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 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/.

This dataset is the output of a python script/ArcGIS model that identifes dikes as having a difference in elevation above a certain threshold. If the elevation difference was below a certain threshold the area was not considered a dike; however, if the difference in elevation between two points was significantly high then the area was marked as a dike. Areas continuous with eachother were considered part of the same dike. Post processing occured. Users examined the data output, comparing the proposed dike locations to aerial imagery, flowline data, and the DEM. Dikes that appeared to be false positives were deleted from the data set.

This dataset is part of the U.S. Geological Survey (USGS) Great Lakes Coastal Wetland Restoration Assessment (GLCWRA) initiative. This data represents the location of dikes within the Lake Ontario Restoration Assessment (LORA) study area. The GLCWRA initiative identifies coastal wetland areas that have the greatest habitat restoration potential. The data model uses seven parameters to identify and rank wetland restoration areas, resulting in a composite index raster that can be used by ecological managers and planners to assist with the selection of wetland restoration sites. The parameters are 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 (represents developed areas without impervious surfaces but high societal value). The ancillary data include dikes, degree flowlines, study area and culverts. These data layers are put through an ecological model, which results in a composite restoration index of ranked restoration areas.

This dataset is part of the U.S. Geological Survey (USGS) Great Lakes Coastal Wetland Restoration Assessment (GLCWRA) initiative. This data represents the location of dikes within the Lake Ontario Restoration Assessment (LORA) study area. The GLCWRA initiative identifies coastal wetland areas that have the greatest habitat restoration potential. The data model uses seven parameters to identify and rank wetland restoration areas, resulting in a composite index raster that can be used by ecological managers and planners to assist with the selection of wetland restoration sites. The parameters are 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 (represents developed areas without impervious surfaces but high societal value). The ancillary data include dikes, degree flowlines, study area and culverts. These data layers are put through an ecological model, which results in a composite restoration index of ranked restoration areas.

This dataset represents the location of dikes within the Connecting River Systems Restoration Assessment (CRSRA) study area. For more information, see the full data release documentation and the GLCWRA webpage: https://glcwra.wim.usgs.gov/.

This dataset represents the location of dikes within the Connecting River Systems Restoration Assessment (CRSRA) study area. For more information, see the full data release documentation and the GLCWRA webpage: https://glcwra.wim.usgs.gov/.

This dataset is part of the U.S. Geological Survey (USGS) Great Lakes Coastal Wetland Restoration Assessment (GLCWRA) initiative. The GLCWRA initiative uses principles of geodesign to identify coastal wetland areas that have the greatest potential for habitat restoration. The data model uses the following seven primary parameters to identify and rank wetland restoration areas. The parameters are 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 (represents developed areas without impervious surfaces but high societal value).The ancillary data include dikes, degree flowlines, study area and culverts. The resulting composite index raster can be used by ecological managers and planners to assist with the identification and selection of wetland for restoration initiatives.