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            <gco:CharacterString> EnviroAtlas &#8211; Potential Wetland Area for the Conterminous United States</gco:CharacterString>
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        <gco:CharacterString>The Potential Wetland Area (PWA) layer shows areas where conditions may be suitable for wetland habitat at a 10-m resolution. Since the 1600's, an estimated 53% of wetlands in the Conterminous United States have been lost, with many areas being converted for agricultural or urban use. The ecosystems services provided by wetlands are extremely valuable, providing flood attenuation, water filtration, nutrient sequestration, vital habitat, and many others. Wetland restoration or creation can help restore these benefits for the surrounding community. There are several government and community projects that can utilize these data to assist in site selection for wetland restoration projects. 
This layer was created using the Random Forest (RF) machine learning algorithm in Google Earth Engine (GEE). The RF model utilized 17 data inputs to identify areas where attributes on the landscape are similar to the attributes found in existing wetlands. The input data for this layer fall into three categories: topographic variables, soils, and satellite imagery. 
Topographic - DEM's sourced from USGS 3D Elevation Program (10-m)
-Elevation
-Aspect
-Slope
-Compound Topographic Index (CTI)
-Vertical Overland Flow Distance (VOFD)
-Horizontal Overland Flow Distance (HOFD)
-Pythagoras Overland Flow Distance (POFD)
-Soils - Natural Resource Conservation Service's gNATSGO and gSSURGO products
&#183; Potential Wetland Soils (PWS)
-European Space Agency's Sentinel-1 Synthetic Aperture Radar (10-m) 

Using these variables, the Random Forest model was run for each 2 digit Hydrologic Unit Code (HUC) in Google Earth Engine. The model used wetlands from the National Wetland Inventory (NWI) to create training data, masking out deep water areas such as the centers of lakes and rivers, and excluding estuarine and marine wetlands. For each HUC an equal number of wetland and non-wetland training points proportional to the size of the HUC were generated, with 30% of those points being reserved for accuracy assessment. 


This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).</gco:CharacterString>
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The overall goal of EnviroAtlas is to employ and develop the best available science to map indicators of ecosystem services production, demand, and drivers for the nation.</gco:CharacterString>
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            <gco:CharacterString>EnviroAtlas</gco:CharacterString>
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          <gmd:keyword>
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          </gmd:keyword>
          <gmd:keyword>
            <gco:CharacterString>Environmental Atlas</gco:CharacterString>
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Summarize the Component table by mukey to Sum the percentage of component coverage (comppct_r) by Mapunit (mukey). Merge the resulting percentage coverage of qualifying drainagecl and hydricrating components by Mapunit Key to the Valu1 added table. Create a new column where if the drainagecl/hydricrating column had 0 but the pwsl1pomu column is greater than 0, input the pwsl1pomu value, else use the drainagecl/hydricrating percent coverage. Join the resulting table with percentage of wetland soils per mapunit to the CONUS 10-m mapunit raster. 

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          <gmd:processStep>
            <gmd:LI_ProcessStep>
              <gmd:description>
                <gco:CharacterString>Created Random Forest training dataset from the October 2021 National Wetland Inventory (NWI). Each state was downloaded and merged to produce a NWI product for the whole conterminous United States (CONUS). The following codes were assigned by wetland subclass: 1 - M1, M2, E1, E1; 2 - PE, PS, PR, PM, PF, PE, PA, Pf, L2, R4, Lh, Lc; 5 - R1, R2, R3, R5, L1, L. The feature class was converted to raster using Polygon to Raster, and the cell size was set to 10m. The raster was then reclassified to binary where the aforementioned classes were used - value 1 = non-wetland (0), value 2 = wetland (1), and value 5 = masked (NoData).</gco:CharacterString>
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              <dateTime>
                <gco:DateTime>2021-10-30T00:00:00</gco:DateTime>
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                      <gmd:title>
                        <gco:CharacterString>National Wetland Inventory</gco:CharacterString>
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          <gmd:processStep>
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                <gco:CharacterString>Access USGS 3DEP DEM resource on Google Earth Engine and use built-in tools to calculate elevation, aspect, and slope.</gco:CharacterString>
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              <dateTime>
                <gco:DateTime>2021-11-30T00:00:00</gco:DateTime>
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              <gmd:source>
                <gmd:LI_Source>
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                      <gmd:title>
                        <gco:CharacterString>USGS 3DEP 10m National Map Seamless</gco:CharacterString>
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                      <gmd:date gco:nilReason="missing"/>
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          <gmd:processStep>
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              </gmd:description>
              <dateTime>
                <gco:DateTime>2021-11-30T00:00:00</gco:DateTime>
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              <gmd:source>
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