meet these objectives by developing and evaluating the following elements:
A sampling strategy which provides unbiased probability estimates of wetland condition with
known precision and accuracy for national and regional scales of resolution:
Indicators that describe and quantify wetland condition:
Techniques and a conceptual framework to analyze the data collected so that results
accurately represent a regional wetland population's condition relative to regional reference
sites, models, available literature, and expert judgement.
This evaluation of the EMAP classification system and statistical design is part of the overall planning
to meet long range program objectives. The program objectives depend on the development of a
statistical design and sampling frame for selecting and monitoring wetlands. The EMAP sampling
design has been developed to provide unbiased probability estimates of both current resource condition
and long-term trends with known precision for national and regional scales of resolution. The design
is based on a systematic triangular point grid randomly located over the conterminous United States
(Overton et al. 1991). A wetlands sampling frame, built upon the EMAP design, provides a list of
functionally distinct wetlands which could be selected for field visits. Development of a wetlands
sampling frame depends on several criteria: 1) the availability of spatial data including the distribution
and extent of wetlands, 2) provide coverage for the entire region, 3) an accurate representation of the
wetlands resource, and 4) the wetland classification system used should allow transformation to the
EMAP classification scheme. The most appropriate data source for developing the EMAP-Wetlands
sampling frame is the U.S. Fish and Wildlife Service's National Wetlands Inventory (NWI) wetland
maps, which cover 73% of the nation's wetland resources, of which 14% have been digitized (Wilen,
1990).
The goal of this study is to quantitatively assess the EMAP classification system and the statistical
sampling design using regionally representative NWI digital data sets. The specific objectives of the
project are to:
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Compare the EMAP classification to the NWI classification relative to
- numbers of identified wetland polygons
- total surface areas of wetlands
- average surface areas of wetlands
- common versus rare classes, and
- minimum mapping unit
Evaluate the EMAP design at the base EMAP grid density of 27 km between sampling points
and compare the hexagon samples to the population values for the parameters listed above.
Compare the design and classification across three regions: Upper Mississippi drainage area
represented by Illinois; the Pacific Northwest represented by Washington; and the Upper
Midwest Prairie Pothole region represented by North and South Dakota.
Discuss the feasibility of using NWI digital map data for generating an EMAP-Wetlands
sampling frame.
This study provides EMAP personnel and other regional scientists and managers engaged in sampling
and assessment efforts using digital data sets with evaluations of the EMAP classification and
statistical design for both regional and inter-regional scales. The EMAP approach for completing a
comprehensive regional program is discussed in terms of how accurately the classification system
represents the NWI population of wetlands, how closely the sample data represent the population data
for each region, and how problems encountered in the sampling design and classification system can
be corrected so that data are comparable across regions. The resulting database will require only field
verification before use as the basis for wetland classification and sample selection in region-wide
monitoring efforts in Illinois, Washington, and parts of North and South Dakota.
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METHODS
This study evaluates an inter-regional comparison of wetland characteristics and landscape attributes
related to the overall EMAP design. The design 1) considers three areas of the country, 2) achieves
a representative sample for comparative purposes, and 3) distributes samples geographically across
several ecoregions (Omernik 1987).
The status of digital wetlands information was assessed during an informal workshop in October 1990
in Warrenton, Virginia with participants from EPA, EPA contractors, and NWI personnel (see Appendix
H for a list of participants). The available data sets were discussed and ranked in relation to the
following criteria: 1) age of photography used to create digital wetland coverages, 2) detail of wetland
classification (Cowardin et al. 1979) mapped, and 3) regional representation and unique features of
wetlands in selected areas. The consensus was to use the regional digital data sets which postdated
1979.
Wetlands data for this study were mapped and digitized by the NWI Program (Wilen, 1990). Dates of
aerial photography used for the three regions included 1980 to 1987 for Illinois, 1980 to 1984 for
Washington state, and 1979 for North and South Dakota. Each digital 7.5' NWI quadrangle map
included the coverages of all linear and polygon wetlands coded using the Cowardin system {Cowardin
et al. 1979). The mapping was executed using primarily color infrared photography at a scale of
1:58,000-1:65,000 for the states of Illinois, North Dakota, and South Dakota and 4% black and white
photography (1:80,000) and 96% color infra-red (CIR) at a scale of 1:58,000 for the state of
Washington. Wetlands attribute data collected for the statistical analysis include surface area and
number of wetlands for both the regional wetland populations and samples for each NWI and EMAP
class. All wetlands, including dot, linear, and polygons, had been assigned surface area values
according to NWI photointerpretation and cartographic standards (U.S Fish and Wildlife Service 1990a
and 1990b). Linear wetlands were considered the domain of other EMAP resource groups. Linear
wetlands were used in this study to assign qualifiers indicating the wetland was associated with a
riverine system. For this study, existing NWI digital wetlands data were used to define the mapped
wetland populations to be sampled. In the future, EMAP will attempt to confirm the accuracy of the
mapped wetland classification on a subset of the NWI wetlands data during field reconnaissance and
sampling operations.
The digital data include portions of Illinois, Washington, North Dakota and South Dakota. The Illinois
data represents inland wetlands with a broad range of flooded water regimes, primarily situated in
floodplains with a smaller population of wetlands associated with isolated basins. The Washington data
represents the West Coast environment with extreme diversity in water regimes and habitats, ranging
from desert, wet and dry floodplains, isolated wetland basins, to estuarine resources. All EMAP
classes are represented. The North and South Dakota data represents the Prairie Pothole region
containing a dense population of very small (<1.0 ha) wetlands set in an agricultural landscape.
Evaluation of both the EMAP classification system and sampling design necessitates bounding of the
regional populations, and extracting a representative sample within each region. The initial step in the
EMAP sampling design is to place a large hexagon containing a triangular grid of sampling points
approximately 27 km apart over North America (See Figure 1). The wetland population domain is
defined by overlaying adjacent, 640 km2 hexagons, centered on the sampling points, on the available
digital information. Sample data are extracted from 40 km2 hexagons also centered on the same
sampling points of each 640 km2 hexagon in the selected regions. The sample data therefore,
represent one sixteenth of the area of the population (Overton et al. 1991) (See Figure 2).
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The distribution of each region's population of 640 km2 hexagons (referred to here also as tiles) was
selected to intersect with as many ecoregions (Omernik 1 987) or subregions (Mann 1 974) as possible.
Analysis of the Illinois data included 99 tiles distributed across five ecoregions (Figure 3). The
Washington data included 97 tiles distributed across five ecoregions (Figure 4). The Prairie Pothole
wetlands data included 36 tiles spread across three subregions (Figure 5).
Aggregating the NWI classification system into an EMAP classification system was proposed by
Leibowitz et al. (1991) for the purpose of: 1) limiting the number of wetlands classes to less than 20
classes per region to allow for adequate sample sizes per class and, 2) establish distinct and logical
boundaries between EMAP wetlands classes and other EMAP resource groups. NWI classifies wetlands
into ecologically distinct wetland classes using aerial photographs, vegetation cover types, geomorphic
settings and, flooding regimes (Cowardin et al. 1979). The EMAP classification system aggregates
NWI classes into wetland classes characterized by dominant vegetation cover, dominant water sources,
e.g., lake, river, basin, estuar" or marine and flooding regime (See Table 1).
Specialized geographic information systems (CIS) programs were developed by the Environmental
Photographic Interpretation Center (EPIC in Warrenton, Virginia) to automate the conversion of NWI
wetland polygons into EMAP wetland polygons and to generate the sample and population data (see
Appendices A and B for further discussion). CIS algorithms were developed to automate the receding
of the Cowardin (NWI) wetland classes into the EMAP classification (Roose and Stout, 1992). The
receding portion of the program performs the following four functions:
1) Splits the full Cowardin code into its hierarchical components and recognizes the
components germane to the EMAP classes,
2) Aggregates functionally similar NWI codes into EMAP codes,
3) Identifies wetlands adjacent to riverine and lacustrine systems which approximate the
dominant water source and assigns special hydrologic location codes (see Appendix B
for a discussion of the technical challenges associated with the EMAP coding),
4) Combines the coded results of the two previous steps into an EMAP code. (Descriptions of
the EMAP codes for the 16 EMAP wetlands classes are listed in Table 2).
Once the EMAP coding is established, the associated wetland characteristics for the EMAP and NWI
polygons, including both number and size characteristics, are generated for both the 640 km2 hexagons
and 40 km2 hexagons. Surface areas of individual wetlands are automatically generated by ARC/lnfo
version 5.0.1 software (Environmental Systems Research Institute, Redlands, California). To prevent
double counting, wetland polygons cut by the tile boundaries are tagged to exclude them from any
individual wetland size analyses (e.g., average size), but not from total area calculations. See Roose
and Stout, 1992, for details on how the associated wetland characteristics were generated.
The data manipulations described yield wetland data with the appropriate wetland polygon numbers
and surface areas for each EMAP class. Wetlands attributes are extracted from a single CIS layer of
wetlands data so that both NWI and EMAP codes are present and identified. This occasionally resulted
in identical contiguous EMAP coded wetland polygons. Therefore, a new CIS layer is created to merge
all contiguous polygons with identical EMAP codes, and the attributes were recalculated. As expected
this new coverage included fewer, but larger, functionally distinct EMAP wetlands polygons.
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Table 1. Proposed EMAP classification system for reporting wetland condition for the continental
United States and corresponding classes in The Classification of Wetlands and Deepwater
Habitats of the United States (Cowardin et al. 1979)
EMAP Class'
Cowardin Class
Palustrine
Lake Edge
Palustrine
Basin
Palustrine
River Edge
Estuarine
Vegetation
Shallows
Emergent
Forested/Scrub-Shrub
Emergent
Forested/Scrub-Shrub
Emergent
Forested/ Scrub-Shrub
Palustrine emergent, forested or scrub-shrub
wetland adjacent to lacustrine system (limnetic or
littoral subsystem)
Palustrine unconsolidated bottom, aquatic bed,
unconsolidated shore
Palustrine emergent wetlands
Palustrine forest and scrub-shrub wetlands
Palustrine emergent wetlands adjacent to all
riverine subsystems (except intermittent)
Palustrine forest and scrub-shrub wetlands
adjacent to all riverine subsystems (except
intermittent)
Estuarine emergent wetlands
Estuarine forested and scrub-shrub wetlands
' Most classes will be monitored for temporary flooded, saturated, and seasonal-permanent flooded
water regimes as defined in the Classification of Wetlands and Deepwater Habitats of the United States
(Cowardin et al. 1979).
10
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Table 2. EMAP Wetland Code Description
EMAP CODE DESCRIPTION
E2EM Estuarine Emergent
E2FO/SS Estuarine Forest and Scrub-Shrub
PEMAR Palustrine Emergent - Temporarily flooded adjacent to a perennial riverine system
PEMA Palustrine Emergent - Temporarily flooded
PEMBR Palustrine Emergent - Saturated adjacent to a perennial riverine system
PEMB Palustrine Emergent - Saturated
PEMCR Palustrine Emergent - Seasonally flooded adjacent to a perennial riverine system
PEMC Palustrine Emergent - Seasonally flooded
PFO/SSAR Palustrine Forested and Scrub-Shrub - Temporarily flooded adjacent to a perennial
riverine system
PFO/SSA Palustrine Forested and Scrub-Shrub - Temporarily flooded
PFO/SSBR Palustrine Forested and Scrub-Shrub - Saturated adjacent to a perennial riverine system
PFO/SSB Palustrine Forested and Scrub-Shrub - Saturated
PFO/SSCR Palustrine Forested and Scrub-Shrub - Seasonally flooded adjacent to a perennial
riverine system
PFO/SSC Palustrine Forested and Scrub-Shrub - Seasonally flooded
PL Palustrine vegetation adjacent to lacustrine system
PS Palustrine Shallows
11
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An "expansion factor" is applied to the 640 km2 hexagons and 40 km2 hexagons to compensate for hexagons
that are only partially represented (Appendix F provides tables for each of the regions showing the percentage
of each hexagon included in the study). Partial hexagons result from boundary lines (extent of NWI digital
data) cutting through the interior of a hexagon rather than following the perimeter. The expansion factor is
determined by calculating the inverse of the proportion of the hexagon:
1
EXPANSION FACTOR =
PROPORTION OF HEXAGON
The wetland attribute is multiplied by the expansion factor to estimate the attribute value as if the entire
hexagon had been included in the study. The 640 km2 hexagons and 40 km2 hexagons are treated separately.
For example: Suppose only 60% of a 640 km2 hexagon and 10% of a 40 km2 hexagon were included in the
study. Then the number and area of the wetlands in the entire 640 km2 hexagon would be multiplied by
1.67 = (1/0.60) but by 10 = (1/0.10) for wetlands in the 40 km2 hexagon. Appendix G contains tables with
entries based on the raw data values before application of the expansion factor correction.
Precision and Accuracy
For the purpose of this report we use the distinction between precision and accuracy presented in Cochran
(1977). Accuracy refers to the magnitude of deviations from a population mean. Precision is reserved for
describing the magnitude of deviations from a sampling mean. For example, the relative difference is a
measure of accuracy. Relative difference measures the proportional difference between the known population
value and an estimate of that value obtained by sampling. The coefficient of variation (CV) on the other hand,
is the ratio between the standard error of an estimate and the estimate and therefore considered a measure
of precision.
Quality Assurance
The NWI program was designed to estimate total acreage and change in total acreage for each wetland type
within 10% of the true values with 90% probability (Frayer et al. 1983). The NWI staff performed both
manual and automated quality control checks at various stages of their map efforts {Wilen 1990; U.S. Fish and
Wildlife 1990a and 1990b). Wilen (1990) states that seven steps are necessary to produce final NWI maps:
1) preliminary field investigations, 2) interpretation of high altitude photographs, 3) review of existing wetlands
information, 4) regional and national consistency quality control of interpreted photos, 5) draft map production,
6) interagency review of draft maps, and 7) final map production. Two studies (Swartwout, 1982; Crowley
et al, 1988) show that the maps are greater than 90% accurate. Wilen attributes this level of accuracy to the
combination of field studies, photointerpretation, use of existing information and interagency review of draft
maps. The digitized map data for this study was derived from the NWI maps by NWI personnel. Cross-
comparisons were made to ensure that the digitized information was consistent with the NWI map information.
Quality assurance issues related to the generation of EMAP-coded wetlands from the NWI-coded wetlands can
be found in Appendices A and B. Issues such as double-counting wetlands cut by tile boundaries and
assignment of riverine and lacustrine locators to wetlands influenced by riverine and lacustrine system external
to a particular hexagon are discussed.
Data analysis was performed on two data sets for each region (see Appendix I for a description): 1) the COD
data set contained coverages that retained the integrity of NWI polygons and relabeled polygons with the
EMAP codes, and 2) the ECO data set which contained coverages that aggregated contiguous polygons with
identical EMAP class codes (i.e., dissolved coincident boundaries between like classes). After generating the
12
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EMAP codes from the NW1 codes the results were checked to be sure that the NWI classes were successfully
aggregated into the correct EMAP class. If not then the reason was ascertained and adjustments to the EMAP
coding algorithms were made.
The data quality was verified and validated prior to analysis to check for errors associated with data generation
or data transfer. A check was made to ensure that the hexagons for the NWI-coded data and the EMAP-coded
data was consistent. Hexagons not contained in both data sets were not included in the analysis. The
procedures used to aggregate the NWI data into the EMAP classes should not affect the total surface area in
a hexagon. The data sets were compared to confirm this. A SAS (SAS Institute, Gary, North Carolina)
program was written which checked the number and summed surface areas of each wetland class within each
tile by region. The statistician reviewed this information to identify outliers, or problematic tiles and resulting
information. This review identified several irregularities which were resolved before proceeding with the
analyses. Outliers without any determinable errors were kept in the data sets.
13
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RESULTS AND DISCUSSION
Data analysis for this study consists of two major components. The first component describes and compares
population characteristics in the 99 Illinois tiles, 97 Washington tiles and 36 Prairie Pothole tiles. The data
represent complete populations and thus permit assessing differences among the regional data sets without
considering sampling variability. Complete population data are rarely available in practice. Comparison of the
EMAP and NWI population attributes are based on surface area and number for each wetland class, and
surface area and number of wetland polygons for several size classes for each region.
The second component compares estimates of surface area and number of wetland polygons obtained from
the EMAP 40 km2 hexagon sample data to the known population parameters. The hexagon sample data
represent a single application of the EMAP design. While the statistical properties of the design, which are
based on repeated applications of the sampling strategy, cannot be evaluated from this single sample, a
comparison of the sample estimates to the population parameters provides a quantitative demonstration of the
performance of an EMAP sample for wetlands. Additionally, the data provide information about the numbers
and surface areas of wetlands likely to be obtained from the EMAP design. Results from this analysis will help
when assessing whether there ?re sufficient numbers of wetlands, sampled by the EMAP grid density of one
sampling point per 27 km, to satisfy the precision standards of the design.
Estimates of surface area and number within each wetland class or size class are theoretically unbiased.
Deviations of the sample estimates from the known population parameters reflect the inherent sampling error
of any sampling design. We can determine deviations, both absolute and relative to the true surface area or
number, for the EMAP sample. Estimated precision is reported as the CV for the estimate (standard error of
the estimate divided by the estimate). When considering the EMAP design performance we recognized that
estimates of number and areas of rare wetland classes (defined as comprising less than one percent of the total
wetlands area or less than one percent of the total number of wetlands) would be poor. This is typical of any
sampling program -- characteristics of rare classes are usually estimated with poor precision unless special
design provisions are invoked specifically for improving estimates of rare classes.
Population estimates of both surface area and number of wetlands in any wetland or size class are attainable
from the EMAP sample data. The procedure for estimating any quantity is to multiply the total number or total
surface area of wetlands in the 40 km2 sample within any classification (wetland, size, or combination of
wetland and size class) by 16 (the EMAP 40 km2 hexagon sample represents 1/16 of the total surface area
of the 640 km2 hexagon). From standard sampling theory, these estimates of numbers and surface areas are
unbiased (Cochran 1977).
Because the EMAP sample is a systematic sample, unbiased estimates of precision are not available from a
single systematic sample (Snedecor and Cochran 1980), so variances are approximated. The approximation
assumes the EMAP sample performs as if the 40 km2 hexagons were selected completely at random, rather
than by the systematic spatial pattern used. Thus, this approximation performs well when wetlands are
randomly distributed throughout the region. The more likely scenario though, is a clustered spatial distribution
of wetlands. The variance approximation is inaccurate to the degree that the random distribution assumption
is violated. While 'certain spatial distribution patterns (e.g., wetlands clustered in the landscape) create
problems with variance estimation, such patterns often favor the true precision of the EMAP systematic design
(Overton et al. 1991). The estimated variance overestimates the true variance if wetlands display a clustered
spatial distribution. Thus, a tradeoff characteristic of systematic sampling is likely present - the actual
precision of the design is better than a completely random design, but the estimates of precision do not reflect
the gain in precision actually achieved.
14
-------
Comparison of EMAP and NWI population data
The EMAP classification system aggregates adjacent NWI polygons with either functionally similar NWI codes
(i.e., all vegetated classes next to lakes) or similar water regimes. Thus, the comparison of the EMAP and NWI
population data for the Illinois, Washington, and the Prairie Pothole regions assesses the effect of this
aggregated classification on total number of wetland polygons, total and average areas of wetlands, and rare
and common wetland classes. The EMAP and NWI populations are compared and summarized by number and
average size of wetlands in Figure 6. Aggregations resulted in a decrease of only 4.0% of the wetland polygon
numbers for all the regions combined. Aggregations in Illinois showed a 6.2% decrease in total number of
wetland polygons, the Washington wetland polygon number decreases by 11%, whereas the Prairie Pothole
aggregation decreases the total number of wetland polygons by only 1.9%. The lower decrease in total
wetland polygons reflects the existence of the Prairie Pothole wetlands as single units with fewer being
subdivided in the way of the Illinois and Washington wetlands. Decreases in the number of wetland polygons
following aggregation measures how often adjacent wetland polygons labelled with different NWI codes, were
relabeled with identical EMAP codes. For example, if following aggregation two adjacent polygons had
identical EMAP codes the boundary between them would be dissolved, the areas combined, and the polygon
counted as a single wetland. Therefore, the actual number of wetland polygons based in the NWI classification
would decrease by one but the total wetland surface area would remain unchanged. See Appendices A and
B for greater detail.
Aggregating the NWI classes does not alter the total area of wetlands, since dissolving lines between
functionally similar adjacent NWI polygons does not affect total wetland area. Rgure 6 displays relative
differences between the NWI and EMAP classifications for number and mean area of wetland polygons.
Changes in relative differences in Figure 6 reflect changes in wetland numbers. In Illinois, the largest relative
difference (approximately 50%) in wetland numbers resulted from aggregation of adjacent emergents, forests,
and scrub-shrub around lakes (PL). This decrease in NWI wetland polygons (resulting from aggregating PL
wetlands) is accompanied by a doubling in the mean area of the resultant PL wetlands. Relative differences
for total number of wetland polygons for PFO/SSAR and PFO/SSCR coded wetlands in Illinois are approximately
27% and 16%, respectively. Relative differences from EMAP aggregations of NWI polygons for the remaining
Illinois wetland classes are comparatively small with changes in polygon numbers of less than 12%. Relative
differences resulting from aggregations of adjacent polygons in the Prairie Pothole region are smaller because
the individual, functionally distinct, wetland classes are isolated in the landscape.
Comparison of the NWI coded population with the EMAP coded population functions as an internal check on
the mechanical procedures of the aggregating algorithm. Exact correspondence in numbers might indicate:
1) every wetland polygon was a single separate entity with respect to the NWI classification -- a situation we
knew not to be true or, 2) the ARC/lnfo program for resolving the NWI codes into the EMAP codes was not
dissolving shared boundaries between adjacent identical EMAP coded polygons correctly. Following
aggregation, if the total wetland surface areas of the EMAP coded polygons was not equivalent to the total
surface area of the NWI coded polygons then the aggregating algorithm would again be suspect. Dissolving
shared boundaries between adjacent identical EMAP classes will not alter the total wetlands surface area.
Differences in total wetland surface areas, following aggregation, indicates errors when dissolving the shared
boundaries between adjacent identical EMAP coded polygons or the existence of classes in the NWI
classification lacking a corresponding EMAP class.
15
-------
-ป
b
0
w
ence
i
O 0.0
.1
3
& *-5
-1.0
1.0 n
ง 0.5
ฃ
i
Q 0.0
.1
3
cc
0.5
-0.5
I I
NP NP |~~| NP pi NP NP 1
t2d 1^1 ^
B2J
-1.0
E2EM PEMAR PEMBR PEMCR PFO/SSAR PFO/SSBR PFO/SSCR PL
E2FO/SS PEMA PEMB PEMC PFO/SSA PFO/SSB PFO/SSC PS
Figure 6. Comparison of the relative differences in wetland polygon numbers and mean areas
of wetland polygons between the NWI level classification and the EMAP level
classification. NP=Not present: No wetland polygons were found in the EMAP
level classification.
