This dataset contains all the layers associated with U.S. Geological Survey (USGS) Great Lakes Coastal Wetland Restoration Assessment (GLCWRA) initiative for the Western Lake Erie Restoration Assessment (WLERA) aims to identify and rank coastal areas with the greatest potential for wetland habitat restoration. Each of the 10-meter raster layers in this dataset has a unique contribution to the identification of restorable wetlands. The 7 parameters (Parameter 0: Mask, Parameter 1: Hydroperiod, Parameter 2: Wetland Soils, Parameter 3: Flowlines, Parameter 4: Conservation and Recreation Lands, Parameter 5: Impervious Surfaces, and Parameter 6: Land Use) and Index Composite directly correlate to areas that are recommended for restoration. The dikes, degree flowlines, culverts, study area and DEM datasets are supplemental layers that provide additional information around the priority rank values. All layers were produced in collaboration with the USGS Upper Midwest Water Science Center, USGS Great Lakes Science Center, and by the New College of Florida. For more information on these parameters, see the full data release documentation and the GLCWRA webpage: https://glcwra.wim.usgs.gov/.

The US Geological Survey (USGS) created the Dikes dataset (version 2.0) as ancillary layer in the Western Lake Erie Restoration Assessment (WLERA) which covers the southwestern shore of Lake Erie. WLERA is a part of the USGS's Great Lakes Coastal Wetland Restoration Assessment (GLCWRA) initiative where coastal areas around the Great Lakes are identified and ranked for potential wetland restoration. The dikes dataset was created to identify human made and naturally occurring dikes or berms which have the potential to block the flow of water between Lake Erie and wetland habits. These potential dikes were outlined by selecting all the areas within the WLERA study area with a slope greater than 12 degrees (derived from the DEM created for WLERA). For more information, see the full data release documentation and the GLCWRA webpage: https://glcwra.wim.usgs.gov/.

The US Geological Survey (USGS) created the Dikes dataset (version 2.0) as ancillary layer in the Western Lake Erie Restoration Assessment (WLERA) which covers the southwestern shore of Lake Erie. WLERA is a part of the USGS's Great Lakes Coastal Wetland Restoration Assessment (GLCWRA) initiative where coastal areas around the Great Lakes are identified and ranked for potential wetland restoration. The dikes dataset was created to identify human made and naturally occurring dikes or berms which have the potential to block the flow of water between Lake Erie and wetland habits. These potential dikes were outlined by selecting all the areas within the WLERA study area with a slope greater than 12 degrees (derived from the DEM created for WLERA). For more information, see the full data release documentation and the GLCWRA webpage: https://glcwra.wim.usgs.gov/.

The U.S. Geological Survey (USGS) created geospatial datasets of potential culvert locations along with flowlines connected to southwestern Lake Erie as part of the Western Lake Erie Restoration Assessment (WLERA). The Degree Flowlines and Culverts datasets represent the flowline network and culverts in the WLERA study area. Both datasets will be served in the Great Lakes Wetlands Restoration Area mapping application [https://glcwra.wim.usgs.gov/]. The map-based user interface can be used by stakeholders to find potential areas for successful wetlands restoration. Each flowline was assigned a connectivity score describing its level of connectedness to Lake Erie. Low numbers represent fewer disconnections, such as culverts or road crossings, between the reach and the water body requiring no flow network modification to restore the area. For more information, see the full data release documentation and the GLCWRA webpage: https://glcwra.wim.usgs.gov/.

The U.S. Geological Survey (USGS) created geospatial datasets of potential culvert locations along with flowlines connected to southwestern Lake Erie as part of the Western Lake Erie Restoration Assessment (WLERA). The Degree Flowlines and Culverts datasets represent the flowline network and culverts in the WLERA study area. Both datasets will be served in the Great Lakes Wetlands Restoration Area mapping application [https://glcwra.wim.usgs.gov/]. The map-based user interface can be used by stakeholders to find potential areas for successful wetlands restoration. Each flowline was assigned a connectivity score describing its level of connectedness to Lake Erie. Low numbers represent fewer disconnections, such as culverts or road crossings, between the reach and the water body requiring no flow network modification to restore the area. For more information, see the full data release documentation and the GLCWRA webpage: https://glcwra.wim.usgs.gov/.

