FOR non-AGOL ACCOUNT HOLDERS, DOWNLOAD THIS GEOSPATIAL DATA HERE: https://gis-fws.opendata.arcgis.com/search?tags=lmvjvThese boundaries are simplified from the U.S. Fish and Wildlife Service Real Estate Interest data layer containing polygons representing tracts of land (parcels) in which the Service has a real estate interest. Interior boundaries between parcels were dissolved to produce a single set of simplified external boundaries for each feature. These are resource grade mapping representations of the U.S. Fish and Wildlife Service boundaries. For legal descriptions of the land represented here, contact the USFWS Realty Office. This map layer was compiled by the U.S. Fish and Wildlife Service. Although these boundaries represent lands administered by the U.S. Fish and Wildlife Service, not all areas are open to the public. Some fragile habitats need to be protected from human traffic and some management areas are closed. The public is urged to contact specific Refuges or other conservation areas before visiting.

Potential Natural Vegetation (PNV) mapping: PROVIDES DETAILED MAPS TO GUIDE RESTORATION OF A HIGHLY ALTERED LANDSCAPE, THE MAPS REFLECT THE EXISTING HYDROLOGIC ENVIRONMENT, PARTICULARLY THE EFFECTS OF THE WORLD’S LARGEST AND MOST COMPREHENSIVE FLOOD CONTROL EFFORT, THE MISSISSIPPI RIVER AND TRIBUTARIES PROJECT, THESE RESTORATION TEMPLATES CAN BE USED IN A GIS ENVIRONMENT TO INVESTIGATE A WIDE RANGE OF SCENARIOS, INCLUDING LANDSCAPE-SCALE PLANNING AS WELL AS HIGHLY SITE-SPECIFIC RESTORATION DESIGN, THE HYDROGEOMORPHIC (HGM) CLASSIFICATION SYSTEM IS INCORPORATED IN THE PROCESS SO THAT THE MAPS REFLECT ECOSYSTEM FUNCTION AS WELL AS TRADITIONAL COMMUNITY COMPOSITION AND STRUCTURE. The HGM approach was used in the creation of this data.Section 404 of the Clean Water Act directs the U.S. Army Corps of Engineers to administer a regulatory program for permitting the discharge of dredged or fill material in “waters of the United States.†As part of the permit review process, the impact of discharging dredged or fill material on wetland functions must be assessed. In 1996, a National Action Plan to implement the Hydrogeomorphic Approach for developing Regional Guidebooks to assess wetland functions was published. The Hydrogeomorphic Approach is a collection of concepts and methods for developing functional indices and subsequently using them to assess the capacity of a wetland to perform functions relative to similar wetlands in a region. This report, one of a series of Regional Guidebooks that will be published in accordance with the National Action Plan, applies the Hydrogeomorphic Approach to wetland and riparian forests in the Arkansas Valley Region of Arkansas in a planning and ecosystem restoration context.

This repository contains Google Earth Engine (GEE) and Python code for drier-end wetland mapping in urban/peri-urban areas: The two Google Earth Engine (GEE) scripts are "S1-preproc-Wetland-LULC" and "Annual-Wetland-LULC". Both scripts generate annual and seasonal features for a single year, with the default period running from June 21st (the start of winter in the Southern Hemisphere) to June 20th of the following year (the end of autumn). Each script should be run once per year to generate its Annual Land Use/Land Cover (LULC) map. The Python script is "LULC-to-Wetlands-map" processes a series of wetland-oriented LULC maps to generate a final wetlands map.

This repository contains Google Earth Engine (GEE) and Python code for drier-end wetland mapping in urban/peri-urban areas: The two Google Earth Engine (GEE) scripts are "S1-preproc-Wetland-LULC" and "Annual-Wetland-LULC". Both scripts generate annual and seasonal features for a single year, with the default period running from June 21st (the start of winter in the Southern Hemisphere) to June 20th of the following year (the end of autumn). Each script should be run once per year to generate its Annual Land Use/Land Cover (LULC) map. The Python script is "LULC-to-Wetlands-map" processes a series of wetland-oriented LULC maps to generate a final wetlands map.

The dataset is comprised of three geojson files containing: (1) training points for a Land Use/Land Cover (LULC) classification with 8 LULC classes, (2) test points for a LULC classification LULC classes, and (3) evaluation points for a Wetland map derived from the LULC classifications, with 5 classes. The methodology to which this points were generated is described on a paper pending to be published.