16
-------
Characterization of the area, size, and wetland classes of the three regions
Wetland populations of the three regions, employing the EMAP classification, are described and compared in
terms of percent composition by numbers and area of wetland polygons and common and rare classes (Table
3). The three regions are distinct in terms of composition of wetlands (this was expected because the regions
were selected to obtain characteristic geographic representation). Illinois wetlands are dominated by palustrine
shallows (PS; 51.4% of total wetland polygons), and seasonally flooded emergents (PEMC; 13.8% of total
wetland polygons). While the PS class in Illinois comprises 51.4% of the wetland population in terms of
numbers, only 10.5% of the total wetland area is PS. This illustrates the importance of representing of
wetlands by both number and area. Washington wetlands are more diverse and biologically variable, with
common classes including seasonally flooded emergents (PEMC), seasonally flooded forest/scrub-shrub along
rivers (PFO/SSCR), seasonally flooded forest/scrub-shrub (PFO/SSC), and palustrine shallows (PS). The Prairie
Pothole region was dominated by emergents, primarily temporally flooded emergents (PEMA) and seasonally
flooded emergents (PEMC). The following EMAP classes are relatively rare throughout the three regions;
saturated emergents (PEMB), saturated emergents along rivers (PEMBR), saturated forest/scrub-shrub along
rivers (PFO/SSBR), and saturated forest/scrub-shrub (PFO/SSB).
Table 3. Percentages of the number and areas of wetlands for each EMAP class for each of the three
regions. NP denotes that the class was not present in the region.
Illinois
Washington
Prairie Pothole
EMAP Class
E2EM
E2FO/SS
PEMAR
PEMA
PEMBR
PEMB
PEMCR
PEMC
PFO/SSAR
PFO/SSA
PFO/SSBR
PFO/SSB
PFO/SSCR
PFO/SSC
PL
PS
%No.
NP
NP
0.8
9.6
0.0
0.1
1.0
13.8
6.3
7.9
0.0
0.0
2.2
5.5
1.6
51.4
%Area
NP
NP
1.1
4.0
0.0
0.2
1.9
8.4
32.3
15.0
0.0
0.0
9.9
8.7
8.0
10.5
%No.
1.8
0.0
1.1
5.3
0.1
0.6
4.8
26.6
4.6
4.7
0.0
0.4
9.9
20.4
1.6
18.1
%Area
6.6
0.0
3.0
5.5
0.0
0.3
8.1
17.3
7.9
5.2
0.0
0.1
16.1
22.4
2.4
5.0
%No.
NP
NP
0.0
45.1
NP
0.0
0.1
46.6
0.0
0.5
NP
NP
0.0
0.2
1.2
6.2
%Area
NP
NP
0.3
34.0
NP
0.0
1.2
53.0
0.1
0.2
NP
NP
0.1
0.1
8.2
2.9
Numbers and surface areas of the dominant NWI classes for each EMAP class in the respective regions are
listed in Appendices C, D, and E.
Analysis of size classes of the three regions
The size class distributions of wetland polygons in each region are described and compared in Figures 7 and
8. Small wetland polygons dominate across all three regions; 73% of Illinois, 62% of Washington and 82%
of the Prairie Pothole region are less than 1.0 ha in size (see Figure 7). But it is important to note
17
-------
80 -
70-
eo-
0)501
co
8
030H
20-
10-
0
Illinois Region
0.0-0.25 0.25-0.5 0.5-1
1-2 2-6 5-10
Size Class in ha
10-25 25-50 50-100 >100
80-
70-
60-
8)501
CO
S 40-
20-
10-
0
I
Washington Region
0.0-0^5 OiSO.5 0.5-1
1-2 2-5 5-10
Size Class in ha
10-25 25-50 50-100 >100
80-
70-
60-
f ป
H 40-
S
ซ30-
20-
10-
n
X^x
yyv'
/Vx>
>oo^
Prairie Pothole Region
'$%
$ t' ^ I Wk I ....
0.0-0.25 0.25-0.5 0.5-1
1-2 2-5 5-10 10-25
Size Class in ha
25-50 50-100 >100
Figure 7. Population summary based on percentage of the number of wetlands in each region.
18
-------
25 -
20 "
o
8*15 -
1
0 10 -
0.
5 -
n
w\ w.
iniiiuia rtcyiwu
m
(
I
!
!
I
I
\
^,
1^1 ki\An
V/A NWI
DEMAP
0.0-0.25 0.25-0.5 0.5-1
1-2 2-5 5-10 10-25
Size Class in ha
25-50
50-100
>100
25 n
Washington Region
Percentage
3 100
25
Prairie Pothole Region
20 -
0
ง15-
E
I-
5 -
n
I
I
\
\
t
!
i
I
I
1,
z
1
0.0-O25 025-05
0.5-1 1-2 2-5 5-10 10-25
Size Class in ha
25-50
50-100
>100
Figure 8. Population summary based on percentage of wetlands surface area in each region.
19
-------
that these small polygons comprise only 10-20% of the wetland area in a region. In Illinois, 60% of the
wetland polygons are less than 0.5 ha in size (see Figure 7), and these comprise 6% of the total wetland area
(see Figure 8). Similarly, in Washington, 44% of the EMAP wetland polygons are less than 0.5 ha in size,
comprising 4% of the wetland area. Prairie Pothole wetland polygons are also predominantly small, 69% are
less than 0.5 ha in size, but comprise only 11 % of the total wetland area in the region. Another interesting
result is that approximately 21 - 24% of the wetland area in both Illinois and the Prairie Pothole region occur
in the size class greater than 100 ha, while only 8% of Washington's wetlands occur in this size class. As
expected, the EMAP aggregations of the NWI data result in a slight shift of the distribution of wetland areas
to the larger size classes.
Figures 7 and 8 also provide information for assessing the effects of establishing minimum mapping unit
standards for the detection of wetlands from aerial photography, satellite imagery or other types of remote
sensing technology. Caution is recommended when evaluating map resolutions (e.g., minimum mapping units).
Most wetlands in these regions are less than 1.0 ha and samples based on minimum mapping units of greater
than 1.0 ha may result in erroneous conclusions by failing to detect the majority of wetlands in a region.
The population analyses reinforce the importance of describing the wetland classification in terms of both
numbers and areas. For example, it is assumed that small wetlands surrounded by intense land uses (i.e.,
agricultural development) will not function or display similar physical and biological attributes as do large
wetlands. In addition, we expect that dryer wetlands are subjected to more intense developmental pressures
than their wetter counterparts. These commonly held assumptions may not be universally true and additional
research is required for substantiation. Thus, when specifying a wetlands sampling design for monitoring
purposes, consideration of both size and numeric attributes is important for representing the important
biological attributes of a wetland.
Assessment of EMAP Design
The EMAP sampling design is evaluated by comparing the number and area of wetland polygons in the 40 krn2
hexagon sample data to the population parameters (number and area in the 640 km2 hexagon). Relative
differences (the ratio of the difference between the estimated value and the population value divided by the
population value), standard errors (SE) and coefficients of variation (CV; ratio of the standard error and the
estimated value) are employed to assess the performance of the statistical design in each region.
The assessment of the EMAP design using a fixed sample is subject to the following limitations:
1) Estimates of wetland classes with small numbers or areas would exhibit low precision.
We expect rare wetland classes to exhibit high variability estimates with larger relative differences
between the true population parameters and the estimated values.
2) The presence of a few wetlands with very large areas may adversely affect precision.
If a rare large wetland was selected in the sample, the resulting estimated total area and the
variability estimate of that class, would be high. In other words, the estimated variance for wetland
area will be high if a few, very large wetlands are present.
20
-------
3) The resulting estimates of population numbers and areas are not independent.
When one parameter is not estimated well neither is the other. Estuarine emergents are not well
estimated using the current design structure. This was expected because of the spatially restricted
distribution of estuarine emergents along the Washington coast; the EMAP sampling plan supports
intensification to allow better estimation of features of this EMAP class.
The EMAP design provides accurate and precise estimates of wetland numbers and areas with the exception
of rare classes (e.g., saturated emergents, PEMB; saturated emergents along rivers, PEMBR; saturated
forest/scrub-shrub along rivers, PFO/SSBR; and saturated forest/scrub-shrub, PFO/SSB (see Tables 4-6 and
Figures 9-11). Relative differences were comparatively low for most EMAP classes (excluding rare classes).
Recall that relative difference is a measure of accuracy. In Figures 9-11, relative difference is displayed along
the abscissa. EMAP classes closest to a vertical line through zero on the abscissa are estimated with the
greatest accuracy. Generally the rare EMAP classes are estimated with less accuracy than common classes.
For example, in Illinois, the relative difference for numbers of PEMA ซ0.01), PEMC (-0.01), PL (-0.03), and
PS (-0.01), were quite good (see Table 4 and Figure 9). In the Prairie Pothole region the results are based on
a very small number of hexagons and therefore, less satisfactory estimates are expected. The existence of
a few large wetland areas among the smaller sized wetlands would result in larger variances and thus less
accurate estimates (see Table 6 and Figure 11).
The CV is a function of the standard error relative to the mean and is a measure of precision. Recall that the
estimated CVs are probably high because of the variance approximation used. The estimated variance
overestimates the true variance if wetlands display a clustered spatial distribution. Figures 9-11 display the
CV along the ordinate axis. The higher a value is along the ordinate axis indicates that the estimate was
measured less precisely than those lower on the axis.
Therefore, EMAP classes clustered closest to the point 0,0 are the most accurate and precise estimates.
Generally, EMAP classes with fewer that 500 wetland polygons were estimated with less precision (CV range:
0.50 to 0.97) and accuracy (relative difference range: 0.38 to 2.20). In only one class, seasonally flooded
palustrine forested/scrub-shrub (PFO/SSC) wetlands of the Prairie Pothole region, was this not the case. There
were 366 PFO/SSC wetland polygons with a relative difference of -0.04 and CV of 0.25 (see Tables 4-6).
The EMAP sampling design provides accurate and precise estimates of wetland numbers and surface areas
with the true population value usually contained within the 90% confidence bounds. Exceptions to this trend
were usually, but not always, rare classes. In the Washington region, PEMA, PEMC and PS wetlands were
underestimated with respect to wetland surface area. A likely explanation is the existence of several large
wetlands of these types in the region. In the Prairie Pothole region, PL was underestimated with respect to
both numbers of wetland polygons and surface area and PEMA, PEMC and PL with respect to surface area.
Sample size in addition to the existence of a few large wetlands contributed to the relatively poorer
estimations. The EMAP sampling design provides for intensification of the sampling grid density to increase
the sampling intensity when rare classes are of interest.
Aggregation into the selected size classes creates no rare classes, therefore, numbers of wetland polygons are
estimated more accurately than the EMAP classes (see Tables 7-9 and Figure 12). Aggregation into size
classes reduces variation of surface area resulting in increased accuracy. In addition, the EMAP design
provided precise estimates for most size classes, with CVs less than 15% for most size classes below 10 ha
in size. The relative difference increases slightly as the size classes increase from 10 to 100 ha, this is
considered a function of fewer wetland polygons in these size classes, and results in higher estimates of
variability and relative difference between the estimated population characteristics. In most size classes the
90% confidence intervals for the estimates of wetland polygon number and surface areas contained the true
population value.
21
-------
Table 4. Sample estimates for number and areas of wetlands by EMAP class for the Illinois region. "*"
indicates that the true population value is contained within the estimate's confidence interval. NP identifies
EMAP classes not present in the region. "--" denotes that estimates were not obtainable for that EMAP class
in the region.
A.
B.
EMAP Class
E2EM
E2FO/SS
PEMAR
PEMA
PEMBR
PEMB
PEMCR
PEMC
PFO/SSAR
PFO/SSA
PFO/SSBR
PFO/SSB
PFO/SSCR
PFO/SSC
PL
PS
TOTAL
EMAP Class
E2EM
E2FO/SS
PEMAR
PEMA
PEMBR
PEMB
PEMCR
PEMC
PFO/SSAR
PFO/SSA
PFO/SSBR
PFO/SSB
PFO/SSCR
PFO/SSC
PL
PS
TOTAL
Number
NP
NP
968
11518
5
104
1169
16483
7515
9438
1
9
2587
6568
1861
61519
119745
Area
(ha)
NP
NP
2742
9929
90
4O1
4690
20806
79920
37O12
0
27
24427
21584
19751
26042
247421
Est.
Number
--
-
1079
11531
0
64
1287
16331
8276
10267
0
0
3116
7882
1776
60600
122209
Est.
Area
--
4089
9855
0
93.26
4395
18279
81169
42018
0
0
22457
20028
14816
26169
243368
- INUIIIUBI ui
Rel.
Diff.
-
0.11
<0.01
-1.00
-0.38
0.10
-0.01
0.10
0.09
-1.00
-1.00
0.20
0.20
-0.03
-0.01
-0.02
of Wetlands
Rel.
Diff.
-
-
0.49
-0.01
-1.00
-0.77
-0.06
-0.12
0.02
0.14
1.00
-1.00
-0.09
-0.07
-0.25
<0.01
0.02
vvciidiiua
SE
-
208
1398
-
44
215
2509
1196
1193
-
--
941
1239
533
7302
in Hectares -
SE
-
_
1288
1528
-
84
1661
4398
25290
9661
-
-
7110
4050
6497
2936
CV
-
-
0.19
0.12
-
0.68
0.17
0.15
0.14
0.12
-
-
0.30
0.16
0.30
0.12
CV
-
-
0.32
0.16
-
0.90
0.38
0.24
0.31
0.23
-
--
0.32
0.20
0.44
0.11
90% Conf.
Lower
Bound
-
-
737
9231
-8
934
12203
6310
8303
~
-
1567
5845
900
48588
90% Conf.
Lower
Bound
-
-
1969
7341
--
-45
1663
11044
39566
26125
-
-
10762
13365
4129
21339
Int.
Upper
Bound
-
_
1422"
13831*
136*
1640'
20459*
10243*
12230*
-
-
4664*
9920*
2652"
72611*
Int.
Upper
Bound
-
-
6208*
12369*
-
232
7128*
25513*
122771*
57910*
-
-
34153*
26691*
25503*
30999*
22
-------
0
C5
lil
tc.
tfi
o
Zj
1 1
ฎ cr F
(3 ฃ o
CE U. O -
ฃ trfiป
"5
(D
U.
0 ^
p m
C i C73
o5 E (o
w o ^ co
a> o O c/3
nt.s
ซ#sa
-Q S 2 ?
E " LLI ซ
^ni
C ^.^ UJ
111-.
c|^-i
i-^-iS5
8C?S ID
,_ Jฃ 0 ^
* v "5 c
SIH
t= ซ ffl 3
ซ ^ 1 ฃ
ซ o w _
ls|g
"sis
ฃ ff'B |
og^g
"D CO (0
c - o 2
m co ป_ (0
-a ffl -jj
t^ m 8 "
ซ ซ CO ^
5 | ง a
8 ป- ซ "5
Ig^^
sM<
^ CD ^c
1 8 ^m
*ฐ (0 -=
0) -ff (0 O
E 3 "5 ?
ซ w r ^~
- c 0 .
ง 12.2
r- ฎ O "S
c ป.. x^ co
0) Q. g>-=
1 ฃt|
ill!
.2 E ^ ^
S JTl-E
ฃ -o * ฃ
?ง!!-S
1-351
o CD P c
c ^ c *
-i *!-
oj ป 5 o
ฎ ฃ o *
ป- O ป- a>
ซ C3) o 3
5 ^ฃ -a
i ง-5 8
ซ1 3 8
J= (0 -2 ^5
^ 3= 73 o
5 S "5 co
^ * - co
_o "o ฃ CO
ฐ- to ซo o
5 co 5^u-
xi g a.
SE ฐ T3
3 T C
c/) c -6- co
o>
CD
3
a>
23
-------
Table 5. Sample estimates for number and areas of wetlands by EMAP class for the Washington region. "*"
indicates that the true population value is contained within the estimate's confidence interval. "--" denotes
that estimates were not obtainable for that EMAP class in the region.
A.
B.
EMAP Class
E2EM
E2FO/SS
PEMAR
PEMA
PEMBR
PEMB
PEMCR
PEMC
PFO/SSAR
PFO/SSA
PFO/SSBR
PFO/SSB
PFO/SSCR
PFO/SSC
PL
PS
TOTAL
EMAP Class
E2EM
E2FO/SS
PEMAR
PEMA
PEMBR
PEMB
PEMCR
PEMC
PFO/SSAR
PFO/SSA
PFO/SSBR
PFO/SSB
PFO/SSCR
PFO/SSC
PL
PS
TOTAL
Number
839
15
507
2443
43
278
2219
12318
2129
2188
19
173
4585
9454
746
8390
46346
Area
(ha)
7512
37
3422
6267
36
303
9265
19661
8979
5947
16
158
18336
25477
2759
5676
113851
Est.
Number
800
48
433
1905
16
160
1582
9664
2305
2032
0
176
4558
8753
656
6680
39768
Ares
Est.
Area
11785
92
4428
2968
1
111
6306
12970
7161
5642
0
99
21396
31952
1851
3469
110231
IXU1IIUGI Ul
Rel.
Diff.
-0.05
2.20
-0.15
-0.22
-0.63
-0.42
-0.29
-0.22
0.08
-0.07
-1.00
0.02
-0.01
-0.07
-0.37
-O.22
-0.14
of Wetlands
Rel.
Diff.
0.57
1.50
0.29
-0.53
-0.96
-0.64
-O.32
-0.34
-0.20
-0.05
1.00
-0.37
0.17
0.25
-0.33
-0.39
0.03
vveimiiua
SE
260
34
156
544
15
113
351
1885
449
395
-
88
912
1398
238
1145
in Hectares -
SE
5244
63
3544
1271
1
96
2249
3594
1884
1624
78
8385
9055
857
608
CV
0.33
0.72
0.36
0.29
0.97
0.71
0.22
0.20
0.19
0.19
--
0.50
0.20
0.16
0.36
0.17
CV
0.44
0.69
0.80
0.43
0.97
0.87
0.36
0.28
0.26
0.29
-
0.78
0.39
0.28
0.46
0.18
90% Conf.
Lower
Bound
372
-9
176
1010
-9
-26
1004
6564
1567
1383
32
3058
6452
264
4797
90% Conf.
Lower
Bound
3159
-12
-14O3
878
-1
-48
2606
7058
4062
2971
-
-28
7603
17058
441
2469
Int.
Upper
Bound
1228*
105*
690*
2800*
41
346*
2160*
12765*
3044"
2681*
320*
6058*
11053*
1048"
8563*
Int.
Upper
Bound
2041 1 "
196*
10259*
5059
4
269
10006*
18881
10259*
8312"
227"
35189*
46848*
3261*
4468
24
-------
2
0
C5
UJ
cc
z
o
J
0
2
X
1
(D ^ ^*^
3 c ^
DC III O Si
< D O
-
0<
CD
Q. O .E
g o S
ซ^5
Z ^- ~ C
AO
25
CD
O)
Lu
-------
Table 6. Sample estimates for number and areas of wetlands by EMAP class for the Prairie Pothole region.
"*" indicates that the true population value is contained within the estimate's confidence interval. NP
identifies EMAP not present in the region. "--" denotes that estimates were not obtainable for that EMAP class
in the region.
A.
B.
EMAP Class
E2EM
E2FO/SS
PEMAR
PEMA
PEMBR
PEMB
PEMCR
PEMC
PFO/SSAR
PFO/SSA
PFO/SSBR
PFO/SSB
PFO/SSCR
PFO/SSC
PL
PS
TOTAL
EMAP Class
E2EM
E2FO/SS
PEMAR
PEMA
PEMBR
PEMB
PEMCR
PEMC
PFO/SSAR
PFO/SSA
PFO/SSBR
PFO/SSB
PFO/SSCR
PFO/SSC
PL
PS
TOTAL
Number
NP
NP
103
99067
NP
2
112
102252
93
1163
NP
NP
88
366
2739
13554
219539
Area
(ha)
NP
NP
859
85644
NP
48
2999
133691
186
488
NP
NP
231
304
20586
7228
252264
Est.
Number
-
-
16
102704
-
0
0
84640
0
1232
-
-
0
352
944
12032
210920
A rr\*\
Micd
Est.
Area
-
-
46
65046
-
0
0
104001
0
539
~
-
0
278
6206
6960
183076
- iNumum ui vvt
Rel.
Diff.
-
-
-0.84
0.04
-
-1.00
-1.00
-0.17
-1.00
0.06
-
-
-1.00
-0.04
-0.66
-0.11
0.08
f\f XA/atlonf^c in
OT VVeuanGS in
Rel.
Diff.
--
-
-0.95
-0.24
-
-1.00
-1.00
-0.22
-1.00
0.10
-
-
-1.00
-0.09
-0.70
-0.04
0.27
ilidiiua -
SE
--
-
15
13144
-
-
--
10836
-
261
-
-
-
87
469
1360
1 Ifi/^t^ir ft
neciare
SE
-
-
44
6826
-
-
-
10933
-
159
-
-
-
106
3670
1625
CV
-
-
0.97
0.13
-
-
--
0.13
--
0.21
-
-
--
0.25
0.50
0.11
5 ~-
CV
--
--
0.97
0.10
--
-
-
0.11
--
0.30
--
-
-
0.38
0.59
0.23
90% Conf.
Lower
Bound
-
-
-9
81082
-
-
-
66815
-
802
-
-
-
209
173
9794
90% Conf.
Lower
Bound
-
-
-27
53817
-
-
-
86015
-
277
-
-
-
104
168
4287
Int.
Upper
Bound
-
-
41
124326*
-
-
--
102465*
-
1662*
-
-
-
495*
1715
14270*
Int.
Upper
Bound
-
-
118
76275
-
-
-
121986
-
801*
-
-
-
452*
1244
9632*
26
-------
CO .
z
o
o
UJ
DC
UJ
O
ฃ
o
0.
UI
gc
o fc 2
fc < IS
6
>
2 5
KB _
Q. ~~
or Q- Q
ll
UJ
^7 i , i , i , i , i - i , i . i . i .
CM
CM
CM*
0
CM
00.
CM
0
" ง
co |
ฐ tfc
5
CD ฎ
O ^
cd
o
ซ! DC
o
CM
0
O
O
CM
O
*t
O
1
CD
O
i
CO
o
0
oojcor^com^-cocM-*- oV
^oooooooo'oo
0
AO
C ^i CB
21
-------
Table 7. Sample estimates by size class for the Illinois region.
is contained within the estimate's confidence interval.
indicates that the true population value
A.