This dataset contains all the layers associated with U.S. Geological Survey (USGS) Great Lakes Coastal Wetland Restoration Assessment (GLCWRA) initiative for the Connecting River Systems Restoration Assessment (CRSRA) which aims to identify and rank coastal areas with the greatest potential for wetland habitat restoration. Each layer has a unique contribution to the identification of restorable wetlands. The 7 parameters (Parameter 0: Mask, Parameter 1: Hydroperiod, Parameter 2: Wetland Soils, Parameter 3: Flowlines, Parameter 4: Conservation and Recreation Lands, Parameter 5: Impervious Surfaces, and Parameter 6: Land Use) and Index Composite directly correlate to areas that are recommended for restoration. The dikes, degree flowlines, culverts, study area and DEM datasets are supplemental layers that provide additional information around the priority rank values. All layers were produced in collaboration with the USGS Upper Midwest Water Science Center, USGS Great Lakes Science Center, and by the New College of Florida. For more information, see the full data release documentation and the GLCWRA webpage: https://glcwra.wim.usgs.gov/.

This dataset contains all the layers associated with U.S. Geological Survey (USGS) Great Lakes Coastal Wetland Restoration Assessment (GLCWRA) initiative for the Connecting River Systems Restoration Assessment (CRSRA) which aims to identify and rank coastal areas with the greatest potential for wetland habitat restoration. Each layer has a unique contribution to the identification of restorable wetlands. The 7 parameters (Parameter 0: Mask, Parameter 1: Hydroperiod, Parameter 2: Wetland Soils, Parameter 3: Flowlines, Parameter 4: Conservation and Recreation Lands, Parameter 5: Impervious Surfaces, and Parameter 6: Land Use) and Index Composite directly correlate to areas that are recommended for restoration. The dikes, degree flowlines, culverts, study area and DEM datasets are supplemental layers that provide additional information around the priority rank values. All layers were produced in collaboration with the USGS Upper Midwest Water Science Center, USGS Great Lakes Science Center, and by the New College of Florida. For more information, see the full data release documentation and the GLCWRA webpage: https://glcwra.wim.usgs.gov/.

This dataset contains all the layers associated with U.S. Geological Survey (USGS) Great Lakes Coastal Wetland Restoration Assessment (GLCWRA) initiative for the Saginaw Bay Restoration Assessment (SBRA) which aims to identify and rank coastal areas with the greatest potential for wetland habitat restoration. Each layer has a unique contribution to the identification of restorable wetlands. The 7 parameters (Parameter 0: Mask, Parameter 1: Hydroperiod, Parameter 2: Wetland Soils, Parameter 3: Flowlines, Parameter 4: Conservation and Recreation Lands, Parameter 5: Impervious Surfaces, and Parameter 6: Land Use) and Index Composite directly correlate to areas that are recommended for restoration. The dikes, degree flowlines, culverts, study area and DEM datasets are supplemental layers that provide additional information around the priority rank values. All layers were produced in collaboration with the USGS Upper Midwest Water Science Center, USGS Great Lakes Science Center, and by the New College of Florida. For more information on these parameters, see the full data release documentation and the GLCWRA webpage: https://glcwra.wim.usgs.gov/.

This dataset contains all the layers associated with U.S. Geological Survey (USGS) Great Lakes Coastal Wetland Restoration Assessment (GLCWRA) initiative for the Saginaw Bay Restoration Assessment (SBRA) which aims to identify and rank coastal areas with the greatest potential for wetland habitat restoration. Each layer has a unique contribution to the identification of restorable wetlands. The 7 parameters (Parameter 0: Mask, Parameter 1: Hydroperiod, Parameter 2: Wetland Soils, Parameter 3: Flowlines, Parameter 4: Conservation and Recreation Lands, Parameter 5: Impervious Surfaces, and Parameter 6: Land Use) and Index Composite directly correlate to areas that are recommended for restoration. The dikes, degree flowlines, culverts, study area and DEM datasets are supplemental layers that provide additional information around the priority rank values. All layers were produced in collaboration with the USGS Upper Midwest Water Science Center, USGS Great Lakes Science Center, and by the New College of Florida. For more information on these parameters, see the full data release documentation and the GLCWRA webpage: https://glcwra.wim.usgs.gov/.

Well-established conservation planning principles and techniques framed by geodesign were used to assess the restorability of areas that historically supported coastal wetlands along the U.S. shore of western Lake Erie. The resulting analysis supported planning efforts to identify, prioritize, and track wetland restoration opportunity and investment in the region. To accomplish this, publicly available data, criteria derived from the regional managers and local stakeholders, and geospatial analysis were used to form an ecological model for spatial prioritization (Western Lake Erie Restoration Assessmente (WLERA)). Within the 192,618 ha study area that was bounded by the mouths of the Detroit River, MI to the north and the Black River, OH to the south, the model identified and prioritized 6,600 hectares of land most suitable for coastal wetland habitat restoration.