B.
Size Class
0 - 0.25
0.25 - 0.50
0.50- 1.0
1 -2
2-5
5- 10
10-25
25 - 50
50-100
>100
Size Class
0-0.25
0.25 -0.50
0.50 - 1.0
1 -2
2 - 5
5 - 10
10 -25
25 - 50
50-100
>100
Number
54299
20009
15519
11902
10198
4007
2454
755
351
250
Area
(ha)
6847
7120
11021
16833
31896
27633
37642
25919
24465
58044
iijumuei
Est.
Number
54529
20304
15963
12671
10797
4064
2504
843
389
144
-------
Table 8. Sample estimates by size class for the Washington region.
value is contained within the estimate's confidence interval.
'*" indicates that the true population
A.
B.
Size Class (ha)
0-0.25
0.25 -0.50
0.50 - 1.0
1 - 2
2-5
5 - 10
10 -25
25 - 50
50 - 1 00
>100
Size Class (ha)
0 - 0.25
0.25 - 0.50
0.50- 1.0
1 -2
2-5
5 - 10
10-25
25-50
50 - 100
>100
Number
12279
8280
8247
6938
6028
2497
1439
406
178
55
Area
(ha)
1691
2972
5961
9845
18851
17297
22308
13941
11865
9113
IMUIIlUt:!
Est.
Number
10793
7727
6928
5169
5071
2096
1296
400
208
80
Ul VVUllcl
Rel.
Diff.
-0.12
-0.07
-0.16
-0.25
-0.16
-0.16
-0.10
-0.01
0.17
0.45
- Area of Wetlands in
Est.
Area
1499
2813
4982
7365
15753
14916
20843
13739
15060
13261
Rel.
Diff.
-0.11
-0.06
-0.16
-0.25
-0.16
-0.14
-0.07
-0.01
0.27
0.45
nua
SE
1747
910
879
791
844
463
375
194
109
40
LJ o/^+arac
nccidres
SE
233
330
639
1143
2658
3347
5969
6863
8005
7128
CV
0.16
0.12
0.13
0.15
0.17
0.22
0.29
0.48
0.53
0.51
CV
0.16
0.12
0.13
0.16
0.17
0.22
0.29
0.50
0.53
0.54
90% Conf.
Lower
Bound
7919
6231
5481
3868
3683
1334
680
81
28
13
90% Conf.
Lower
Bound
1116
2270
3931
5484
11381
9412
11024
2450
1891
1536
Int.
Upper
Bound
13666*
9224*
8375*
6471
6459*
2858*
1912*
719*
388*
147*
Int.
Upper
Bound
1882*
3355*
6033*
9246
20125*
20422*
30661*
25028*
28228*
24986*
29
-------
Table 9. Sample estimates by size class for the Prairie Pothole region.
value is contained within the estimate's confidence interval.
indicates that the true population
A.
B.
Size Class (ha)
0-0.25
0.25 -0.50
0.50 - 1.0
1 - 2
2 - 5
5- 10
10 - 25
25 - 50
50 - 1 00
>100
Size Class (ha)
0-0.25
0.25 -0.50
0.50- 1.0
1 -2
2- 5
5 - 10
10-25
25 - 50
50 - 1 00
>100
Number
113549
39212
29046
18308
12733
4013
1923
437
198
121
Area
(ha)
14557
13951
20535
25574
38810
27673
28717
15123
13839
53485
i\/umut:i
Est.
Number
115531
39415
30076
17575
12372
3449
1633
321
96
55
Ul VVeiial
Rel.
Diff.
0.02
0.01
0.04
-0.04
-0.03
-0.14
-0.15
-0.27
-0.52
-0.55
- Area of Wetlands in
Est.
Area
14862
14004
21211
24450
37399
23454
23087
10894
7312
6400
Rel.
Diff.
0.02
<0.01
0.03
-0.04
-0.04
-0.15
-0.20
-0.28
-0.47
-0.88
IlUb
SE
12055
3799
2508
1736
1068
464
239
82
47
37
H6Ct3f6S
SE
1486
1337
1784
2434
3332
3298
3426
2907
3623
4362
CV
0.10
0.10
0.08
0.10
0.09
0.13
0.15
0.26
0.49
0.68
CV
0.10
0.10
0.08
0.10
0.09
0.14
0.15
0.27
0.50
0.68
90% Conf
Lower
Bound
95700
33167
25950
14719
10615
2686
1240
186
18
-6
90% Conf
Lower
Bound
12418
11085
18277
20446
31919
18029
17451
6112
1352
-776
. Int.
Upper
Bound
135361*
45664*
34202*
20432*
14128*
4213*
2027*
455*
174
116
. Int.
Upper
Bound
17306*
16204*
24145*
28454*
42880*
28879*
28723*
15676*
13273
13576
30
-------
1.0 n
8 0.5-
b o.o
0)
J!J
ซ -0.5 H
-1.0
Illinois Region
Number
DArea
0.0-0.25 0.25-0.5 0.5-1
1-2 2-5 5-10 10-25 25-50 50-100 >100
Size Class in ha
Washington Region
0.0-0.25 0.25-0.5 0.5-1 1-2
2-5 5-10 10-25 25-50 50-100 >1OO
Size Class in ha
Prairie Pothole Region
0.0-0.25 0.25-0.5 0.5-1
1-2 2-5 5-10 10-25 25-50 50-100 >100
Size Class in ha
Figure 12. Comparison of the relative differences between the true population value and the
estimated value for wetland numbers and surface area for several size classes
in the 3 regions.
31
-------
CONCLUSIONS
The goal of this study was to quantitatively assess the EMAP-Wetland's classification and statistical sampling
design with the following objectives in mind: 1) compare wetland polygon numbers, surface areas, common
versus rare wetland classes and the effect imposing a minimum mapping unit, 2) evaluate the EMAP base grid
density of 27 km between sampling points and compare sample values to known population values, 3)
compare the sampling design and EMAP classification across the three regions, 4) discuss procedures for
generating a sampling frame using the NWI digital data.
The large majority of wetlands in the three regions were less than 1 ha in size. The types of wetlands in each
of the regions were distinct. In the Illinois region the most common wetlands were seasonally flooded
palustrine emergents (PEMC) and palustrine shallows (PS). All wetlands classes were present in the
Washington region which was dominated by seasonally flooded palustrine emergents (PEMC) seasonally
flooded forest/shrub-scrub wetlands (PFO/SSC) and palustrine shallows (PS). Palustrine emergents, both
temporarily (PEMA) and seasonally flooded (PEMC), dominated the Prairie Pothole region. Information
presented in this study regarding the size distribution of wetlands provides resource managers and others
interested in wetland monitoring and assessment programs with the means to evaluate the magnitude of the
effect of imposing minimum mapping units. For example, if a minimum mapping unit of 0.5 ha was chosen
as the resolution level for identifying wetlands using remote sensing technology, approximately 70% of the
wetlands in the Prairie Pothole region would be excluded. This would severely bias the results and
underestimate the wetlands.
Evaluation of the sample data by comparison to the known population values provided accurate and precise
estimates of wetland polygon numbers and surface areas with the exception of rare EMAP classes. It is
unusual and informative to have the population data available to evaluate the performance of a sampling
design. The availability of the population permitted identification of rare EMAP classes however, precision
estimates for rare classes were lower than the more common classes. This is characteristic of any design not
specifically tailored for the objective of estimating rare classes well. Population information pertaining to rare
classes will prove valuable when intensifying the base grid density to sample a rare class.
The EMAP sampling design with a base grid density of 27 km performs well with the possible exception of rare
classes and classes with restricted spatial distributions (e.g., estuarine emergent wetlands). Relative
differences and CVs were comparatively low. The 90% confidence intervals for the estimates usually
contained the population values for both the EMAP classes and size classes. The base grid density may require
intensification to ensure adequate sample sizes for rare and spatially restricted wetland types when those
classes are of interest. Results from our study suggest that intensification of the base sampling grid may be
necessary when fewer than 500 wetlands occur in an EMAP class over a given region. Also, wetlands with
surface areas above 50 ha, may also require intensification of the base grid density for adequate sampling.
Rare wetland classes in the region sampled include saturated palustrine emergents (PEMB), saturated
emergents along rivers (PEMBR) and saturated forest/scrub-shrub wetlands along rivers (PFO/SSBR).
Across all three regions the majority of wetlands were relatively small (less than 1 ha). The most common
EMAP class across the regions were the seasonally flooded emergents (PEMC). Relatively rare EMAP classes
across the three regions were saturated emergents (PEMB), saturated emergents along rivers (PEMBR),
saturated forest/scrub-shrub along rivers (PFO/SSBR) and saturated forest/scrub-shrub (PFO/SSB).
As expected, the aggregation of wetlands from the NWI classification to the EMAP classification results in
fewer wetlands with larger areas. Total wetland surface area in a region, however, is not affected. The
presence of extremely large wetlands also creates a problem for area estimates. A possible solution would
be sampling these wetlands employing a separate sampling design. Large wetlands are easy to locate and
32
-------
therefore development of a list frame should not pose a problem. Augmentation of the EMAP base grid density
will be necessary for rare wetlands and those that are spatially restricted (e.g., estuarine emergent wetlands)
to ensure adequate sample sizes. The EMAP sampling design allows for intensification across regions.
The NWI classification and digitized maps can be used for the EMAP sample frame development in the regions
investigated. Expansion of this procedure for implementation across the entire U.S. requires further study.
The NWI maps effectively match the criteria for EMAP sample frame development presented in the
introduction. The NWI maps contain spatial data, include information about the distribution and extent of
wetlands, when completed will cover the entire U.S. and, include all wetlands of interest to EMAP-Wetlands.
The NWI program was designed to estimate total acreage and change in total acreage for each wetland type
within 10% of the true values with a 90% probability (Prayer, et al. 1983). Our study demonstrates that the
NWI classification based on Cowardin et al. (1979) can successfully be aggregated into the EMAP
classification. This successful aggregation demonstrates that EMAP-Wetlands can develop sampling frames
from the available NWI digital data sets.
It is expected that the EMAP sampling design and EMAP classification system will be useful for wetlands
resource managers implementing regional monitoring and research programs. The NWI maps are currently the
most appropriate maps available for EMAP-Wetlands sampling frame development. The NWI maps provide
national coverage, include the distribution and extent of wetlands, and are the most complete in terms of
covering the nations wetlands. The EMAP classification and sampling design based on NWI digital data will
require only field verification (i.e., ground truthing) before implementation.
33
-------
LITERATURE CITED
Cochran, W.G. 1977. Sampling Techniques. John Wiley and Sons, New York, New York. 428pp.
Cowardin, L.M., V. Carter, F.C. Golet, and E.T. LaRoe. 1979. Classification of Wetlands and Deepwater
Habitats of the United States. U.S. Department of the Interior, Fish and Wildlife Service. FWS/OBS-79/31.
131 pp.
Crowley, S., C. O'Brien, and S. Shea. 1988. Results of the wetland study and the 1988 draft wetland
rules. Report by the Agency of Natural Resources Divisions of Water Quality, Waterbury, VT. 33 pp.
Prayer, W.E., TJ. Monahan, D.C. Bowden, and F.A. Graybill. 1983. Status and Trends of Wetlands and
Deepwater Habitats of the Conterminous United States, 1 90's to 1970's. Colorado State University, Fort
Collins, Colorado. 32pp.
Leibowitz, N., L. Squires, and J. Baker. 1991. Research Plan for Monitoring Wetland Ecosystems.
EPA/600/3-91/010. U.S. Environmental Protection Agency, Environmental Research Laboratory, Corvallis,
OR. 157 pp plus appendices.
Mann, G.E. 1974. The Prairie Pothole Region: A Zone of Environmental Opportunity. [Map.] Naturalist
25(4):2.
Omernik, J.M. 1987. Ecoregions of the United States. Map at a scale of 1:7,500,000. Supplement to
the Annals of the Association of American Geographers, Volume 77, Number 1.
Overton, W.S., D. White, and D.L. Stevens, Jr. 1991. Design Report for EMAP, Environmental Monitoring
and Assessment Program. EPA 600/3-91/053. US Environmental Protection Agency, Environmental
Research Laboratory, Corvallis, OR.
Roose, D.V. and K.K. Stout. 1992. CIS Methods for Reclassifying Wetland Maps for EMAP Sampling
and Monitoring. Proceedings of the Twelfth Annual ESRI User Conference, Palm springs, CA. 19pp.
Snedecor, G.W. and W.G. Cochran. 1980. Statistical Methods. The Iowa State University Press, Ames,
Iowa. 507pp.
Swartwout, D.J. 1982. An evaluation of National Wetlands Inventory in Massachusetts. MS Thesis,
University of Massachusetts, Amherst. 123 pp.
U.S. Fish and Wildlife Service, National Wetlands Inventory. 1990a. Photointerpretation Conventions of the
National Wetlands Inventory. Internal document. U.S. Fish and Wildlife Service, St. Petersburg, Florida.
45pp plus appendices.
U.S. Fish and Wildlife Service, National Wetlands Inventory. 1990b. Cartographic Conventions for the
National Wetlands Inventory. Internal document. U.S. Fish and Wildlife Service. St. Petersburg, Florida.
43pp plus appendices.
Wilen, B.O. 1990. The U.S. Fish and Wildlife Service's National Wetlands Inventory, pp. 9-20 In: S.J.
Kiraly, R.A. Cross, and J.D. Buffington (eds.) Federal Coastal Wetlands Mapping Programs. FWS Biological
Report 90(18). US Department of the Interior Fish and Wildlife Service, Washington, DC.
34
-------
Appendix A
Database Design and Procedures Necessary to
Correct Errors Associated with
Use of Multiple GIS Coverages
35
-------
Database
The original NWI digital data existed in individual coverages equivalent in extent to U.S.G.S. 7 1/2'
quadrangles. Software storage limitations (ARC/Info allows only 10,000 arcs per polygon) prevented the
creation of one large GIS coverage for each region. A database design was therefore needed to partition
the digital data into several artificially divided coverages, or tiles, with minimal effect on the desired
wetland attributes. The optimum tile structure was defined as one that:
1) Would cover the largest geographic area (require the fewest coverage boundaries) as possible
without exceeding ARC/Info storage limitations during any stage of processing,
2) Would not perturb the size and number of wetlands in the sample population (40 km2 hexagons),
3) Would facilitate the correct coding of EMAP wetlands located at the borders of the separate
coverages,
4) Would promote calculation of error rates associated with the impact of the coverage
boundaries on wetland attributes.
The optimal tile size, location, and configuration was determined to be a 640 km2 hexagon, positioned on
the centroid of the 40 km2 hexagon. Thus adjacent tiles represent continuous coverage of a study area, in
which the center hexagon (1/16th of area) experiences a minimal chance of being cut by a tile boundary.
ARC/lnfo's Librarian module was used to reformat the data from the NWI quadrangle digital cover into the
640 km2 tile structure. Librarian was selected for its extraction capability, the capability to automatically
create a coverage of any defined geographical extent from a collection of source coverages. Because the
data is geographically referenced within Librarian, the software can easily acquire the data, copy it, and
reconstruct topologically correct coverages. This capability was used in the wetland receding and
enumeration steps described below. The Librarian software also provided a passive quality control on the
data by accepting only source coverages that included identically defined items or data fields in the data
base.
Technical Challenges with Polygon Enumerations
The multiple spatial coverages within a region caused some technical challenges which had to be overcome
before accurate enumeration of the population was possible. Tile boundaries cut polygons on the border
into two or more pieces/polygons, depending on the wetlands's shape, position within the tile, or position
within a group of wetlands. (See Figure A1). The resulting total number of wetlands in the study area
would be overestimated by summing the total number of wetlands in each tile.
A window coverage, a tile coverage and a 5 km buffer around the tile (refer to Figure 7), was used for
both receding and enumeration purposes. When the tile's boundary arc is inserted into a copy of the
window containing wetlands with unique identifiers, wetlands at the tile border are split in pieces. These
pieces (polygons) retain their original wetland identification. An INFO program that relates the original
window to the 'split' wetland coverage, can count how many times each original wetland identification
occurs in the split window. An uncut wetland will be counted as one, while a wetland cut three times
receives a value of three.
The corrected number of wetlands in the study area is calculated by summing the number of wetlands that
are not cut by the tile structure outline plus half the number of wetlands cut in two pieces plus a third of
the number of wetlands cut in three pieces plus ... and so forth.
36
-------
c.
D.
Rgure A. Wetlands can be cut by the tile structure in various ways, creating an
unpredictable number of polygons.
37
-------
Appendix B
Technical Challenges Associated with EMAP Coding
38
-------
Assigning EMAP Hydrologic Locators
An EMAP code depends on both its NWI code and its locational relationship to a perennial riverine or a
lacustrine system. Riverine wetlands may be under-represented. Portions of some rivers or streams are
mapped as Palustrine and not assigned the riverine hydrologic locator. This is because by NWI mapping
conventions, if a river and its adjacent wetland vegetation do not exceed the minimum mapping unit width
for polygons then only the wetland vegetation is mapped and represented as a Palustrine linear feature
(Roose and Stout, 1992. Rivers or lakes located outside a tile could therefore influence the EMAP class
assigned to a wetland within and along the tile's border. Since topological continuity between tiles does
not exist in ARC/lnfo version 5.0.1, one must extract and recede a coverage wider than the tile to make
sure that all external river or lake influences on the wetlands inside the tile are taken into account (see
Figure B1). This coverage, referred to as 'window' in the text below, includes wetlands inside the tile and
from a 5 km buffer area around the tile.
NWI digitizes rivers and lakes as either linear or polygons, depending on their size. In the original data for
Illinois, linear and polygon features existed in separate ARC/lnfo coverages. They were combined in the
same coverage for this study to determine adjacency of wetlands to riverine or lacustrine features. Once
combined, the impact of surrounding features on each wetland polygon was searched and identified using
the powerful relational capabilities of INFO, the database portion of the software. Using INFO for this
search greatly increased processing efficiency and reduced processing time.
However, there were situations where INFO topology alone could not accurately code all river edge
wetlands (i.e. in the case of island polygons.) According to the EMAP Wetland classification, if a group of
contiguous polygon wetlands is surrounded by a riverine wetland, all the individual wetlands are influenced
by the river and should receive the appropriate riverine hydrologic locator code. This is true even when
there are upland polygons in the group.
Fortunately, ARC manipulations and analyses were well suited to respond to these situations. In the above
example, the polygon group is correctly characterized in terms of its relationship to the riverine system by
creating a second coverage containing only the riverine polygons, without island groups. By doing so,
riverine attributes now extend over the former island area. Overlaying the two coverages creates an INFO
table that can be used to code the wetlands from the original coverage that are within the riverine
polygons of the second coverage. A similar procedure is used to exclude island wetlands that are
completely surrounded by upland.
Coding Limitations
Hydrologic locators were introduced in the EMAP classification to differentiate the source of hydrology
among wetlands (e.g., basin, riverine, lacustrine). The riverine locator was intended to represent the
influence of all perennial rivers. It was assumed that all rivers were mapped by NWI as riverine systems.
However, according to NWI mapping conventions, if a river and its adjacent wetland vegetation do not
exceed the minimum mapping unit width for polygons, only the wetland vegetation is mapped and
represented as a linear feature. Therefore, portions of some rivers or streams are mapped as palustrine
systems, and were not used in this model to assign the riverine hydrologic locator. In some instances,
rivers (polygons or linear) were not mapped as they flowed through a chain of wetlands. In those cases
the program only assigns the riverine hydrologic locator to the wetland at the ends of the chain. Using
non-network CIS topology it is not possible to distinguish between interior wetlands in the chain, and a
wetland separated from a river by another wetland, (see Figure B2). Therefore, river edge wetlands will be
under represented in both the sample and the wetland population.
39
-------
o
o
c
T>
C
CO
CD
CD
O
C
"a.
E
co
CO
x
CO
c
CO
CO
5
.c
in
c
g
"*-
jo
o>
en
m
0)
-------
WETLANDS
I
WETLANDS -
RIVER
WETLANDS -
RIVER
WETLANDS
I
Figure B2. Non-network topology can not distinguish among the situations above.
41
-------
Old NWI Water Regimes
Some of the quadrangles in the Washington study area were mapped using older NWI water regime
modifiers (X,Y,Z). The modifier Y lumps saturated, semipermanent, and seasonal water regimes. These
are separate under the EMAP wetland classification (i.e., B = saturated, C = seasonally-permanently
flooded). All NWI classes with the Y water regime modifier were placed in a class with a "C" EMAP water
regime, the wetter regime.
NWI Mixed Wetland Classes
The NWI-to-EMAP code translation was complicated by the occurrence of NWI mixed classes. If two
vegetative classes co-exist in the same wetland and each of them covers at least 30% of the area, NWI
codes the wetland with both classes. For example, 'PEM/SS1C' is a palustrine wetland where both
emergent and scrub-shrub extend over at least 30% of the area and where 'EM' has the largest extent. In
the NWI code, the dominant class precedes the other and is separated from it by a slash (/). This latter
may only appear in the fourth, fifth or sixth position in the code, limiting the situations to a manageable
and programmable number.
The dominant wetland class is used exclusively when assigning the EMAP wetland code. 'PEM/SS1C' is
thus simplified to a Palustrine ('P') Emergent ('EM') for EMAP receding purpose.
Other Notes
In the receding program two general classes were created which included EMAP-Surface Water, rivers and
lakes, and EMAP-Near Coastal resources, marine and intertidal resources other than wetlands. These
classes were not included in the study analysis. In addition, an orphan class was added in order to identify
NWI codes not assigned to an EMAP resource class. Wetlands falling into this orphan class were reviewed
regularly. Older, obsolete NWI codes in the data were identified this way, and where possible, were
assigned to the appropriate EMAP class.
42
-------
Appendix C
Table summarizing the EMAP classes after aggregating the NWI classes
for the Illinois region
43
-------
Table C. Summary of NWI classes mapped to each EMAP class for the Illinois
Region.
EMAP
PEMAR
PEMA
PEMBR
PEMB
PEMCR
NWI
PEM/FO1A
PEM/FOA
PEM/SS1A
PEM/USA
PEM1A
PEMA
PEMAD
PEMADF
PEMAF
PEMAH
PEMAX
PEM/F01A
PEM/SS1A
PEM1A
PEM1AD
PEM1AF
PEMA
PEMAC
PEMAD
PEMADF
PEMADH
PEMAF
PEMAFD
PEMAFH
PEMAFX
PEMAH
PEMAX
PEM/SS1B
PEMB
PEM/FO1B
PEM/SS1B
PEMB
PEMBD
PEM/F01C
PEM/F01F
PEM/FOC
PEM/OWF
PEM/SS1C
PEM/SS1F
PEM/UBF
PEM1C
PEM1F
PEM2G
i
i
i
i
i
i
Number j
i
i
34[
2!
70!
i!
4!
824|
32',
8!
55,'
11!
4!
37!
97!
13!
1!
i!
3900!
i!
385!
635J
3!
5670!
7!
4!
i!
168|
82!
i!
4!
4!
5!
86!
10!
141
6!
i!
i!
36!
3!
li
4!
2!
4!
1
1
1
Percent | ~
Number j
i
i
3.3,'
0.2J
6.7J
0.1!
0.4J
78.9!
3.1|
0.8j
5.3[
i.ij
0.4J
0.3[
0.9!
0.1J
o.o[
o.o!
35. 4j
o.o!
3.5!
5.8!
o.o!
51.5[
o.i!
O.Oj
o.o[
1.5|
0.7[
20.0!
80.0!
3.8]
4.8!
81.9!
9.5|
i-i!
0.5J
0.1 j
o.i!
2.9J
0.2j
o.i!
0.3|
0.2!
0.3!
Area j
(ha) [
Total !
i
i
112.2!
1.6!
201.7J
0.4[
5.5!
1804. 6j
238. 6|
56.0J
144.8J
16.1[
23.6!
79.2!
346.0!
42.9J
1.0j
1.0!
3758.7!
0.2!
818.2!
945.9!
15.3!
3060.8!
5.8J
2.8!
0.3!
102.7!
56.4!
58.5!
31.5!
36.9!
52.4!
157.1!
154.0J
51.41
13.4|
0.3j
4.3!
196.3J
4.7[
14.7!
4.5!
0.5[
4.1!
Area j
(ha) [
% Total]
1
4.3!
o.i!
7.7!
o.o!
0.21
69.3J
9.21
2.2J
5.6!
0.6!
0.9J
0.9!
3.7!
0.5|
o.o!
o.o!
40.7J
o.o!
8.9!
10.2!
0.2!
33.1!
o.i!
o.o|
o.o!
i.i!
0.6!
65.0!
35.0!
9.2]
13.1!
39.2!
38.4]
1.21
0.3!
o.o!
o.i!
4.5|
o.i!
0.3!
0.11
o.o|
o.i!
i
i
Area (ha) [
_ i
MEAN !
_ i
i
i
3.30J
0.82[
2.88|
0.45J
1.37|
2.19!
7.461
7.00!
2.63!
1.46!
5.91J
2.14!
3.57!
3.30!
0.96!
0.96!
0.96!
0.20J
2.13!
1.49!
5.10!
0.54!
0.83J
0.69[
0.25J
0.61!
0.69!
58.53J
7.87!
9.23!
10.49|
1.83]
15.40J
3.67',
2.24|
0.34|
4.26]
5.45 j
1.55|
14.72 !
1.12!
0.25 !
1.02 !
44
-------
Illinois Region
EMAP NWI
PEMCR PEMC
PEMCD
PEMCDF
PEMCDH
PEMCF
PEMCH
PEMCX
PEMF
PEMFD
PEMFH
PEMFX
PEMG
PEMC PEM/AB3F
PEM/AB4F
PEM/ABF
PEM/ABG
PEM/F01C
PEM/FO1F
PEM/FO1G
PEM/F06F
PEM/OWF
PEM/OWFH
PEM/OWFX
PEM/OWG
PEM/SS1C
PEM/SS1F
PEM/UBF
PEM/UBFH
PEM/UBFX
PEM/UBGX
PEM1/2FH
PEM1C
PEM1CD
PEM1CH
PEM1F
PEM1FH
PEM2/AB3
PEM2CD
PEM2F
PEM2FH
PEM2G
Number
782
79
10
1
8
34
16
199
5
10
6
1
6
9
17
1
83
9
1
2
29
2
1
2
229
12
5
2
1
1
1
20
2
5
2
1
1
2
18
2
19
i i
i i
i i
i i
i Percent i ~
\ Number |
i i
i i
! 63. 9 j
! 6.5!
! 0.8|
i o.ij
! o.7j
! 2.8!
! 1.3!
! 16.3!
! 0.4[
! 0.8!
1 n c 1
1 U. r> ,
! o.i!
! o.o!
! o.i!
! o.i!
! o.o;
! o.5!
! o.i!
! o.o!
! o.o!
! o.2i
I o.o!
! o.o|
! o.o!
! 1.4!
! o.i!
i o.o[
i o.oj
! o.oj
! o.o!
! o.o!
! o.i!
! o.o!
! o.oj
! o.o!
! o.o!
! o.o!
! o.oi
! o.i!
I o.oj
! o.i!
Area
(ha)
Total
2250.0
766.0
373.0
1.6
5.7
58.2
23.6
518.3
5.4
26.4
3.1
0.2
106.2
9.2
62.8
22.7
182.1
13.6
4.0
6.6
22.3
8.5
1.4
3.0
781.8
19.5
48.6
0.3
0.5
2.1
3.5
22.3
0.2
1.1
2.5
0.1
10.0
1.7
36.9
0.8
15.6
j Area
! (ha)
!% Total
1
! 52.0
! 17.7
[ 8.6
! o.o
! o.i
! 1.3
] 0.5
] 12.0
! o.i
! 0.6
! o.i
j 0.0
! 0.5
! o.o
! 0.3
! o.i
! 0.9
j 0.1
! o.o
! o.o
! o.i
! o.o
j o.o
! o.o
! 4.0
! o.i
! 0.2
! o.o
! o.o
! o.o
! o.o
! o.i
i o.o
i o.o
! o.o
! o.o
! o.i
! o.o
! 0.2
! o.o
! o.i
Area (ha)
MEAN
2.88
9.70
37.30
1.58
0.71
1.71
1.47
2.60
1.09
2.64
0.52
0.15
17.70
1.02
3.69
22.72
2.19
1.51
4.00
3.32
0.77
4.27
1.41
1.51
3.41
1.62
9.72
0.13
0.47
2.14
3.46
1.11
0.08
0.22
1.27
0.15
10.02
0.87
2.05
0.41
0.82
45
-------
Illinois Region
EMAP
PEMC
PFO/SSAR
PFO/SSA
NWI
PEM2GH
PEMC
PEMCD
PEMCDF
PEMCDH
PEMCF
PEMCFD
PEMCFX
PEMCH
PEMCHX
PEMCX
PEMF
PEMFB
PEMFD
PEMFH
PEMFHX
PEMFX
PEMG
PEMGH
PEMGX
PFO/SS1A
PFO1/4A
PFOl/EMA
PF01A
PF01AD
PFO1AH
PFO1AX
PFOA
PSS/EM1A
PSS/FO1A
PSS1/EMA
PSSl/USA
PSS1A
PSS1AD
PSS1AH
PSSA
PFO/EM1A
PFO/EMA
PFO/SS1A
PFOl/EMA
PF01A
i
i
i
i
Number |
i
i
15|
9987[
924J
108 j
5!
427|
1!
i!
714J
4|
371J
2141[
1!
86|
578|
1!
548|
6!
17!
6!
25|
1!
54!
9064!
15!
90!
i!
i!
i!
ill
60 i
i!
636|
3!
7!
i!
i!
i!
50|
59|
7875[
i
i
i
i
Percent J -
Number [
i
i
o.i!
60. 8j
5.6!
0.7 j
0.0!
2.6[
O.Oj
O.Oj
4.3!
o.o!
2.3!
13. OJ
o.o!
0.5J
3.5!
o.oj
3.3|
o.o[
o.i!
o.o[
0.3!
o.o!
0.5!
90.9J
0.2|
0.9j
o.o!
o.oj
o.o!
o.i!
0.6!
O.OJ
6.4!
O.Oj
o.ij
o.o!
0.0|
0.0|
0.5J
0.6j
80.8!
Area j
(ha) |
Total j
1
1
19.7J
10529.0J
2986.9J
300.6}
37.2J
442.6,'
2.0J
0.3!
494.6J
2.9[
178. 5j
2496.9}
4.9J
227.8!
281.9J
0.1!
342.1J
4.9!
9.8J
7.8!
240. 3j
1.1!
224. 2 j
72156.9!
299.8J
1401.4!
26.5J
0.2!
6.3J
90.6J
218.0!
1.2!
1743.5!
6.6!
9.9[
1.3!
6.6|
1.4!
230.9!
211.2J
30844.6!
Area !
(ha) !
% Total!
i
'
1
I
o.ij
53.3!
15.1|
1-5!
0.2!
2.2|
o.o|
o.o!
2.5J
o.o[
0.9J
12.6!
o.o!
1.2|
1.4!
o.o!
1.7!
o.o!
o.o!
o.o!
0.3!
o.o!
0.3|
94.4!
0.4|
1.8|
0.0|
o.o|
0.0]
0.1]
0.3|
o.o|
2.3J
o.o!
o.oj
o.o!
0.0]
o.oi
0.7!
0.6
88.2
1
1
Area (ha) !
i
i
MEAN I
_ i
i
i
i
1.31!
1.05|
3.23!
2.78J
7.44J
1.04]
1.96!
0.32J
0.69!
0.73J
0.48[
1.17!
4.87,'
2.65!
0.49[
0.12J
0.62!
0.81!
0.58!
1.29|
9.61|
l.ll!
4.15[
7.96J
19.99!
15.57!
26.48|
0.22J
6.32,'
8.24J
3.63|
1.25J
2.74[
2.20J
1.42 j
1.29[
6.64]
1.41J
4.62 j
3.58J
3.92J
46
-------
Illinois Region
EMAP
PFO/SSA
PFO/SSBR
PFO/SSB
PFO/SSCR
NWI
PFO1AD
PFO1AF
PFO1AH
PFO1AX
PFOA
PFOAH
PSS/EM1A
PSS/F01A
PSSl/EMA
PSS1A
PSS1AD
PSS1AH
PSS1AX
PSSA
PF01B
PFO1B
PSS1/EMB
PSS1B
PSS1BD
PFO/EMC
PFO/SS1C
PFO/SS1F
PF01/EMC
PF01/EMF
PFO1C
PF01CD
PFO1CH
PFO1CX
PFO1F
PFO1FH
PFO1FX
PF05G
PFO6/SS1
PFO6/UBF
PFO6C
PFO6F
PSS/F01C
PSS1/ABF
PSS1/EMC
PSS1/EMF
PSS1/UBF
Number
110
2
191
7
1
1
6
16
99
1248
28
44
7
6
1
5
1
1
2
1
20
2
30
4
2251
10
62
5
75
2
1
2
1
1
5
12
3
1
23
5
4
i i
i i
i i
i i
J Percent J -
! Number |
i i
i i
i i.i!
! o.o!
! 2.0J
I o.i!
! o.oj
! o.o!
i n i '
1 U. I |
! 0.2!
! i.oi
! 12.8J
0.3|
! o.s!
! o.i!
i n i '
1 U.I,
! 100.0!
! 55.6!
! n.i!
! ii.i!
! 22.2!
! o.o!
! o.7i
! o.i!
! i.i!
! o.i!
! 79.9|
! o.4j
! 2.2!
! 0.2!
! 2.7J
! o.ij
i O.OJ
! o.ii
! o.o!
! o.o!
! 0.2!
! o.4|
! o.i!
i o.o!
! o.8|
! 0.2!
! o.i!
Area |
(ha) i
Total i%
i
443.4!
2.3|
385.2J
3.9J
0.4!
O.lj
17.9!
105.5!
334.5!
2271.0!
34.2,'
88.4[
3.0!
3.9!
0.4!
15.8!
7.6!
1.7|
1.8!
0.7!
135.2!
16.6|
124.4J
10. 4 !
18408.7!
33.0{
726.2J
7.0!
220.5J
0.7!
3.6!
4.7!
26.8!
3.8!
37.3J
241.1!
27.0!
2.3!
70.9J
25.1J
43.0[
Area j j
(ha) {Area (ha) J
.j. i
Total !
i
i
1.3!
o.o;
i.i!
O.OJ
o.o!
0.0|
0.1|
0.3!
i.os
6.5!
o.i!
0.3!
o.o!
o.o;
loo.o!
58.8!
28.4!
6.2J
6.6!
o.o!
0.6[
o.i!
0.6!
o.oj
86.4!
0.2!
3.4!
O.OJ
i.o!
o.o!
o.o!
o.o!
o.i!
O.OJ
0.2!
i.i!
o.i!
O.OJ
0.3!
o.ii
0.2!
MEAN i
_ i
t
i
t
4.03!
1.14J
2.02{
0.56J
0.45!
0.07!
2.98J
6.60!
3.38J
1.82J
1.22!
2.01!
0.43J
0.66!
0.42J
3.16J
7.65J
1.67J
0.88[
0.67!
6.76!
8.28!
4.15J
2.61J
8.18J
3.30[
11.71!
1.39J
2.94J
0.35[
3.55!
2.34J
26.76!
3.79J
7.47 j
20.09J
9.00!
2.31J
3.08]
5.01!
10.74!
47
-------
Illinois Region
EMAP
PFO/SSCR
PFO/SSC
NWI
PSS1C
PSS1CD
PSS1CH
PSS1F
PSS1FD
PSS1FH
PSS1FX
PFO/EMC
PFO/SS1C
PFO/SS1F
PFO/UBGH
PF01/5F
PFO1/EMC
PFO1/EMF
PF01/OWF
PF01/UBF
PF01C
PFOICD
PF01CDH
PFO1CH
PFO1CX
PFO1F
PF01FD
PFO1FH
PFO1FX
PF01GH
PFO2/SS1
PF02C
PF02F
PF02FH
PFO5/6G
PF05/AB4
PF05/OWF
PFO5/SS1
PF05F
PFO5FH
PFO5G
PFO5GH
PF06/AB4
PF06C
PF06F
i
i
i
i
i
i
Number \
i
i
251!
2j
3!
25',
1!
15j
i!
i!
66j
2j
i!
2!
104!
43 j
2!
7!
4045!
91!
5!
196!
39}
376J
3!
43!
9!
1!
i!
i!
2!
2)
i!
i!
2!
i!
7!
3!
4!
3!
i!
H
76|
!
Psjrcsnt |
Number {
i
i
8.9J
O.lj
o.i!
0.9!
o.oj
0.5!
o.o!
o.oj
i.o!
o.o!
o.o!
o.o!
1.6!
0.6!
o.o!
o.i!
60.4!
1.4!
o.i!
2.9!
0.6!
5.6!
o.o!
0.6!
o.i!
o.oj
o.o!
o.o!
o.oi
o.o|
o.o!
o.o!
o.o!
o.o!
o.i!
o.oj
o.i!
o.o!
o.o!
o.o!
i.i!
Area j
(ha) j
Total !
i
i
828.5J
17. 9j
18. 9 j
225.1!
1-1!
33.9J
2.7J
0.6,'
322.2J
19.5!
0.7!
10.7[
220. Oj
95.3[
3.6J
62.8|
12753.0!
192.1!
10.5j
375.2!
55.3]
988.9!
1.2]
106. 4j
20.4J
3.4!
0.8!
0.6[
34.3J
5.8!
31.0!
0.4[
i-i!
20.4!
19.5!
1.8!
16.6!
4.3|
26.9J
1.8!
1303.0!
Area j
(ha) {A
% Total!
i
i
3.9J
0.1!
O.lj
l.lj
O.Oj
0.2J
o.o!
o.o[
1.6J
o. i j
o.oj
o. i [
i.ij
0.5!
O.Oj
0.3[
65.3!
i. o j
o.i!
1-9!
0.3!
5.1!
o.o!
0.5!
o.i!
o.o!
o.o!
o.oj
0.2 j
o.o!
0.2!
o.o[
o.oj
o.i!
o.i!
o.o[
o.i!
o.oj
o.i!
o.o!
6.7!
rea (ha) !
_ i
i
MEAN j
i
i
3.30J
8.93J
6.29J
9.001
1.06J
2.26|
2.73!
0.60|
4.88!
9.75J
0.67!
5.37,1
2.12!
2.22!
1.79]
8.97,'
3.15!
2.11!
2.09!
1.91!
1.42 !
2.63!
0.39|
2.47!
2.27)
3.40!
0.80!
o.eoj
17.13!
2.90!
30.96J
0.45!
0.53!
20.44!
2.79!
0.62!
4.14!
1.43]
26.92 !
1.76,'
17.14!
48
-------
Illinois Region
EMAP NWI
PFO/SSC PFO6FD
PFO6FH
PFO6G
PFOC
PSS/EM1F
PSS/EMC
PSS/EMF
PSS/FO1C
PSS/FO1F
PSS1/AB4
PSS1/ABF
PSS1/EM2
PSSl/EMC
PSSl/EMF
PSS1/F05
PSS1C
PSS1CD
PSS1CDH
PSS1CH
PSS1CX
PSS1F
PSS1FD
PSS1FH
PSS1FX
PSS5F
PSSCD
PSSF
PL L2EM/UBG
L2EM2G
L2EM2GH
L2EMGH
PAB3F
PAB3FH
PAB4/SS1
PAB4F
PAB4FH
PAB4GH
PABF
PABFH
PABGH
PABHH
i
i
i
i
Number j
i
i
i!
4|
2!
i!
4!
4!
i!
31!
i!
2!
c 1
-> 1
-1 1
-1- 1
149!
1 Q '
-1- ^ 1
6!
968!
42',
2!
45!
12 J
205|
6!
31!
14 ',
1!
i!
i!
2!
3!
7 '
' 1
5|
i j
2|
i 1
J- 1
c 1
3 1
O 1
^ 1
1 1
-1- 1
2!
4!
13!
i!
t
1
1
1
Percent j
Number ]
o.o!
o.ij
o.o!
o.o!
o.i!
o.i!
o.o!
0.5!
o.o!
o.o!
o.i!
o.o1,
2.2!
0.3',
o.i!
14.4!
0.6!
o.o!
0.7!
0.2 J
3.1!
o.i!
0.5)
0.2!
o.o!
o.o|
o.o!
o.i!
o.i!
0.2!
o.i!
o.o!
o.i!
o.o!
o.i!
o.i!
o.o!
o.ij
o.i!
0.4!
o.o!
Area
(ha)
Total
2.1
41.7
73.0
0.2
17.1
4.7
4.6
91.5
61.1
2.1
4.3
2.7
503.9
97.7
8.5
1236.5
83.5
2.3
49.5
11.5
462.1
3.5
42.8
9.4
1.6
0.7
0.6
58.2
183.9
20.8
47.2
0.3
10.6
4.0
6.1
0.3
0.8
2.9
6.4
30.8
2.3
j Area
I (ha)
|% Total
i
i
i o.o
i 0.2
! 0.4
! o.o
! o.i
! o.o
! o.o
! 0.5
! 0.3
! o.o
j 0.0
! o.o
! 2.6
! 0.5
! o.o
! 6.3
! 0.4
! o.o
! 0.3
i o.i
! 2.4
! o.o
! 0.2
! o.o
i o.o
! o.o
! o.o
! 0.3
! i.o
! o.i
j 0.3
! o.o
! o.i
! o.o
! o.o
! o.o
! o.o
! o.o
! o.o
! 0.2
j o.o
', Area ( ha ) j
! MEAN [
i i
i i
! 2.io!
! 10.43J
! 36.51!
! 0.16!
! 4.29!
! 1-17!
! 4.60!
! 2.95',
! 61.14!
! 1-07!
! 0.87!
! 2.65J
! 3.38!
! 5.14!
! 1-42!
! 1-28!
! 1.99!
! 1-13!
! i.io!
! 0.96!
! 2.25!
! 0.58!
! 1.38!
! 0.67)
! 1.58!
! 0.70!
i 0.61!
! 29.09!
! 61.32J
! 2.98!
I 9.43!
! 0.34!
! 5.30J
i 4.03|
1 1 00 1
1 -L ^-3 1
! o.i7!
! 0.85}
! 1-45!
i 1.59!
! 2.37!
! 2.26!
49
-------
Illinois Region
EMAP NWI
PL PEM/AB3F
PEM/AB4F
PEM/ABGH
PEM/FO1A
PEM/FO1C
PEM/F01F
PEM/OWF
PEM/SS1A
PEM/SS1C
PEM/SS1F
PEM/UBFX
PEM1A
PEM1AH
PEM1CH
PEM1FH
PEM2G
PEM2GH
PEMA
PEMAD
PEMAF
PEMAFH
PEMAH
PEMAHF
PEMAX
PEMBD
PEMC
PEMCD
PEMCF
PEMCH
PEMCHX
PEMCX
PEMF
PEMFD
PEMFH
PEMFX
PEMGH
PFO/EM1C
PFO/SS1A
PFO/SS1C
PFO/SS1F
PFO1/EMA
i
t
i
i
i
Number |
i
i
i!
2!
i!
2!
12|
41
i!
9!
29{
27|
IS
2!
i!
2|
4!
i!
9 1
^ 1
28}
3!
5|
5!
89|
2!
4!
i!
92!
4!
i!
305!
i!
28!
47!
i!
247|
20|
2!
i!
3!
9i
8!
5!
1
1
1
1
Percent ]
Number j
i
i
o.o!
o.i!
o.o!
O.lj
0.3!
o.i!
O.Oj
0.3!
0.8[
0.8!
O.Oj
o.i!
o.o!
o.i!
O.lj
o.o!
o.i!
0.8!
o.i!
O.lj
o.i!
2.6J
o.i!
o.i!
o.o!
2.6!
O.lj
o.o!
8.7!
o.o!
0.8J
1.3!
o.o!
7.1!
0.6!
o.i!
O.Oj
o.i!
0.3J
0.2J
O.lj
Area j
(ha) j
Total j
i
i
46.8J
0.9!
5.5J
6.8J
44.4|
8.2!
0.3|
17.8J
77.5|
154.2!
5.9!
15. 9j
0.3!
2.5J
8.2!
0.3|
1.5J
44.8!
5.1|
15.1J
27. 7!
132.7J
8.6!
a o 1
j . y ,
60.4J
307. 6!
43.4!
2.0!
643.8J
0.4!
23.3J
268.2J
6.3J
580.6!
32. 9j
11.1!
0.1!
19. 8 j
45.4|
91.8|
13.6!
Area |
(ha) [
i
% Total!
i
i
0.3!
o.oj
o.o!
o.oj
0.2[
o.o!
o.oj
o.i!
0.4J
0.8!
o.o!
O.lJ
o.o!
o.o!
o.o!
o.o!
o.o!
0.2J
o.o!
o.i!
o.i!
0.7!
o.o!
o.o!
0.3J
1.7!
0.2|
o.o!
3.5|
o.o!
o.i!
1.5!
o.o!
3.1|
0.2!
o.i!
o.o!
o.i)
0.2|
0.5|
o.i!
i
Area (ha) [
i
i
MEAN !
i
i
!
46.77!
0.44J
5.46J
3.41!
3.70,'
2.06!
0.29!
1.98[
2.67J
5.71[
5.93!
7.95!
0.25!
1.25J
2.05J
0.30J
0.73!
1.60J
1.69!
3.02!
5.53!
1.49J
4.30,'
0.98!
60.40!
3.34!
10.85!
1.95J
2.11,'
0.38!
0.83J
5.71!
6.29J
2.35[
1.65]
5.53j
0.14J
6.59!
5.04!
11.47!
2.73|
50
-------
Illinois Region
EMAP NWI
PL PF01/EMC
PF01/EMF
PFO1/UBF
PF01A
PF01AH
PF01C
PFO1CH
PFO1CHX
PF01CX
PFO1F
PF01FH
PFO1FX
PF02/UBG
PFO5F
PF05FH
PFO5GH
PF05GX
PFO5HH
PFO6/UBG
PF06C
PF06F
PF06G
PFOAH
POW/EMF
POW/F05F
POWF
POWGX
POWH
POWHX
PSS/FO1A
PSS/FO1C
PSS/F01F
PSS1/EMA
PSSl/EMC
PSS1/EMF
PSS1A
PSS1AH
PSS1AX
PSS1C
PSS1CH
PSS1CX
i
i
i
Number j
H i
i
28!
38',
10 i
232 i
565|
134',
685J
1!
2!
22 j
74|
1!
2|
i!
4|
2|
i!
12!
2!
2!
io[
6!
1 1
-1- 1
i!
i!
J 1
* 1
0 1
* 1
1 1
-1- 1
1 1
-3 1
U
4|
22j
i!
23|
35!
25!
35]
3!
33!
106J
3!
i
i
Percent i
Number j
+_
i
0.81
i-i!
0.3J
6.6|
16.2J
3.8J
19.61
O.Oj
0.11
0.6|
2.1J
0.01
o.ij
0.0',
o.i!
o.il
O.Oj
0.3!
o.i!
o.il
0.3!
0.21
o.oi
o.oi
O.Oj
o.ii
o.i!
o.ol
o.ii
o.oi
o.ij
0.61
o.oi
0.7!
i.ol
0.71
1.01
o.il
0.9!
3.0!
o.il
Area 1
(ha) !
Total j
!
51.5!
115.6!
44.5!
2142.9J
4156.61,
1019.2!
4302.6!
0.2J
0.6!
76.5J
705.2J
2.4|
0.7]
12.2!
21.0!
10.5!
51.2!
115.8!
13.0!
42.7!
65.7[
342.8J
0.2|
0.9!
1.1!
0.5!
0.3J
0.4!
0.6!
1.8!
3.4!
142.7!
4.8J
140.0J
356.0!
68.1!
74.8!
3.2!
213.5{
256.7!
4.9!
Area j
(ha) !
% Total!
i
i
0.3!
0.6!
0.2!
11.6!
22.5!
5.5J
23.3!
0.0!
o.o!
0.4!
3.8!
o.o!
o.o!
o.i!
o.i!
o.i!
0.3j
0.6J
o.i!
0.2]
0.4|
1.9J
o.o!
o.o!
o.o,1
o.o!
o.o!
o.o!
o.o!
o.o!
o.o!
0.8J
o.o|
0.8!
1.9!
0.4!
0.4|
o.o!
1.2J
1.4|
o.o!
i
Area (ha) j
i
MEAN J
_ _ i
i
i
i
1.84J
3.04!
4.45J
9.24J
7.36J
7.61!
6.28!
0.23J
0.30!
3.48!
9.53J
2.42J
0.36!
12.20!
5.26!
5.26!
51.24',
9.65J
6.52!
21.36J
6.57[
57.13J
0.24!
0.91!
1.09!
0.27[
0.17J
0.40!
0.19!
1.79J
0.84!
6.49,'
4.85!
6.09!
10.17J
2.72!
2.14J
1.05!
6.47!
2.42[
1.65J
51
-------
Illinois Region
EMAP
PL
PS
NWI
PSS1F
PSS1FH
PSS1FX
PSSCH
PUB/ABG
PUBF
PUBFH
PUBG
PUBGH
PUBGHX
PUBGX
PUSCH
PUSCX
PAB/EMF
PAB/FO5F
PAB/OWF
PAB/OWFH
PAB/OWG
PAB/OWGH
PAB/OWH
PAB/OWHH
PAB/OWHX
PAB/UBFX
PAB/UBGH
PAB/UBGX
PAB1F
PAB2C
PAB2GX
PAB3F
PAB3FH
PAB3FX
PAB3G
PAB3GH
PAB3GX
PAB4/3G
PAB4/EMF
PAB4/FO1
PAB4/FO5
PAB4/F06
PAB4/OWF
PAB4/OWG
Number
9
132
3
1
3
8
26
11
68
6
23
1
1
5
3
9
1
1
1
1
1
1
]_
3
1
1
1
1
86
20
2
45
215
35
2
7
1
1
1
10
1
i i
i i
i i
i i
i Percent | *
| Number |
i i
i i
! 0.3|
! 3.8J
i o.ij
! o.oj
! o.i!
! 0.2!
! o.7!
! o.3!
! i.9|
! 0.2!
! o.7|
! o.oj
! o.o[
! o.o!
! o.oj
! o.o!
! o.o[
i o.oj
! o.o!
! o.o!
! o.o!
! o.o!
! o.o|
! o.o!
! o.oj
i o.o[
! o.o!
! o.o!
! o.ij
! o.o!
! o.o!
! o.i!
i 0.4|
i o.i!
! o.o!
! o.o|
1 o.o!
! o.o!
i o.o!
! o.o!
! o.o|
Area j
(ha) [
Total !
i
i
75.3J
435.1J
3.5!
0.4J
15.8!
5.6J
29.8!
20.5!
108.7!
5.6!
30.9|
1.6!
3.1!
8.2!
3.5|
11.9!
0.9!
0.41,
4.4|
0.3J
0.2[
i.oj
6.4!
0.5!
0.3[
0.2!
0.8!
0.5!
80.0!
4.4!
0.6!
50.4!
78.5!
15.0!
4.7!
3.9!
1.6!
0.4!
21.9!
7.7|
0.9!
Area j
(ha) !
% Total!
i
i
0.4!
2.4!
o.oj
o.o!
o.i[
o.o!
0.2!
o.i!
0.6J
o.o!
0.2!
o.o!
o.o!
o.o|
o.o!
o.o!
o.o!
o.o|
o.o[
o.o!
o.o!
o.o!
o.o!
o.o!
O.Oj
o.o!
o.o|
o.o|
0.3!
o.o!
o.o!
0.2|
0.3|
o.i!
o.o!
o.o|
o.o|
o.o|
o.i!
o.o!
o.o!
i
i
Area (ha) \
_ i
i
MEAN [
i
8.3?!
3.30|
1.16!
0.45',
5.28!
0.71!
1.15!
1.86!
1.60!
0.94!
1.34!
1.59!
3.14!
1.64J
1.17!
1.32J
0.90J
0.38J
4.38J
0.31J
0.23!
l.Olj
6.36!
0.16!
0.33!
0.21!
0.80|
0.51J
0.93!
0.22[
0.28!
1.12!
0.37!
0.43!
2.36!
0.56!
1.65|
0.41',
21.91!
0.77!
0.88!
52
-------
Illinois Region
EMAP NWI
PS PAB4/OWH
PAB4/SS5
PAB4/UBG
PAB4F
PAB4FH
PAB4FX
PAB4G
PAB4GH
PAB4GX
PAB4H
PAB4HH
PAB4HX
PAB6GH
PABF
PABFD
PABFH
PABFX
PABG
PABGD
PABGDH
PABGH
PABGX
PABH
PABHH
PABHX
POW/AB4F
POW/AB4G
POW/AB4H
POW/ABF
POW/ABFD
POW/ABFH
POW/ABFX
POW/ABG
POW/ABGX
POW/ABH
POW/ABHH
POW/ABHX
POW/EMF
POW/EMFH
POW/EMFX
POW/EMG
Number
3
2
1
201
25
9
32
140
64
6
1
4
1
382
10
158
61
189
4
1
694
178
6
4
2
15
8
3
48
1
1
2
8
6
2
1
cr
31
o
4
1
i i
i i
i i
i i
I Percent |
! Number |
+ i
1 1
1 1
! o.o!
! o.o:
! o.o!
! o.3|
! o.o!
! o.o!
i r\ i i
1 U. 1 |
i n ? '
1 U. ^ i
! o.i!
! o.o!
I o.oj
! o.o!
! o.o!
! 0.6!
! o.o!
i n T '
1 U. J |
i n 1 !
1 U . 1 |
I 0.3|
! o.o:
! o.o!
! 1.2!
! o.3|
! o.o!
! o.o:
! o.oj
! o.o!
! o.o:
! o.ol
! o.i!
! o.o!
! o.o!
! o.ol
! o.oi
! o.o:
i o.o!
! o.o:
i o.o:
: o.ii
: o.oj
! o.o!
i o.o:
Area ',
(ha) i
Total !
1
1
1.8J
6.5!
0.4J
88.5!
3.4!
3.5!
31. 4j
37. 9 1
19.9J
10. 7 j
0.3!
1.0',
1.0!
195.3J
14.7[
19.2 j
14.3!
210. 7j
2.0|
4.4!
208.8!
77. 5|
7.0[
1.6!
O.lj
15.2!
4.7!
0.9[
22.6J
0.5]
1.9!
0.6J
9.0[
5.6J
3.5!
0.4!
1.9!
28.9]
1.7|
i.o!
1.9J
Area
(ha)
% Total
0.0
0.0
0.0
0.4
0.0
0.0
0.1
0.2
0.1
0.0
0.0
0.0
0.0
0.8
0.1
0.1
0.1
0.8
0.0
0.0
0.8
0.3
0.0
0.0
0.0
0.1
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
1
1
Area (ha) [
h i
MEAN !
L 1
1
1
1
0.59!
3.27!
0.38!
0.44|
0.13J
0.38J
0.98!
0.27!
0.31!
1.78!
0.32!
0.25!
i.oo!
0.51!
1.47!
0.12!
0.23',
i.ii!
0.51!
4.35',
0.30!
0.44!
1.17!
0.40!
0.07J
i.oi!
0.59J
0.31!
0.47!
0.54J
1.87J
0.29!
1.12!
0.93!
1.74',
0.44!
0.38!
0.93J
0.56!
0.26!
1.90!
53
-------
Illinois Region
EMAP NWI
PS POW/EMGH
POW/F05F
POWF
POWFD
POWFH
POWFX
POWG
POWGH
POWGX
POWH
POWHH
POWHX
POWHXD
PUB/AB3G
PUB/AB4G
PUB/ABF
PUB/ABGH
PUB/ABGX
PUB/EM2F
PUB/EM2G
PUB/EMF
PUB/FO1F
PUB/FO5G
PUB/SS1F
PUBA
PUBAH
PUBCH
PUBCX
PUBF
PUBFD
PUBFH
PUBFHX
PUBFX
PUBG
PUBGB
PUBGD
PUBGDH
PUBGF
PUBGH
PUBGHR
PUBGHX
i
i
i
i
i
i
Number |
i
i
3 1
J 1
-1 1
J 1
532|
2!
9!
66|
114!
102|
1134!
227!
332',
1951!
1!
1!
4!
2!
12!
2!
i!
i!
2!
i!
3!
i!
i!
i!
i!
i!
1297]
22]
2530]
2!
1590|
2351|
1!
4]
2]
3]
33256
1
io|
i
i
i
i
Percent | ~
Number [
i
i
o.o!
o.o!
0.9[
o.o1,
o.o!
o.i!
0.2!
0.2[
1 Q '
x. y ,
0.4J
0.6|
3.3!
o.oj
o.o!
o.oj
o.o[
o.o!
o.o!
o.o!
o.oj
o.o[
o.o!
o.o!
o.o!
o.o!
o.oj
o.oj
o.o!
2.2J
o.o[
4.2|
o.oj
2.7|
3.9!
o.oj
o.o[
o.o!
O.OJ
55.8[
o.o!
o.o!
Area '
(ha) !
i
Total i
i
i
4.5!
2.3J
131. 3j
1.3',
2.1J
16.6!
70.2]
37. 9j
461.5!
187. 4j
251.3|
1278.5J
O.OJ
0.8!
J 0 1
jL . J |
0.7J
11.6|
13.3!
0.9!
1.9J
41. 8j
13.6J
9.2!
0.3J
11.9J
0.6J
0.9!
0.5J
606.1,'
33.5J
273.8!
4.7J
339.8!
1379.7!
0.1]
2.1]
4.0!
0.3]
10906.3]
0.8|
4.2J
Area j
(ha) [
i
% Total]
i
o.oj
o.o!
0.5!
o.oi
o.o!
o.ij
0.3!
0.2!
1.8!
0.7[
i.o!
5.1!
o.o!
o.o|
o.o!
o.o!
o.o!
0.1]
0.0]
0.0]
0.2]
0.1]
0.0]
o.o!
O.OJ
o.o!
O.o|
o.o!
2.4|
o.i!
i.i!
o.o
1-4!
5.5!
0.0
0.0
0.0
0.0
43.5
0.0
0.0
Area (ha) i
~ ~ i
MEAN i
i
i
i
i
1.51!
0.77J
0.25J
0.64!
0.23!
0.25!
0.62!
0.37,'
0.41j
0.83!
0.76]
0.66!
O.Olj
0.85!
0.58!
0.34,'
0.97J
6.63J
0.91J
1.90!
20.92J
13.63!
3.08!
0.34!
11.92J
0.60!
0.87!
0.49 j
0.47[
1.52J
0.11[
2.37J
0.21J
0.59!
0.11!
0.51!
1.98J
O.llj
0.33!
0.78!
0.42,'
54
-------
Illinois Region
EMAP NWI
PS PUBGX
PUSH
PUBHH
PUBHX
PUBKH
PUS/EMAH
PUS2/EMC
PUS2/EMF
PUSA
PUSAH
PUSAX
POSC
PUSCH
PUSCX
POSFX
POSGH
Number
10812
29
93
214
5
1
2
2
10
3
8
10
18
63
1
1
i i
i i
i i
i i
i Percent |
! Number J
i i
i i
i 18.1|
0.0!
! o.2!
i 0.4!
! o.o|
! o.o!
! o.o!
! o.o!
i o.o!
i o.oj
! o.o|
! o.oj
i o.oi
! o.i!
! o.o!
! o.o!
Area
(ha)
Total
6795.7
49.5
173.5
506.2
2.6
1.6
0.3
0.9
3.9
0.9
7.9
10.0
9.8
39.5
0.7
0.3
! Area !
! (ha) !
+ i
|% Total!
i i
i i
i 27.1!
0.2!
! o.7!
! 2.0J
! o.oi
! o.o!
! o.oj
! o.oi
! o.oj
i o.oj
! o.oi
! o.o!
! o.o!
! o.2i
i o.oj
! o.oj
Area (ha) j
MEAN J
i
i
i
0.63|
1.71|
1.87',
2.37',
0.51J
1.59!
0.16]
0.43|
0.39',
0.30|
0.99',
1.00!
0.54J
0.63J
0.74!
0.30J
55
-------
Appendix D
Table summarizing the EMAP classes after aggregating the NWI
classes for the Washington region
56
-------
Table D. Summary of NWI classes mapped to each EMAP class for the Washington
Region.
EMAP
E2EM
PEMAR
PEMA
PEMBR
PEMB
PEMCR
NWI
E2EM/ABN
E2EM/USN
E2EM1N
E2EM1P
E2EMN
E2EMP
PEM/SS1A
PEM/SSA
PEM1A
PEM1W
PEMA
PEMAD
PEMAH
PEMS
PEM/FO1A
PEM/FO1W
PEM/FOA
PEM/SS1A
PEM/SSA
PEM/SSAD
PEM1A
PEM1W
PEM1WD
PEM1WX
PEMA
PEMAD
PEMAH
PEMAX
PEMJ
PEM1/FO4
PEM1B
PEMB
PEM/SSB
PEM1B
PEMB
PEM/ABF
PEM/ABH
PEM/OWF
PEM/SS1Y
PEM/SSC
PEM/SSCB
PEM/SSF
Number
1
21
14
3
119
24
1
1
6
31
217
11
1
2
2
1
1
2
7
2
67
269
6
1
1071
78
16
1
2
3
9
26
2
121
89
2
3
4
3
13
6
6
i i
i i
i i
i i
! Percent | -
! Number |
i i
i i
! o.5!
! 11-5!
! 7.7|
! 1.6!
! 65.4!
! 13.2!
! o.4[
! o.4!
i 2.3!
! ii.5[
i 80.2!
! 4.1!
! o.4j
! 0.8!
! o.i!
! o.i[
! o.i!
! o.i!
! o.4[
! o.ij
! 4.4!
! 17.6!
! 0.4!
! o.i!
! 70.2!
! s.i!
! i.o!
! o.i!
! o.i!
! 6.8!
! 23.8!
! 69.4!
i i.o!
! 57.1!
! 41.9!
! o.i!
! o.2!
! o.2!
! 0.2!
! 0.7!
! o.3!
! o.3[
Area
(ha)
Total
2.3
83.7
45.3
3.6
434.7
39.1
13.1
0.7
47.0
64.2
809.8
84.0
0.8
5.0
5.9
1.0
0.5
7.6
25.8
3.1
657.8
292.4
13.7
0.9
2031.0
706.9
140.8
0.4
63.1
3.0
6.7
3.1
5.3
171.1
23.8
32.6
60.5
4.7
112.8
188.4
11.4
10.2
! Area
! (ha)
i
i
!% Total
1
1
1
! 0.4
! 13.7
! 7.4
! 0.6
i 71.4
! 6.4
! 1.3
0.1
! 4.6
! 6.3
! 79.0
! 8.2
! 0.1
! 0.5
! o.i
! o.o
! o.o
! 0.2
i 0.7
! o.i
i 16.7
! 7.4
! 0.3
! o.o
! 51.4
! 17.9
! 3.6
! o.o
! 1.6
! 23.6
! 52.5
! 23.9
i ) 7
i * 1
\ 85.4
! 11.9
! 0.6
! 1.2
! 0.1
i -> )
i 4.4
! 3.6
! 0.2
! 0.2
1 1
1 1
[Area (ha) [
. i
+ i
J MEAN !
i
i i
i i
! 2.35]
! 3.98!
! 3.24!
! 1-19!
i 3.65[
{ 1.63!
! 13.10!
i 0.71!
I 7.84!
! 2.07|
! 3.99!
! 9.34!
! 0.76!
! 4.98!
! 2.94|
! i.oo!
! 0.54|
3.78!
! 6.46!
1 Til1
1 J -1-1- 1
! 12.65!
! 1-09!
! 2.28J
! 0.93!
! 2.03!
! 10.40!
! 11.73!
! 0.38|
! 63.09!
i 1.51!
! 0.96!
! o.i5!
! 5.33!
i 2.48|
! 0.42J
! 32.59!
! 30.23!
! 4.69!
i 37.59!
! 18.84!
1.90!
! 2.05|
57
-------
Washington Region
EMAP NWI
PEMCR PEM/SSFB
PEM/SSFH
PEM/SSR
PEM1/OWZ
PEM1C
PEM1CD
PEM1CH
PEM1F
PEM1FH
PEM1R
PEM1RD
PEM1Y
PEM1YD
PEM1YH
PEM1Z
PEMC
PEMCB
PEMCD
PEMCH
PEMCX
PEMF
PEMFB
PEMFH
PEMFX
PEMH
PEMHB
PEMR
PEMRS
PEMT
PEMY
PEMC PEM/ABF
PEM/ABH
PEM/FO1C
PEM/FO1Y
PEM/FOC
PEM/OWF
PEM/OWFH
PEM/OWH
PEM/OWZ
PEM/SS1C
i
i
i
i
i
Number j
1
ป
4!
i!
7!
i!
28[
2!
i!
i!
ii!
2{
i!
45 i
i!
i!
i!
1338J
24j
7!
28!
i '
' i
158|
31!
13!
8!
6!
3!
81!
2i
2!
i!
9!
13!
i|
2!
3!
7!
i!
18!
i!
12!
1
1
1
1
Percent | ~
Number \
\
\
0.2!
o.i!
0.4[
o.ij
1.5J
o.ij
o.i!
o.i!
0.6!
o.i!
o.i!
2.4J
o.i|
o.i!
o.ij
72.2!
1.3|
0.4J
1.5!
0.4J
8.5J
1.7J
0.7!
0.4[
0.3!
0.2!
4.4J
o.i!
o.i!
o.i!
o.i!
o.i!
o.o!
o.o!
o.o!
o.i!
o.o!
0.2[
o.o!
o.i!
Area \
(ha) [
_ i .
i
Total JS
i
i
6.0!
i.o!
30.2|
2.9!
65.1!
3.8J
0.3J
1.2!
30.4)
1-9!
3.9J
60.3J
4-5!
1.3!
0.2,'
3881.5!
13.4J
56.3|
247.9!
5.2J
127.7J
12.6J
6.2J
3.3!
4.3!
2.8!
224.2)
0.8!
1.1!
1.5|
22.4]
76.6!
2.6!
5.3!
25.9!
15.4!
0.2!
45.8!
1.4J
16.6}
Area \
(ha) !
k Total!
i
i
o.i!
o.oj
0.6,'
o.i!
1-2!
O.lj
o.oi
o.oj
0.6,1
o.o[
o.i!
1.2!
o.ij
O.OJ
o.o!
74.3[
0.3!
i.i!
4.7!
o.ij
2.4!
0.2|
o.i!
o.i!
o.i!
o.i!
4.3!
0.0]
o.o|
o.o|
0.2|
0.6]
o.o|
o.oj
0.2!
o.i!
o.o
0.4
o.oi
o.i!
i
i
Area (ha) ,'
_ i
MEAN !
i
i
i
i
6 . 00 ,'
1.04,'
10.07!
2.94J
2.60!
3.76!
0.32!
1.20!
30.37,'
0.97!
3.91!
1.34!
4.54,'
1.25J
0.22!
3.29J
0.56,'
8.04!
8.85!
0.74!
0.93J
0.45J
0.48!
0.42!
0.71,'
0.94J
5.34!
0.82!
1.06!
1.45J
2 . 80 ,'
6.38J
2.64!
2.65',
12.97|
2.20|
0.17J
3.06!
1.38!
8.29|
58
-------
Washington Region
EMAP
PEMC
PFO/SSAR
NWI
PEM/SSC
PEM/SSCB
PEM/SSCH
PEM/SSCX
PEM/SSF
PEM/SSFB
PEM/SSFH
PEM1/AB4
PEM1/OWY
PEM1/OWZ
PEM1C
PEM1F
PEM1FH
PEM1Y
PEM1YD
PEM1YH
PEM1Z
PEMC
PEMCB
PEMCD
PEMCH
PEMCHS
PEMCS
PEMCX
PEMF
PEMFB
PEMFH
PEMFX
PEMG
PEMGB
PEMGH
PEMH
PEMHB
PEMHH
PEMYD
PFO/EM1A
PFO/EMA
PFO/SS1A
PFO/SS1W
PFO/SSA
Number
72
10
1
2
34
4
3
6
56
10
165
22
2
484
4
17
18
6510
69
57
71
2
2
48
917
131
56
44
14
2
2
51
14
1
1
1
-I
4
5
11
i i
i i
i i
i Percent i ~
1 Number !
i i
i i
! 0.8 j
1 o.i1,
! o.o!
! o.o!
! 0.4;
1 o.o!
! o.oi
! o.i!
! 0.6!
! o.i!
! 1.8 [
! o.3!
! o.oj
! 5.4!
! o.o!
! 0.2!
1 0.2!
! 72.6!
! 0.8!
! 0.6!
! 0.8!
! o.o!
! o.o!
! o.5!
i 1 n 9 '
1 J.U.Z i
1 1. 5 J
] 0. 6 j
! 0.5,'
! 0.2!
! o.oj
! o.oj
! 0.6!
! 0.2!
! o.o!
! o.o!
! o.i!
! o.i!
! 0.2!
i n -a i
1 U.J i
j 0.6J
Area |
(ha) 1
_ _ _ i
Total [
i
218.4!
19.7]
2.4!
13.4!
114.5J
1.5[
4.5!
22.6!
60.6J
16.6!
373.6!
7.2!
0.3J
560.8!
20.7!
10.7!
23.3!
9690.5!
35.2J
231.0J
173.7)
3.9!
6.9}
21.3!
695.5!
36.9]
53.0J
33.5,'
12.8!
3.1!
4.5!
25.3!
15.8!
1.4!
1.4|
5.5!
1.3!
60.5!
43.7!
176.4J
Area
(ha)
% Total
1.7
0.2
0.0
0.1
0.9
0.0
0.0
0.2
0.5
0.1
2.9
0.1
0.0
4.4
0.2
0.1
0.2
76.1
0.3
1.8
1.4
0.0
0.1
0.2
5.5
0.3
0.4
0.3
0.1
0.0
0.0
0.2
0.1
0.0
0.0
0.1
0.0
1.1
0.8
3.3
! t
|Area (ha) \
+ i
1 MEAN !
i
i i
i i
! 3.58J
! 1.97i
' 9 AR '
1 ^.ซ3 (
1 13.42!
! 3.82!
1 1.53J
1 1.48J
1 3.76J
1 1.08!
1 1.66J
! 3.63J
! 0.38J
! o.i6!
! 1-191
1 5.17J
1 0.63[
1 1.30!
! 1.631
1 0.58j
1 4.621
i 2.52J
1 3.88J
! 6.89J
! 0.45[
1 0.80!
1 0.38!
1 1.08!
! 0.76|
! o.9i!
1 1.57!
i 2.24!
1 0.55!
i TIT1
i " -1--3 i
i 1-381
! 1.39J
! 5.52!
! 1.35J
! 20.18!
! 8.74!
! 25.191
59
-------
Washington Region
EMAP
PFO/SSAR
PFO/SSA
NWI
PF01A
PF01W
PFO4A
PFO4W
PFOA
PFOAH
PFOAS
PFOJ
PFOS
PSS/FOA
PSS1/FLW
PSS1A
PSS1W
PSS4/1W
PSSA
PFO/EM1A
PFO/EM1W
PFO/EMA
PFO/SS1A
PFO/SS1W
PFO/SSA
PF01/4A
PFO1/4W
PFO1/4WD
PFO1A
PFO1W
PFO4/1W
PFO4A
PFO4W
PFOA
PFOAD
PFOAH
PFOAX
PFOJS
PSS/EM1A
PSS/EM1W
PSS/EMA
PSS/FO1A
PSS/FOA
PSS1/4W
i
l
i
i
i
Number !
i
i
34!
1 1 "5 1
-L -LJ 1
i!
l!
1002 ,'
12!
i j
11 !
8!
4!
3!
li!
26!
1 1
530!
3!
3!
3!
io!
4!
5!
i!
6!
i!
51!
101!
4!
3!
9!
800!
i!
2!
2!
2!
21
2!
2!
1 1
i!
i!
1
1
1
1
Percent |
Number \
i
i
1.9 |
6.3!
o.i!
o.i!
56.3!
0.7!
o.i!
0.6!
0.5j
0.2!
0.2!
0.6J
1. 5 j
o.i!
29.8!
0.2J
0.2|
0.2!
0.7[
0.3|
0.3!
o.i!
0.4]
o.i!
3.5J
6.9|
0.3!
0.21
0.6!
55.0!
o. i !
o.i!
o.i!
o.i!
o.i!
o.i!
o.i!
o.i!
o.i!
o.i!
Area 1
(ha) 1
_. 1
Total 1
1
1
329.2!
464.3!
5.8!
o.o!
3063.7!
84. Ij
3.4!
361.1!
8.4!
14.2!
7.2!
13. 8j
49.2J
0.9!
701.5J
5.2[
27.2J
14.8!
57.3,'
8.1!
32.1',
O.Sj
33. 2j
11.3 !
83.1J
308.0!
20.3]
71.1!
21.7J
2346.0!
2.4!
6.0!
2.6!
24.0!
9.0!
3.3|
1.9!
0.7J
6.8]
1.5!
Area !
(ha) 1
% Total!
i
i
6.1!
8.6!
o.i!
o.o!
56.8!
1.6J
0. 1 i
6.7!
0.2!
0.3!
o.i!
0.3J
0.9!
o.o!
13.0J
o.i!
0.8!
0.4,'
1.6!
0.2|
0.9!
o.o!
0.9!
0.3!
2.3!
8.6J
0.6!
2.0!
0.6|
65.6,'
o.i!
0.2!
o.i!
0.7!
0.3!
o.i!
o.i!
0.0]
0.2]
o.oj
1
1
Area (ha) |
_ i
MEAN i
i
t
i
9.97J
4.22!
5.81J
0.00!
3.33!
7.64!
3.361
72.22!
1.20!
3.54!
2.40J
1.53J
1.89J
0.91!
1.47!
1.72J
9.08!
7.38!
5.731
2.02J
6.41!
0.50!
5.53J
11.32!
1. 81 1
3.05|
5.07J
35.56!
2.42!
3.56!
2.42|
2.98!
1.32!
23.96!
4.48J
1.64!
0.93|
0.66!
6.77J
1.46[
60
-------
Washington Region
EMAP NWI
PFO/SSA PSS1A
PSS1W
PSS4/1W
PSS4W
PSSA
PS SAD
PSSAX
PFO/SSBR PFO1B
PFOB
PSS1B
PSSB
PFO/SSB PFO1/4B
PF01B
PFO4/1B
PF04/EM1
PFO4B
PFOB
PSS/EM1B
PSS/EMB
PSS1B
PSS4/EM1
PSS4B
PSSB
PFO/SSCR PFO/EM1C
PFO/EM1Y
PFO/EMC
PFO/SS1Y
PFO/SSC
PFO/SSCH
PFO/SSF
PFO/SSR
PFO/USC
PFO1/4Y
PF01/FLY
PF01/OWY
PFO1C
PFO1R
PF01Y
PFO4/1C
PFO4/5C
Number
11
85
2
6
325
3
3
1
T
1
9
3
4
5
1
21
33
1
1
12
7
-i
41
3
1
4
10
26
1
4
2
2
2
1
1
15
3
80
11
3
Percent
Number
0.8
5.8
0.1
0.4
22.3
0.2
0.2
8.8
20.9
8.8
61.5
2.0
2.9
3.5
1.0
15.9
25.9
0.8
0.8
9.2
5.5
1.0
31.6
0.1
0.0
0.1
0.2
0.6
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.3
0.1
1.8
0.2
0.1
Area
(ha)
Total
9.3
86.6
4.4
10.5
357.1
6.0
2.7
0.2
1.5
2.3
2.2
1.0
3.7
43.0
5.0
43.1
10.5
0.7
0.8
2.8
8.5
0.2
10.8
1.2
4.5
17.0
48.5
186.2
28.0
6.8
10.2
2.0
24.9
4.4
7.7
15.4
9.9
360.7
18.2
1.7
Area | |
(ha) jArea (ha) [
i i
T i
% Total ! MEAN !
h + '
1 1
1 1
0.3! 0.93J
2.4! 1.02J
0.1! 2.22]
0.3! 1.75[
lo.o! 1.17]
0.2! 1.99[
0.1! 0.89j
3.8! 0.24!
23.8! 0.49!
37.2! 2.30!
35.2! 0.31!
0.8J 0.52!
2.9! 1.24!
33. Oj 10.75!
3.8! 4.98!
33. Ij 4.79!
8.1! 0.81!
0.6! 0.73!
0.6! 0.80!
2.1J 0.28!
6.5! 1.41!
o.i! o.i?!
8.3! 0.28!
0.0] 0.60!
0.0! 4.45]
0.2! 5.67]
0.5! 4.85!
2.0J 7.16J
0.3J 28.00!
0.1! 6.75]
o.i! lo.is!
o.oj i.oij
0.3! 12.47!
O.Oj 4.41]
O.lj 7.69!
0.2[ 1.19!
0.1! 3.30!
3.8J 4.51J
0.2! 18.22!
0.0! 0.86!
61
-------
Washington Region
EMAP
PFO/SSCR
PFO/SSC
NWI
PFO4C
PFO4Y
PFOC
PFOCB
PFOCD
PFOCH
PFOCS
PFOR
PSS/EM1C
PSS/EMC
PSS/EMCB
PSS/EMR
PSS/FO1C
PSS/FOC
PSS/USC
PSS1/4C
PSS1/4Y
PSS1/FLY
PSS1C
PSS1Y
PSS4/1Y
PSS5Z
PSS5ZH
PSSC
PSSCB
PSSCD
PSSCH
PS SCX
PSSF
PSSFB
PSSFH
PSSR
PSSY
PFO/ABHH
PFO/EM1C
PFO/EM1Y
PFO/EMC
PFO/SS1Y
PFO/SSC
PFO/SSCB
i
i
i
i
i
i
Number ]
1
1
13!
i!
739!
Ij
3!
i!
4!
29!
i!
15!
3!
2!
i!
151
10!
11
1
9 1
* 1
2!
5!
76!
31
5!
i!
3258!
21!
2!
27!
2!
9[
9!
2!
63|
i!
2!
2!
10!
10 !
12!
33!
i!
1
Percent |
Number j
i
0.3[
o.o!
16.4J
o.oj
o. i j
o.o!
o.i!
0.6|
o.oj
0.3 j
0.1'
o.oj
o.o[
0.3',
0.2!
o.o!
o.o!
o.oj
o.i!
1.7!
O.lj
O.lj
O.Oj
72.5!
0.5!
O.Oj
0.6[
O.Oj
0.2J
0.2J
O.Oj
1.4!
O.Oj
o.o!
o.o!
o.i!
o.i!
o.i!
0.4!
o.o!
Area j
(ha) J
i
Total !
i
i
10.6[
1.4J
2571. 6j
0.6!
14.6J
1.1!
2.0!
90. 2j
4.3J
135.5J
3.1!
1.1!
2.8[
58.1',
29. 2 j
0.5J
3.6!
5.0!
3.4|
184.4J
13. 3j
5.5!
0.2!
5095.7!
37.5J
35. Oj
90.6,'
5.8J
12.6!
4-3!
11.4!
251.7!
1. 6 j
6.2|
5.1!
32.2!
51.3|
58.0|
169.3|
1.9!
Area
(ha)
% Total
0.1
0.0
27.3
0.0
0.2
0.0
0.0
1.0
0.0
1.4
0.0
0.0
0.0
0.6
0.3
0.0
0.0
0.1
0.0
2.0
0.1
0.1
0.0
54.0
0.4
0.4
1.0
0.1
0.1
0.0
0.1
2.7
0.0
0.0
0.0
0.2
0.3
0.4
1.1
0.0
i i
i i
[Area (ha) j
.j. i
! MEAN !
^ i
i i
i i
! 3.55!
! 1.44!
! 3.91!
! 0.57|
! 4.85!
! i.os!
i 1.02!
! 5.31!
! 4.32!
! 12 . 31 !
! 1-03!
! 1.12!
! 2.81J
1 4.151
! 2.92J
! 0.49!
! 1.79J
1 0 C1 1
1 ^ >-! 1
i 0.68J
! 2.43|
! 4.43J
! i.ioj
j 0.21!
j 1.75}
i 1-78i
i 3^62!
! 2.88!
1 1. 41 !
! 0.48J
! 5.68!
! 5.99!
! 1.65!
! 6.24!
! 2.55!
! 3.22,'
! 6.41!
! 4.83|
! 7.70!
! 1-87!
62
-------
Washington Region
EMAP NWI
PFO/SSC PFO/SSF
PF01/4C
PFO1/4Y
PF01C
PFO1Y
PF04/1C
PFO4/1Y
PFO4/5C
PFO4/EM1
PFO4/SS1
PFO4C
PFO4Y
PF05/1Y
PFO5/4C
PF05/EM1
PFO5C
PFO5F
PF05Y
PF05Z
PF05ZH
PFOC
PFOCB
PFOCD
PFOCH
PFOCX
PFOF
PFOFH
PFOHH
PFOY
PSS/EM1C
PSS/EM1Y
PS S/ EMC
PSS/EMCB
PSS/EMF
PSS/EMFB
PSS/FOC
PSS/FOF
PSS/USCX
PSS1/4Y
PSS1/FLY
Number
1
17
10
79
128
6
26
7
1
1
26
43
1
4
1
4
3
1
14
1
1640
2
5
3
1
2
2
j
1
6
29
58
7
5
1
16
1
1
14
5
i
i
i
i
Percent (
Number |
i
i
o.o!
0.2|
o.i!
i.o!
1.6|
o.i!
0.3!
o.i|
o.o!
o.o|
0.3!
0.5|
o.o!
o.o!
o.o!
o.o!
o.o!
o.o!
0.2!
o.o!
20.3J
o.o!
o.i!
o.o!
o.o!
o.o!
o.o!
o.o!
o.o!
o.i!
0.4!
0.7J
o.i|
o.i!
o.o|
0.2|
O.Oj
o.o!
0.2!
o.i!
Area
(ha)
Total
1.9
59.9
118.3
79.0
214.4
38.6
124.0
6.4
3.3
4.4
71.0
91.6
3.7
1.7
1.1
1.0
0.3
4.7
26.3
0.5
5149.0
1.1
42.0
10.3
1.6
4.1
1.3
3.5
0.2
17.6
81.1
240.0
28.7
53.3
2.7
87.6
6.6
1.7
127.1
10.3
j Area
! (ha)
i _
i
!% Total
i
i
i o.o
! 0.4
! 0.7
! 0.5
! 1.4
! 0.2
! 0.8
! o.o
! o.o
! o.o
i 0.4
! 0.6
! o.o
! o.o
! o.o
! o.o
! o.o
! o.o
! 0.2
! o.o
! 32.5
! o.o
! 0.3
! o.i
! o.o
! o.o
! o.o
! o.o
! o.o
! o.i
! 0.5
! 1.5
! 0.2
! 0.3
! o.o
! 0.6
! o.o
! o.o
! 0.8
! o.i
i i
i i
jArea (ha) !
! MEAN i
i i
j 1.94!
! 4.28J
! 11.83!
i 1-58!
! 1-67!
i 7.73!
! 4.77J
! 1.07!
! 3.34!
! 4.40!
! 5.46!
j 2.13!
! 3.71!
! 0.57!
! i.os!
! 0.34!
! o.ie!
i 4.73!
! 1.88!
! 0.53!
! 3.36|
! 0.53[
i 8.39J
i 3.43!
! 1.59!
I 2.04J
j 0.64!
! 3.47J
j 0.18J
i 2.93!
j 2.80!
! 4.61!
! 4.ii!
! 13.33!
! 2.72 !
! 5.47!
! 6.63',
1 179'
1 ฑ . / Z ,
\ 9.08!
5.14!
63
-------
Washington Region
EMAP NWI
PFO/SSC PSS1/OWY
PSS1C
PSS1FH
PSS1Y
PSS1YB
PSS1YH
PSS3/EM1
PSS3Y
PSS4/1Y
PSS4C
PSS4Y
PSS5/EM1
PSS5/OWZ
PSS5Z
PSS5ZB
PSSC
PSSCB
PSSCD
PSSCH
PSSCX
PSSF
PSSFB
PSSFH
PL L2EM/OWF
L2EMFH
L2EMH
PAB/OWH
PABH
PEM/ABH
PEM/SSC
PEM/SSF
PEM1W
PEM1Y
PEM1YH
PEMA
PEMAH
PEMC
PEMCH
PEMCX
PEMF
i
l
i
i
i
i
Number '
I
I
2!
75!
.1!
308 j
i!
i!
i!
i!
20|
i!
23!
? '
* i
i!
41!
i|
5153|
78!
5|
22j
13|
831
12j
s!
i!
1 1
! 1
4|
i!
-) i
j i
i!
2!
8!
2!
10!
i!
2!
7!
84[
59|
i!
49j
1
1
Percent | *
Number !
j
0.0!
0.9!
O.Oj
3.8!
o.o!
o.o!
o.oj
o.o!
0.2!
o.o[
0.3!
o.o!
o.oj
0.5!
o.o!
63.6!
i.o!
o.i!
0.3!
0.2!
i.o!
o.i!
o.ij
0.2!
0.2!
0.7J
0.2|
0.5',
0.2!
0.4!
1.4!
0.4!
1.8!
0.2!
0.4!
1.3!
15.1!
10.5!
0.2!
8.8|
Area j
(ha) [
1
Total !
i
i
8.9!
51.8!
O.lj
511.6!
0.4!
1 7 '
ฑ. ฃ |
10.3J
1.3!
95.0!
1.7!
38.6[
0.9!
3.5!
40.7J
0.6!
7688.4!
150.2!
18.5!
25.3|
11.8!
134. 8 1
2.8!
11.8!
3.1!
4.6|
0.6J
0.9!
2.8]
4.3!
4.8[
21.3!
1.9!
27.6!
0.7!
0.5!
32.3J
299.4!
130.6|
1.6!
84.2!
Area j
(ha) !
% Total!
i
o.i!
0.3J
o.o!
3.2!
o.o!
o.oj
o.i!
o.o!
0.6!
o.o!
0.2!
o.o!
o.o!
0.3!
o.o!
48.5!
0.9!
o.i!
0.2J
o.i!
0.9',
o.o!
o.i!
0.2!
0.3!
o.o!
o.i!
0.2!
0.3!
0.3[
1-4!
o.i!
1.8!
o.o!
o.oj
2.1!
19.6!
8.6!
o.i!
5.5!
i
i
Area (ha) !
MEAN !
i
i
!
4.46J
3.24J
0.10!
1.71!
0.42!
1.18!
10.34!
1.25J
4.75}
1.68!
1.68!
0.43J
3.45!
1.13J
0.61J
1.63!
2.21|
3.70!
1.20!
0.91!
1.64J
0.24J
2.94|
3.14J
4.64!
0.14!
0.86[
0.951
4.28J
2.38!
3.04!
0.96!
2.76|
0.65!
0.23!
4.62J
3.84!
2.29!
1.63!
1.79J
64
-------
Washington Region
EMAP NWI
PL PEMFH
PEMH
PFO/EMC
PFO/SSC
PF01W
PF04A
PFOA
PFOAH
PFOC
PFOCH
POWH
POWHH
POWHX
POWZ
PSS/EMC
PSS/EMF
PSS/FOC
PSS1Y
PSS1YH
PSSA
PSSAH
PSSC
PSSCH
PSSCX
PSSF
PSSFH
PS PAB/EMF
PAB/EMH
PAB/EMHH
PAB/OWH
PAB/OWHX
PAB/USN
PAB4/OWH
PAB4/OWZ
PAB4Z
PAB5/OWZ
PABF
PABFB
PABFH
PABFX
i
i
i
i
i Percent
Number ] Number
i
i
12[ 2.1
3! 0.5
1| 0.2
5! 1.0
1| 0.2
l! 0.2
24] 4.2
6| 1.0
36! 6.5
9] 1.5
2 ! 0.4
l! 0.2
1] 0.2
2 j 0.4
11] 2.0
1] 0.2
l! 0.2
3] 0.5
2] 0.4
3! 0.5
2j 0.4
130] 23.2
59! 10.6
l! 0.2
5j 0.9
1] 0.2
5! 0.1
19,' 0.3
2] 0.0
19] 0.3
l! 0.0
1| 0.0
3| 0.1
2] 0.0
16| 0.3
l! 0.0
66| 1-1
10! 0.2
4] 0.1
5| 0.1
Area
(ha)
Total
,,,
19. 7
0.8
1.5
12.8
2.1
3.8
96.2
6.0
84.6
28.2
1.5
0.2
0.1
0.5
105.7
2.0
0.9
2.0
5.5
5.9
7.4
452.2
51.3
2.2
6.9
5.2
5.1
31.5
8.4
48.7
0.8
1.2
1.9
8.2
19.7
2.6
47.9
0.6
0.9
1.5
Area
(ha)
% Total
1.3
0.1
0.1
0.8
0.1
0.2
6.3
0.4
5.5
1.8
0.1
0.0
0.0
0.0
6.9
0.1
0.1
0.1
0.4
0.4
0.5
29.6
3.4
0.1
0.5
0.3
0.1
0.9
0.2
1.3
0.0
0.0
0.1
0.2
0.5
0.1
1.3
0.0
0.0
0.0
i
i
Area (ha) [
MEAN !
i
1.64!
0.28!
1.53!
4.26J
2.08!
3.78[
4.58]
1.19!
2.42|
9.40[
0.74J
0.20!
0.09[
0.26!
10.57J
1.95[
0.93!
0.67]
2.74!
1.96!
3.70!
3.65!
0.97!
2.20J
1.39!
5.16',
1.02!
1.75!
4.22!
2.57J
0.77!
1.16J
0.62!
4.09!
1.23|
2.60!
0.90j
0.06!
0.23!
0.31!
65
-------
Washington Region
EMAP NWI
PS PABG
PABH
PABHB
PABHH
PABHX
PFLW
POW/ABH
POW/ABHH
POW/ABHX
POW/EM1F
POW/EMH
POW/EMHB
POW/EMHX
POWAX
POWF
POWFB
POWFH
POWFX
POWG
POWGB
POWGX
POWH
POWHB
POWHH
POWHX
POWY
POWYH
POWZ
POWZB
POWZH
POWZX
PUBC
PUBCX
PUBF
PUBFB
PUBFH
PUBFX
PUBG
PUBGH
PUBGX
i
i
i
i
Number |
i
i
i!
279|
3!
25!
46!
1!
271
3!
6!
1!
7!
i!
3!
0 1
* 1
270J
15!
3!
27|
2!
5j
i!
2213J
26!
140!
423!
16!
2!
258!
3!
219!
17!
i!
3!
47!
9!
16j
48!
2!
3!
i!
i
i
i
i
Percent j -
Number 1 !
i
i
o.oj
4.8J
o.ij
0.4J
0.8J
o.o!
0.5!
o.i!
o.i[
o.oj
o.i!
o.oj
o.ij
o.o!
4.7!
0.3J
o.i!
0.5 j
o.o!
o.i!
o.o!
38.1!
0.4[
2.4!
7.3|
0.3j
o.o!
4.5!
o.i!
3.8!
0.3J
o.o!
o.i!
0.8!
0.2!
0.3!
0.8,'
o.o!
o.ij
o.oj
Area \
(ha) !
. 1
Total !
|
0.7J
269.7J
1.3!
18.4[
33.1,'
1.8J
44.8!
8.3J
4.7!
o.i!
4.2!
3.1!
0.9!
0.9!
54.3}
9.0!
0.8!
9.0J
0.6J
1.3!
o.i;
1328.2!
8.3[
57.3!
197.0J
4.3J
0.5J
216.6!
3.8!
119.7!
4.5!
0.2J
3.3J
15.4!
2.0]
4.7[
19.5|
5.0]
0.4|
0.4]
Area !
(ha) !
% Total]
i
o.o[
7.4!
o.oj
0.5J
0.9!
o.oj
1.2!
0.2!
o.i!
o.o!
o.i!
o.i!
o.o!
o.oi
1.5!
0.2!
o.o!
0.2]
o.oj
o.oj
o.o!
36.6!
0.2!
1.6[
5.4|
o.i!
o.o!
6.0]
0.1]
3.3!
o.i|
0.0|
0.1]
0.4]
o.i!
o.i!
0.5!
O.lj
0.0|
O.Oj
1
1
Area (ha) ]
_ _ i
MEAN i
_ _ i
i
i
0.74!
1.04|
0.44!
0.88!
0.72!
1.76!
2.04!
2.77,'
0.94J
0.11!
0.70|
3.12!
0.28!
0.90',
0.21|
1.80!
0.25!
0.35!
0.28|
0.25',
0.08!
0.64!
0.33J
0.50!
0.60!
0.27!
0.26!
0.94J
1.27!
0.55!
0.27!
0.16!
1.11!
0.33{
0.34!
0.30}
0.42[
2.49|
0.12!
0.41[
66
-------
Washington Region
EMAP NWI
PS PUBH
PUBHB
PUBHH
PUBHX
PUBHXR
PUSA
PUSC
PUSCH
PUSCS
PUSCX
PUSCXS
Number
464
40
183
485
2
8
219
4
10
53
1
i i
i i
i i
i i
| TJ-- f~lf^vi +- I
j Number \
\ 8.0 j
! 0.7J
! 3.i[
' 8.4!
! o.o!
! o.i!
! 3.8!
! o.i!
! 0.2!
! 0.9J
! o.o!
Area
(ha)
.
Total
387.8
6.3
59.8
244.7
0.9
22.5
165.2
1.2
69.3
30.0
0.2
Area
(ha)
% Total
10.7
0.2
1.6
6.8
0.0
0.6
4.6
0.0
1.9
0.8
0.0
i i
i i
!Area (ha) [
i i
j MEAN [
i i
! 0.86J
! 0.23J
! 0.34J
! 0.53!
! 0.43!
i 2.81',
! 0.79,'
! 0.40!
! 13.85!
! 0.62!
! 0.23!
67
-------
Appendix E
Table summarizing the EMAP classes after aggregating the NWI
classes for the Prairie Pothole region
68
-------
Table E. Summary of NWI classes mapped to each EMAP claos for the
Prairie Pothole Region.
EMAP
PEMAR
PEMA
PEMB
PEMCR
PEMC
NWI
PEM/FOA
PEMA
PEMAd
PEM/FOA
PEM/FOAD
PEM/FOAH
PEM/FOAd
PEM/SSA
PEM/SSAD
PEM1A
PEMA
PEMAD
PEMAH
PEMAX
PEMAd
PEMAh
PEMAx
PEMB
PEM/ABF
PEM/FOC
PEMC
PEM/ABF
PEM/ABFD
PEM/ABFH
PEM/ABFX
PEM/ABFd
PEM/ABFh
PEM/ABFx
PEM/FOC
PEM/FOCD
PEM/FOCH
PEM/FOCX
PEM/FOCd
PEM/FOCh
PEM/FOFH
PEM/SSC
PEM/UBFH
PEM/UBFX
PEM1C
PEM1F
PEMC
PEMCD
PEMCH
Number
56
57
2
119
6
1
1
15
1
3
77605
2048
52
25
818
6
3
2
12
16
84
3417
66
31
6
8
3
3
153
2
11
1
1
1
1
4
1
1
3
1
72007
986
96
i i
i i
i i
i i
i Percent i
i Number |
i i
i i
1 48. 7|
! 49.6|
! 1.7|
! o.i!
! o.oi
i o.o!
! o.oj
! o.o!
! o.oj
! o.o;
! 96.2|
! 2.5!
! o.i!
! o.o!
( i.oj
! o.o;
! o.o!
! loo.o!
1 10.7J
! 14.3!
! 75.0J
i 4.3J
! o.i!
! o.o!
! o.oj
! o.o!
! o.oj
i o.oj
I 0.21
! o.o!
! o.oi
! o.o!
! o.oi
! o.o!
! o.oi
! o.oi
i o.o!
! o.o!
! o.oi
! o.oj
! 90.6!
1 19"
1 ฑ. Z ,
\ o.i!
Area
(ha)
Total
298.3
517.4
14.0
91.2
64.9
7.8
43.4
15.5
1.4
0.6
63717.2
2696.1
114.7
10.6
724.1
1.8
0.3
48.0
271.3
55.1
2384.7
17434.1
545.6
140.5
2.3
31.2
5.7
0.5
143.1
19.9
23.6
0.6
3.1
0.7
1.4
4.8
2.3
0.8
0.5
14.2
73016.9
2037.3
190.7
! Area
! (ha)
i
!% Total
i
J 35.9
! 62.4
! 1.7
! o.i
! o.i
! o.o
! o.i
! o.o
! o.o
! o.o
! 94.4
! 4.0
j 0.2
! o.o
1.1
! o.o
i o.o
i 100.0
! 10.0
! 2.0
! 88.0
i 17.2
! 0.5
! o.i
! o.o
! o.o
! o.o
! o.o
! o.i
! o.o
i o.o
! o.o
! o.o
! o.o
! o.o
j o.o
! o.o
i o.o
! o.o
! o.o
! 71.9
! 2.0
! 0.2
Area (ha)
.
MEAN
5.33
9.08
7.02
0.77
10.81
7.84
43.36
1.04
1.35
0.21
0.82
1.32
2.21
0.42
0.89
0.29
0.10
23.98
22.61
3.44
28.39
5.10
8.27
4.53
0.38
3.90
1.91
0.16
0.94
9.96
2.15
0.57
3.08
0.71
1.37
1.19
2.29
0.79
0.18
14.23
1.01
2.07
1.99
69
-------
Prairie Pothole Region
EMAP
PEMC
PFO/SSAR
PFO/SSA
PFO/SSCR
PFO/SSC
NWI
PEMCX
PEMCd
PEMCh
PEMCx
PEMF
PEMFD
PEMFH
PEMFX
PEMFd
PEMFx
PFO/EMA
PFOA
PFO/EMA
PFO/EMAD
PFO/EMAX
PFO/SSA
PFO/SSAD
PF01A
PF01AH
PFOA
PFOAD
PFOAH
PFOAX
PFOAd
PFOAh
PSS/EMA
PSS/EMAD
PSS/FOA
PSS/FOAD
PSSA
PSSAD
PFO/EMC
PFOC
PFO/EMC
PFO/EMCH
PFO/EMCh
PFO/SSC
PFOC
PFOCD
PFOCH
PFOCd
i
i
i
i
i
i
Number j
i
98]
193 i
4|
12|
2243J
75|
23!
12 j
1!
1!
8!
84[
61!
3|
1!
2!
i1,
5!
2!
794!
8!
6!
i!
9!
2!
i!
i!
9!
i!
40|
2]
21!
57|
78|
i!
i!
i!
193
5
6
1
1
1
1
Percent j
Number j
I
i
i
o.i!
0.2J
o.oi
o.o[
2.8J
O.lj
o.o!
o.o[
o.o!
O.OJ
8.7J
91.3!
6.4[
0.3!
o.ij
0.2J
o.i!
0.5!
0.2J
83.7j
0.8J
0.6!
o.ij
0.9!
0.2J
o.i!
o.i[
0.9J
o.i!
4.2[
0.2!
26.9J
73.1!
26.1!
0.3J
0.3J
0.3!
64.5[
1.7|
2.0!
0.3J
Area |
(ha) !
Total !
i
i
77.2|
265.3!
4.1!
3.2!
7176.7!
364.2!
27.2!
12.1!
3.6!
1.4|
44.5!
141.2!
61.9!
8.4!
0.7|
1.2!
1.0!
2.4|
0.5!
269.6!
7.5!
3.1!
o.i!
2.71
0.2!
0.3J
0.7!
7.0|
1.5!
12.9J
C Q 1
o . y |
105.3!
loo.i!
117.0!
4.6|
0.6!
0.8!
100.5}
4.3!
6.8J
o.i!
Area !
(ha) !
- 1
% Total!
i
i
o.i!
0.3!
o.o!
o.o!
7.1!
0.4J
o.oj
o.o!
o.o!
o.oi
24.0!
76.0!
16.0!
2.2J
0.2!
0.3!
0.3J
0.6]
o.i!
69.6|
1.9!
0.8]
0.0]
0.7!
o.i!
o.i!
0.2!
1.8!
0.4|
3.3J
1.5!
51.3
48.7J
47.7J
1.9|
0.3
0.3]
41.0
1.8
2.8
0.1
i
i
Area (ha) i
_ i
i
MEAN ]
i
i
i
i
0.79J
1.37!
1.02!
0.27J
3.20!
4.86!
1.18J
1.01!
3.56[
1 . 44 !
5.56J
1.68!
1.01!
2.80|
0.68!
0.58!
1.02!
0.48!
0.24[
0.34!
0.94J
0.52!
0.11!
0.30J
0.12!
0.28!
0.72!
0.78J
1.46[
0.32J
2.93!
5.02 j
1.76!
1.50!
4.64J
0.64!
0.79!
0.52!
0.86!
1.14!
0.14!
70
-------
Prairie Pothole Region
EMAP
PFO/SSC
PL
NWI
PFOCh
PFOCx
PSS/EMC
PSS/FOC
PSSC
PAB/EMF
PAB/EMFH
PAB/EMFh
PABF
PABFH
PABFX
PABFh
PABFx
PABGX
PEM/ABF
PEM/ABFH
PEM/ABFX
PEM/ABFh
PEM/FOA
PEM/FOC
PEM/FOCH
PEM/FOCx
PEM/USA
PEM1F
PEMA
PEMAD
PEMAH
PEMAd
PEMAh
PEMC
PEMCD
PEMCH
PEMCX
PEMCd
PEMCh
PEMF
PEMFD
PEMFH
PEMFX
PEMFh
PFO/EMA
|
Number |
!
i j
i j
3!
i!
7!
2!
2!
4j
13!
6!
99j
6!
35!
i!
149 j
36!
7!
2!
3!
3!
4!
i!
i!
i!
1566J
29!
10!
8!
i!
662!
13,'
21
1
9!
ii!
2!
362!
1 1
A 1
7!
2!
4!
3!
1
1
1
1
Percent | *
Number j
i
i
0.3!
0.3J
1.0!
0.3!
2.3!
o.i!
o.i!
o.i!
0.4;
0.2J
3.2!
0.2!
i.i!
o.o!
4.8!
1.2!
0.2!
o.ii
o.i!
o.ij
o.i!
o.o!
o.o!
o.o,1
50.0J
0.9J
0.3J
0.3J
o.o!
21.2!
0.4J
O.ij
0.3J
0.4J
o.ij
11.6!
o.o!
0.2J
o.i!
o.i!
o.i!
Area
(ha)
Total
0.6
0.1
1.3
6.5
1.7
23.3
146.8
37.8
13.9
3.3
12.7
7.6
5.5
0.2
1433.8
4917.5
1.3
10.3
5.6
5.8
1.3
0.3
21.8
2.6
1982.3
25.1
10.1
14.1
0.4
6968.7
22.7
1.4
0.7
6.4
1.8
2365.2
122.5
29.8
0.4
2.3
3.6
! Area j
! (ha) j
!% Totalj
i i
i i
! o.2j
! o.oj
! o.s!
! 2.6[
i 0.7J
I o.ij
1 o p 1
i u. e |
[ 0.2J
! o.ij
j o.o!
j o.ij
j o.oj
j o.oj
j o.oj
! 7.9!
! 27.0!
! o.oj
i nil
1 U. 1 |
j O.Oj
j O.OJ
! o.oj
I o.oj
j o.ij
o.o!
j 10.9J
j o.ij
j O.lj
j o.ij
1 o.oj
j 38.2J
o.i!
j o.o!
I o.o!
! o.o!
! o.o!
! i3.o[
! 0.7J
! o.2!
! o.o|
1 o.oj
j o.oj
t
i
Area (ha) j
_ _ i
MEAN j
_ i
i
i
0. 59 j
0.09J
0.44J
6.46J
0.25J
11.63!
73.38!
9.45J
1.07]
0.54!
0.13!
1.27J
0.16!
0.24[
9.62J
136.60!
0.19J
5.15J
1.88!
1.93J
0.34!
0.28J
21.76!
2.57J
1.27J
0.87!
1.01!
1.76J
0.41!
10.53J
1.74}
0.71[
0.08J
0.58J
0.88J
6.53J
122. 53j
4.26J
0.20J
0.57J
1.21!
71
-------
Prairie Pothole Region
EMAP NWI
PL PFO/EMAH
PFO/EMC
PFOA
PFOAH
PFOAh
PFOC
PFOCH
PSS/EMC
PSS/FOA
PSSA
PUBFHX
PUBFX
PUS/FOCX
PUSA
PS PAB/EMF
PAB/EMFD
PAB/EMFH
PAB/EMFd
PAB/EMFh
PABF
PABFD
PABFH
PABFHX
PABFX
PABFh
PABFhx
PABFX
PABG
PABGH
PABGX
PABGh
PABGx
PUB/EMFH
PUB/FOFH
PUB/FOFX
PUBF
PUBFH
PUBFHX
PUBFX
PUBFx
PUBGH
i
i
i
i
i
i
Number J
|
l!
1!
20 j
i!
ii!
3!
3!
2!
2!
3!
i!
13|
i!
i!
161|
3!
9!
4!
4!
551|
5!
255!
19!
4212!
80]
9!
2052!
3!
5!
15!
2!
34|
i!
i!
i!
3|
333!
72|
2640,'
15!
39|
i
i
i
i
Percent | ~
Number j
i
O.Oj
o.oj
0.6|
O.Oj
0.4|
o.ij
O.lj
o.i!
o.ij
o.ii
o.o!
0.4!
o.o|
o.o!
1.5J
o.o!
o.i!
O.Oj
o.o!
5.2|
O.Oj
2.4!
0.2!
39.8J
0.8!
O.lj
19.4[
O.Oj
o.o!
O.lj
O.Oj
0.3J
O.Oj
o.o!
o.o!
O.Oj
3.2|
0.7!
2 5 . 0 j
o.i!
0.4J
Area j
(ha) j
Total j
i
i
0.5J
0.6J
5.8J
1-9!
2.3!
0.9J
2.3!
0.7[
0.9J
6.5J
o.i!
1.7!
0.2!
0.6!
1255. 8j
104.1!
122.5!
20. Ij
12.0[
1420.8!
8.8J
200.1!
-3 q i
J . y |
649.6!
110.3J
1.4!
307. 9j
5.5!
10. 8j
20. 4j
4.9J
68. 8j
1.2!
0.9!
0.2J
0.3J
417.51
27.4J
422.8|
3.9|
97.9!
Area j
(ha) 1
% Total j
i
i
O.Oj
O.Oj
o.oi
o.o[
O.Oj
O.Oj
O.Oj
O.Oj
O.Oj
o.o!
O.Oj
O.Oj
o.o!
o.o!
23. 6j
2.0!
j -i i
ฃ . j |
0.4J
0.2!
26.7J
0.2J
3.8J
o.i[
12.2 j
2.1!
o.o!
5.8J
o.i!
0.2 j
0.41
o.i!
1.3J
o.o!
o.o!
o.o!
o.oj
7.81
0.5|
7.9]
o.i!
1.8!
Area (ha) |
i
i
MEAN !
i
!
0.45|
0.57J
0.291
1.87J
0.21J
0.29J
0.76J
0.37J
0.44!
2.16J
O.llj
0.13!
0.23J
0.57 j
7.80!
34.70!
13.61J
5.03!
3.01!
2.58J
1.76[
0.78!
0.21J
0.15!
1.38J
0.15[
0.15J
1.83J
2.16|
1.361
2.46J
2.02!
1.21!
0.92 j
0.18J
O.llj
1.251
0.38J
0.16J
0.26!
2.51!
72
-------
Prairie Pothole Region
EMAP NWI
PS PUBGHX
PUBGX
PUSA
PUSCH
PUSCX
PUSFH
Number
o
24
4
1
10
1
rGL cent
Number
0.0
0.2
0.0
0.0
0.1
0.0
Area
(ha)
Total
1.0
18.4
1.7
0.1
4.1
1.6
Area
(ha)
% Total
0.0
0.3
0.0
0.0
0.1
0.0
Area (ha)
MEAN
0.52
0.76
0.44
0.07
0.41
1.61
73
-------
Appendix F
Tables for each region showing the tile identifier number and the
percentage of each tile (640 km2 hexagon) and each hexagon (40
km2 hexagon)
74
-------
Table F1. Illinois Region. Percentage of tiles and hexagons included in the study.
Tile Percentage Percentage
Identifier in Tile in Hexagon
7363
7364
7365
7366
7367
7368
7519
7520
7521
7522
7523
7524
7525
7669
7676
7677
7678
7680
7681
7826
7827
7834
7836
7837
7838
7839
7840
7979
7984
7985
7994
7995
7996
7997
7998
8137
8138
8139
8142
8144
8145
8153
8154
8155
8298
100.00
99.65
69.08
69.33
79.45
82.13
100.00
100.00
100.00
100.00
100.00
96.15
93.43
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
73.52
100.00
100.00
100.00
100.00
100.00
100.00
90.45
54.48
93.66
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
75.56
100.00
100.00
1 00.00
100.00
100.00
100.00
100.00
1 00.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
97.83
100.00
100.00
100.00
100.00
100.00
100.00
100.00
99.01
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
75
-------
Illinois Region
Tile Percentage Percentage
Identifier in Tile in Hexagon
8299
8300
8301
8302
8303
8304
8306
8314
8315
8459
8460
8461
8462
8463
8464
8465
8467
8468
8475
8476
8477
8622
8623
8624
8625
8626
8628
8630
8631
8639
8786
8787
8788
8789
8792
8793
8950
8951
8952
8953
8954
8959
9116
9117
9118
100.00
1 00.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
71.43
100.00
100.00
100.00
100.00
100.00
100.00
100.00
97.84
75.70
100.00
100.00
100.00
100.00
100.00
100.00
99.87
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
76
-------
Illinois Region
Tile Percentage Percentage
Identifier in Tile in Hexagon
9TT9 100.00 100.00
9120 100.00 100.00
9125 100.00 100.00
9282 62.46 95.78
9283 100.00 100.00
9286 95.19 100.00
9287 100.00 100.00
9450 90.56 100.00
9454 65.47 100.00
77
-------
Table F2. Washington Region. Percentage of tiles and hexagons included in the study.
Tile Percentage Percentage
Identifier in Tile in Hexagon
25612
25613
25614
25615
25616
25617
25729
25730
25731
25732
25733
25734
25735
25736
25846
25847
25848
25849
25850
25851
25852
25961
25962
25963
25964
25965
25966
25967
26077
26078
26079
26080
26081
26082
26189
26190
26191
26192
26193
26194
26195
26301
26302
26303
26304
47.54
68.90
46.96
35.13
23.40
12.51
21.00
100.00
100.00
100.00
100.00
100.00
94.09
100.00
88.65
100.00
100.00
100.00
100.00
100.00
30.23
44.65
100.00
100.00
100.00
100.00
100.00
78.98
100.00
100.00
100.00
100.00
100.00
9.39
78.08
100.00
100.00
100.00
100.00
100.00
50.02
23.20
100.00
100.00
100.00
44.37
78.84
31.20
0.01
0.00
0.00
0.00
1 00.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
50.60
0.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
0.00
53.42
100.00
100.00
100.00
100.00
100.00
100.00
0.00
100.00
100.00
100.00
78
-------
Washington Region
Tile Percentage Percentage
Identifier in Tile in Hexagon
26305
26306
26307
26308
26413
26414
26415
26416
26417
26418
26419
26523
26524
26525
26526
26527
26528
26529
26633
26634
26635
26636
26637
26742
26744
26745
26746
26747
26848
26849
26850
26851
26852
26853
26953
26954
26955
26956
26957
26958
26959
26960
27058
27060
27061
100.00
100.00
93.22
100.00
100.00
100.00
100.00
100.00
100.00
100.00
26.25
47.92
100.00
100.00
100.00
100.00
100.00
72.87
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
46.02
26.75
100.00
100.00
100.00
100.00
100.00
52.44
34.66
94.13
100.00
100.00
100.00
100.00
100.00
65.01
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
33.21
0.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
0.00
100.00
100.00
100.00
100.00
100.00
63.08
0.93
1 00.00
100.00
100.00
100.00
100.00
100.00
33.05
100.00
100.00
79
-------
Washington Region
Tile Percentage Percentage
Identifier in Tile in Hexagon
27062 100.00 100.00
27063 100.00 100.00
27064 100.00 100.00
27065 100.00 100.00
27066 67.20 100.00
27162 21.89 0.00
27163 100.00 100.00
80
-------
Table F3. Prairie Pothole Region. Percentage of tiles and hexagons included in the study.
Tile Percentage Percentage
Identifier in Tile in Hexagon
14717
14718
14719
14720
14721
14906
14907
14908
14909
15088
15089
15095
15096
15097
15274
15275
15276
15281
15282
15283
15284
15460
15461
15462
15463
15469
15647
15648
15653
15654
15830
15831
15836
15837
16013
16014
9.36
50.99
70.98
89.18
80.32
73.73
100.00
100.00
100.00
100.00
86.20
100.00
100.00
100.00
60.39
100.00
46.61
71.98
68.36
100.00
73.68
86.15
73.89
45.68
63.18
100.00
100.00
83.39
100.00
97.76
63.83
100.00
34.71
60.87
98.38
100.00
0.00
53.94
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
89.32
100.00
33.71
100.00
63.76
100.00
100.00
100.00
100.00
28.68
96.84
100.00
100.00
100.00
100.00
100.00
98.05
100.00
29.69
91.38
100.00
100.00
81
-------
Appendix G
Tables containing raw data values (i.e., no expansion factor
correction applied).
82
-------
Table G1. Changes in the numbers of wetlands when mapping from the NWI level classification to
the EMAP level classification.
NUMBERS OF WETLANDS
Illinois
Washington
Prairie Pothole
EMAP Class
E2EM
E2FO/SS
PEMAR
PEMA
PEMBR
PEMB
PEMCR
PEMC
PFO/SSAR
PFO/SSA
PFO/SSBR
PFO/SSB
PFO/SSCR
PFO/SSC
PL
PS
TOTAL
NWI
0
0
1045
11005
5
105
1223
16426
9971
9752
1
9
2818
6701
3489
59625
122175
EMAP
0
0
923
10923
5
103
1101
15741
7240
8970
1
9
2384
6089
1757
59312
114558
NWI
1031
16
583
2320
35
193
2319
11301
2597
2071
18
136
5578
9891
720
7773
46582
EMAP
819
15
478
2235
34
190
1934
10812
1933
1978
17
128
4033
8496
586
7639
41327
NWI
0
0
115
80703
0
2
112
79465
92
949
0
0
78
299
3130
10570
175515
EMAP
0
0
101
79676
0
2
101
78102
92
932
0
0
78
296
2399
10405
172184
AVERAGE SIZE (in hectares)
Illinois
Washington
Prairie Pothole
EMAP Class
E2EM
E2FO/SS
PEMAR
PEMA
PEMBR
PEMB
PEMCR
PEMC
PFO/SSAR
PFO/SSA
PFO/SSBR
PFO/SSB
PFO/SSCR
PFO/SSC
PL
PS
NWI
0
0
2.49
0.84
18.00
3.81
3.54
1.20
7.67
3.59
0.42
2.99
7.56
2.91
5.29
0.42
EMAP
0
0
2.82
0.85
18.00
3.89
3.93
1.26
10.56
3.90
0.42
2.99
8.93
3.21
10.51
0.42
NWI
7.18
2.29
5.40
2.36
0.94
1.18
3.44
1.53
2.99
2.45
0.84
0.85
2.94
2.33
3.18
0.63
EMAP
9.03
2.45
6.59
2.45
0.97
1.19
4.12
1.60
4.02
2.56
0.89
0.90
4.07
2.72
3.91
0.64
NWI
0
0
7.21
0.84
0
23.98
24.21
1.28
0.02
0.41
0
0
2.63
0.82
5.83
0.50
EMAP
0
0
8.21
0.85
0
23.98
26.84
1.30
2.02
0.42
0
0
2.63
0.83
7.60
0.51
83
-------
Table G2. Percentages of the number and areas of wetlands for each EMAP class for each of the
three regions. Values reported are percentages based on raw data values. NP identifies
EMAP classes not present in the region.
Illinois
Washington
Prairie Pothole
EMAP Class
E2EM
E2FO/SS
PEMAR
PEMA
PEMBR
PEMB
PEMCR
PEMC
PFO/SSAR
PFO/SSA
PFO/SSBR
PFO/SSB
PFO/SSCR
PFO/SSC
PL
PS
%No.
NP
NP
0.8
9.5
0.0
0.1
1.0
13.7
6.3
7.8
0.0
0.0
2.1
5.3
1.5
51.8
%Area
NP
NP
1.1
4.0
0.0
0.2
1.9
8.5
32.9
15.1
0.0
0.0
9.2
8.4
8.0
10.8
%No.
2.0
0.0
1.2
5.4
0.1
0.5
4.7
26.2
4.7
4.8
0.0
0.3
9.8
20.6
1.4
18.5
%Area
7.3
0.0
3.1
5.4
0.0
0.2
7.9
17.1
7.7
5.0
0.0
0.1
16.2
22.8
2.3
4.8
%No.
NP
NP
0.1
46.3
NP
0.0
0.1
45.4
0.1
0.5
NP
NP
0.0
0.2
1.4
6.0
%Area
NP
NP
0.4
34.2
NP
0.0
1.4
51.5
0.1
0.2
NP
NP
0.1
0.1
9.2
2.7
84
-------
Table G3. Population summary by size for each of the regions. Values reported are percentages
based on raw data values.
A.
Percentage of the Number of Wetlands
Illinois
Washington
Prairie Pothole
Size Class (ha)
0.0-0.25
0.25 -0.5
0.5 - 1
1 - 2
2 - 5
5 - 10
10 - 25
25 - 50
50 - 1 00
>100
NWI
43.4
16.7
13.5
10.6
9.1
3.5
2.0
0.6
0.3
0.2
EMAP
45.5
16.8
13.0
9.9
8.4
3.3
2.0
0.6
0.3
0.2
NWI
27.1
17.3
17.9
15.5
13.1
5.1
2.9
0.7
0.3
0.1
EMAP
26.9
17.9
17.8
15.0
12.7
5.2
3.1
0.9
0.4
0.1
NWI
51.5
17.7
13.3
8.8
5.8
1.8
0.8
0.2
0.1
0.1
EMAP
51.9
17.7
13.2
8.5
5.7
1.8
0.8
0.2
0.1
0.1
B.
Percentage of Wetlands Surface Area
Illinois
Washington
Prairie Pothole
Size Class (ha)
0.0-0.25
0.25 -0.5
0.5- 1
1 -2
2- 5
5- 10
10-25
25-50
50-100
>100
NWI
2.9
3.1
5.1
7.9
15.0
12.9
16.1
11.0
9.6
16.5
EMAP
2.8
2.9
4.5
6.9
13.0
11.2
15.2
10.4
9.8
23.0
NWI
1.6
2.9
5.9
10.1
18.9
16.2
20.5
11.6
8.4
3.8
EMAP
1.5
2.6
5.2
8.7
16.2
14.8
19.6
12.2
10.6
8.5
NWI
5.8
5.6
8.4
10.9
15.9
11.0
10.9
5.5
4.4
21.6
EMAP
5.7
5.5
8.1
10.4
15.3
10.6
10.9
5.7
4.9
22.8
85
-------
Table G4. Sample estimates for number and areas of wetlands by EMAP class for the Illinois
region. "*" indicates that the true population value is contained within the estimate's
confidence interval. The values below were computed from the raw data values. NP
identifies EMAP classes not present in the region. "--" denotes that the estimates were not
obtainable for that EMAP class.
EMAP Class
E2EM
E2FO/SS
PEMAR
PEMA
PEMBR
PEMB
PEMCR
PEMC
PFO/SSAR
PFO/SSA
PFO/SSBR
PFO/SSB
PFO/SSCR
PFO/SSC
PL
PS
TOTAL
.
EMAP Class
E2EM
E2FO/SS
PEMAR
PEMA
PEMBR
PEMB
PEMCR
PEMC
PFO/SSAR
PFO/SSA
PFO/SSBR
PFO/SSB
PFO/SSCR
PFO/SSC
PL
PS
TOTAL
Number
NP
NP
923
10923
5
103
1101
15741
7240
8970
1
9
2384
6089
1757
59312
114558
Area
(ha)
NP
NP
2605
9237
90
400
4325
19760
76428
34989
0
27
21297
19529
18464
25085
232236
I^UI 1 1
Est.
Number
-
-
1072
11504
0
64
1280
16288
8240
10224
0
0
3104
7840
1776
60320
121712
AfG3 OT
Est.
Area
-
4073
9838
0
93
4369
18233
80390
41919
0
0
22399
19938
14816
26099
242167
uci ui vvciia
Rel.
Diff.
-
-
0.16
0.05
-1.00
-0.38
0.16
0.03
0.14
0.14
-1.00
-1.00
0.30
0.29
0.01
0.02
0.06
VvGusnos in
Rel.
Diff.
-
-
0.56
0.07
-1.00
-0.77
0.01
-0.08
0.05
0.20
-
0.05
0.02
-0.20
0.04
0.04
I IUO
SE
-
--
208
1396
-
44
214
2508
1194
1192
-
940
1237
533
7289
Hectsres
SE
--
1288
1526
-
84
1660
4381
25232
9653
-
7097
4044
6497
2936
CV
-
-
0.19
0.12
-
0.68
0.17
0.15
0.14
0.12
-
0.30
0.16
0.30
0.12
CV
--
-
0.32
0.16
-
0.90
0.38
0.24
0.31
0.23
-
0.32
0.20
0.44
0.11
90% Conf. Int.
Lower
Bound
-
-
731
9208
-8
928
12162
6275
8263
-
1557
5806
900
48330
90% Conf. Int.
Lower
Bound
-
1954
7327
-45.37
1638
11026
38883
26040
10725
13286
4129
21269
Upper
Bound
1413*
13800*
-
136*
1632*
20414*
10205*
12185*
~
4651*
9874*
2652*
72310*
Upper
Bound
6192*
12349*
232
7101*
25440*
121897*
57798*
34074*
26591*
25503*
30929*
86
-------
Table G5. Sample estimates for number and areas of wetlands by EMAP class for the Washington
region. "*" indicates that the true population value is contained within the estimate's
confidence interval. The values below were computed from the raw data values. "--"
denotes that the estimates were not available for that EMAP class.
EMAP Class
E2EM
E2FO/SS
PEMAR
PEMA
PEMBR
PEMB
PEMCR
PEMC
PFO/SSAR
PFO/SSA
PFO/SSBR
PFO/SSB
PFO/SSCR
PFO/SSC
PL
PS
TOTAL
.
EMAP Class
E2EM
E2FO/SS
PEMAR
PEMA
PEMBR
PEMB
PEMCR
PEMC
PFO/SSAR
PFO/SSA
PFO/SSBR
PFO/SSB
PFO/SSCR
PFO/SSC
PL
PS
TOTAL
Number
819
15
478
2235
34
190
1934
10812
1933
1978
17
128
4033
8496
586
7639
41310
Area
(ha)
7398
37
3148
5478
33
227
7966
17346
7767
5072
15
115
16399
23067
2290
4901
105752
MUIM
Est.
Number
800
48
368
1808
16
160
1536
9600
2208
2000
0
176
4368
8496
656
6640
38880
AfQO ("if
Est.
Area
11785
92
4348
2919
1
111
6281
12960
7033
5627
0
99
21171
31685
1851
3467
109430
uci ui v venal iu;
Rel.
Diff.
-0.02
2.20
-0.23
-0.19
-0.53
-0.16
-0.21
-0.11
0.14
0.01
-1.00
0.38
0.08
0.00
0.12
-0.13
-0.06
\A/of IjsnHc in HP
VVcUallUo III lie
Rel.
Diff.
0.59
1.50
0.38
-0.47
-0.95
-0.51
0.21
-0.25
-0.09
0.11
-1.00
-0.14
0.29
0.37
-0.19
-0.29
0.03
j
SE
260
34
130
530
15
113
350
1886
433
394
-
88
901
1392
238
1145
ftJirPQ _.
SE
5244
63
3544
1270
1
96
2249
3594
1880
1624
-
78
8387
9061
857
608
CV
0.33
0.72
0.35
0.29
0.97
0.71
0.23
0.20
0.20
0.20
-
O.50
0.21
0.16
0.36
0.17
CV
0.44
0.69
0.81
0.44
0.97
0.87
0.36
0.28
0.27
0.29
-
0.78
0.40
0.29
0.46
0.18
90% Conf. Int.
Lower
Bound
372
-9
154
935
-9
-26
971
6498
1495
1353
-
32
2886
6207
264
4757
90% Conf. Int.
Lower
Bound
3159
-12
-1481
830
-1
-48
2581
7047
3940
2956
-
-28
7375
16781
441
2467
Upper
Bound
1228*
105*
582*
2681*
41*
346*
2111*
12702*
2921*
2647*
-
320*
5850*
10785*
1048*
8523*
Upper
Bound
20411*
196*
10178*
5009
4
269*
9981*
18872*
10125*
8299*
-
227*
34968*
46590*
3261*
4466
87
-------
Table G6. Sample estimates for number and areas of wetlands by EMAP class for the Prairie Pothole region.
"" indicates that the true population value is contained within the estimate's confidence interval.
The values below were computed from the raw data values. NP identifies EMAP classes not present
in the region. "--" denotes that the estimates were not obtainable for theat EMAP class.
/-v.
EMAP Class
E2EM
E2FO/SS
PEMAR
PEMA
PEMBR
PEMB
PEMCR
PEMC
PFO/SSAR
PFO/SSA
PFO/SSBR
PFO/SSB
PFO/SSCR
PFO/SSC
PL
PS
TOTAL
,
EMAP Class
E2EM
E2FO/SS
PEMAR
PEMA
PEMBR
PEMB
PEMCR
PEMC
PFO/SSAR
PFO/SSA
PFO/SSBR
PFO/SSB
PFO/SSCR
PFO/SSC
PL
PS
TOTAL
Number
NP
NP
101
79676
NP
2
101
78102
92
932
NP
NP
78
296
2399
10405
172184
Area
(ha)
NP
NP
830
67490
NP
48
2711
101555
186
387
NP
NP
206
245
18234
5327
197219
mum
Est.
Number
--
16
102704
0
0
84640
0
1232
0
352
944
12032
201920
ArซO f\f
r\l Co \J
Est.
Area
-
-
46
59671
-
0
0
93345
0
519
-
-
0
201
4532
6105
164419
uei ui vveudiiu:
Rel.
Diff.
-
-0.84
0.29
-
-1.00
-1.00
0.08
-1.00
0.32
-
-1.00
0.19
-0.61
0.16
0.17
VA/PtlanHc in HP
V VC Uol ItJo III DC
Rel.
Diff.
-
-
-0.94
-0.12
-
-1.00
-1.00
-0.08
-1.00
0.34
-
-
-1.00
-0.18
-0.75
0.15
-0.17
5
SE
-
-
15
13144
-
-
-
10836
-
261
-
-
87
469
1360
i^tarQC _
SE
"
-
44
6631
-
-
-
10686
-
159
-
-
-
72
2219
1434
CV
-
0.97
0.13
ซ
-
0.13
0.21
-
0.25
0.50
0.11
CV
-
-
0.97
0.11
-
-
-
0.11
-
0.31
-
-
-
0.36
0.49
0.23
90% Conf. I
Lower
Bound
-9
81082
66815
802
209
173
9794
90% Conf.
Lower
Bound
-
-
-27
48763
-
-
-
75767
-
257
-
-
-
82
882
3747
,nt.
Upper
Bound
--
41
124326
-
-
102465*
1662*
-
-
-
495*
1715
14270*
Int.
Upper
Bound
-
-
118
70579*
-
-
110924*
-
781*
-
-
-
321*
8182
8464*
88
-------
Table G7. Sample estimates by size class for the Illinois region. "" indicates that the true population value is
contained within the estimate's confidence interval. The values below were computed from the raw data
values.
Size Class (ha)
0 - 0.25
0.25 - 0.50
0.50 - 1.0
1 - 2
2- 5
5 - 10
10- 25
25 - 50
50- 100
>100
Number
52130
19199
14865
11336
9680
3784
2304
707
327
226
Est.
Number
54256
20240
15920
12624
10768
4048
2496
832
384
144
Rel.
Diff.
0.04
0.05
0.07
0.11
0.11
0.07
0.08
0.18
0.17
-0.36
SE
6359
1835
1384
1162
1038
473
391
148
94
63
CV
0.12
0.09
0.09
0.09
0.10
0.12
0.16
0.18
0.24
0.43
90% Conf. In
Lower
Bound
43796
17222
13643
10712
9061
3270
1852
588
230
41
t.
Upper
64716*
23258*
18197*
14536*
12475*
4826*
3140*
1076*
538*
247*
B.
-- Area of Wetlands in Hectares
90% Conf. Int.
Size Class (ha)
0 - 0.25
0.25 - 0.50
0.50- 1.0
1 - 2
2- 5
5 - 10
10 - 25
25- 50
50- 100
>100
Area
(ha)
6570
6832
10553
16033
30265
26061
35353
24237
22823
53509
Est.
Area
6869
7268
11233
17824
34137
27651
38381
28771
25346
44688
Rel.
Diff.
0.05
0.06
0.06
0.11
-0.11
0.06
0.09
0.19
0.11
-0.16
SE
767
658
983
1650
3416
3309
6105
5413
6066
25404
CV
0.11
0.09
0.09
0.09
0.10
0.12
0.16
0.19
0.24
0.57
Lower
Bound
5608
6186
9616
15110
28518
22207
28339
19866
15367
2899
Upper
Bound
8130*
8350*
12849*
20538*
39755*
33095*
48424*
37676*
35325*
86477*
89
-------
Table G8. Sample estimates by size class for the Washington region. "*" indicates that the true population
value is contained within the estimate's confidence interval. The values below were computed from
the raw data values.
Size Class (ha)
0-0.25
0.25 - 0.50
0.50 - 1.0
1 - 2
2 - 5
5 - 10
10 - 25
25 - 50
50- 100
>100
B.
Size Class (ha)
0 - 0.25
0.25 - 0.50
0.50- 1.0
1 -2
2 - 5
5 - 10
10- 25
25 - 50
50-100
>100
Number
11101
7396
7364
6214
5239
2159
1284
357
161
52
Area
(ha)
1521
2668
5311
8846
16423
14945
19819
12372
11734
8622
Est.
Number
10656
7520
6688
4992
4944
2096
1296
400
208
80
ui vvcudi IDO
Rel.
Diff.
-0.04
0.02
-0.09
-0.20
-0.06
0.03
0.01
0.12
0.29
0.53
- Area of Wetlands in Heci
Est.
Area
1483
2740
4807
7122
15460
14917
20843
13739
15060
13261
Rel.
Diff.
-0.02
0.02
-0.09
-0.19
-0.06
<0.01
0.05
0.11
0.40
0.54
SE
1751
904
868
780
839
463
375
194
109
40
tares
SE
233
327
630
1130
2656
3347
5968
6863
8005
7128
CV
0.16
0.12
0.13
0.16
0.17
0.22
0.29
0.48
0.53
0.51
CV
0.16
0.12
0.13
0.16
0.17
0.22
0.29
0.50
0.53
0.54
90% Conf.
Lower
Bound
7776
6034
5260
3709
3564
1334
680
81
28
13
90% Conf.
Lower
Bound
1099
2202
3772
5263
11091
9412
11024
2450
1891
1536
Int.
Upper
Bound
13536*
9006*
8116*
6275*
6325*
2858*
1912*
719*
388*
147*
Int.
Upper
Bound
1867*
3278*
5843*
8982*
19829*
20422*
30661*
25028*
28228*
24986*
90
-------
Table G9. Sample estimates by size class for the Prairie Pothole region. "*" indicates that the true population
value is contained within the estimate's confidence interval. The values below were computed from the raw
data values.
Size Class (ha)
0 - 0.25
0.25 - 0.50
0.50- 1.0
1 - 2
2-5
5- 10
10-25
25-50
50- 100
>100
B.
Size Class (ha)
0 - 0.25
0.25 - 0.50
0.50- 1.0
1 -2
2-5
5- 10
10-25
25-50
50- 100
>100
Number
89394
30473
22705
14710
9864
3056
1415
327
144
96
Area
(ha)
11327
10832
16065
20561
30137
20944
21401
11335
9737
44879
i^umuci
Est.
Number
106128
35968
27584
16144
11216
2976
1472
304
96
32
ui vveudiiuo
Rel.
Diff.
0.19
0.18
0.21
0.10
0.14
-0.03
0.04
-0.07
-0.33
-0.67
SE
12619
3893
2595
1775
1O41
361
230
79
47
22
CV
0.12
0.11
0.09
0.11
0.09
0.12
0.16
0.26
0.49
0.68
90% Conf.
Lower
Bound
85369
29564
23315
13223
9503
2382
1093
174
18
-4
Int.
Upper
Bound
126887*
42372*
31853
19065*
12929*
3570*
1851*
434*
174*
68
- Area of Wetlands in Hectares
Est.
Area
135660
12827
19490
22452
33907
19943
20756
10442
7312
3724
Rel.
Diff.
0.20
0.18
0.21
0.09
0.13
-0.05
-0.03
-0.08
-0.25
-0.92
SE
1531
1384
1854
2484
3151
2442
3293
2857
3623
2518
CV
0.11
0.11
0.10
0.11
0.09
0.12
0.16
0.27
0.50
0.68
90% Conf.
Lower
Bound
11049
10551
16439
18366
28724
15925
15340
5743
1352
-418
Int.
Upper
Bound
16084*
15104*
22540*
26538*
39091*
23960*
26172*
15141*
13273*
7865
91
-------
Appendix H
List of participants at the October 1990 informal workshop in
Warrenton, VA
92
-------
Nancy Leibowitz
Oregon Division of State Lands
Salem, OR
Lyman McDonald
Western EcoSystems Technology
Cheyenne, WY
Nina Mata
Bionetics Corporation
Warrenton, VA
Doug Norton
US Environmental Protection Agency
Warrenton, VA
Dick Novitzki
ManTech Environmental Technology
Corvallis, OR
Denis Roose
Bionetics Corporation
Warrenton, VA
Kris Stout
Bionetics Corporation
Warrenton, VA
Rose Sullivan
Bionetics Corporation
Warrenton, VA
Bill Wilen
US Fish and Wildlife Service
National Wetlands Inventory Program
St. Petersburg, FL
93
-------
Appendix I
Description and location of the data files used in this study
94
-------
Two data files were necessary for the analyses in each of the three regions.
xxxCOD.DAT Contains data that retains the integrity of the NWI polygons and relabels
polygons with EMAP codes.
xxxECO.DAT Contains data that aggregates contiguous polygons with like EMAP class
codes (i.e., dissolve coincident boundaries between like classes). The ECO
stands for EMAP Code.
Variable Field Number
COD ECO
Hexagon Number 1 1
Area 2 2
Perimeter 3 3
NWI Code 4
EMAP Code 5 4
Latitude 6 5
Longitude 7 6
In 40 Hex Flag 8 7
Information regarding these data files can be obtained by contacting:
EMAP-Wetlands Technical Director
U.S. Environmental Protection Agency
Environmental Research Laboratory
200 SW 35th Street
Corvallis. OR 97333
qc
J^ &[>.$- GOVERNMENT PRINTING OFFICE' 1993 - 750-002/80239
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