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Saginaw Bay Restoration Assessment Dikes (2016)
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.
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Saginaw Bay Restoration Assessment Dikes
공공데이터포털
This dataset represents the location of dikes within the Saginaw Bay Restoration Assessment (SBRA) study area. An ArcGIS model identified dikes as having a difference in elevation and slope above a certain threshold. See the full data release documentation and the GLCWRA webpage: https://glcwra.wim.usgs.gov/ for further information.
Saginaw Bay Restoration Assessment Dikes
공공데이터포털
This dataset represents the location of dikes within the Saginaw Bay Restoration Assessment (SBRA) study area. An ArcGIS model identified dikes as having a difference in elevation and slope above a certain threshold. See the full data release documentation and the GLCWRA webpage: https://glcwra.wim.usgs.gov/ for further information.
Western Lake Erie Restoration Assessment Composite Model (2016)
공공데이터포털
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.
Saginaw Bay Restoration Assessment Composite Model
공공데이터포털
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/.
Saginaw Bay Restoration Assessment Composite Model
공공데이터포털
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/.
Saginaw Bay Restoration Assessment Degree Flowlines
공공데이터포털
The U.S. Geological Survey (USGS) created geospatial datasets of potential culvert locations along with flowlines connected toLake Huron as part of the Saginaw Bay Restoration Assessment (SBRA). The Degree Flowlines and Culverts datasets represent the flowline network and culverts in the SBRA 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 Huron. 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/.
Saginaw Bay Restoration Assessment Degree Flowlines
공공데이터포털
The U.S. Geological Survey (USGS) created geospatial datasets of potential culvert locations along with flowlines connected toLake Huron as part of the Saginaw Bay Restoration Assessment (SBRA). The Degree Flowlines and Culverts datasets represent the flowline network and culverts in the SBRA 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 Huron. 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/.
Great Lakes Coastal Wetland Restoration Assessment (GLCWRA) Green Bay, U.S.: Composite Model Layers
공공데이터포털
This dataset contains all the layers associated with U.S. Geological Survey (USGS) Great Lakes Coastal Wetland Restoration Assessment (GLCWRA) initiative for the Green Bay Restoration Assessment (GBRA) 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 the methodology used to create these parameters, view the metadata from GLCWRA: Green Bay Restoration Assessment (GBRA) and the GLCWRA webpage: https://glcwra.wim.usgs.gov/.
Great Lakes Coastal Wetland Restoration Assessment (GLCWRA) Green Bay, U.S.: Composite Model Layers
공공데이터포털
This dataset contains all the layers associated with U.S. Geological Survey (USGS) Great Lakes Coastal Wetland Restoration Assessment (GLCWRA) initiative for the Green Bay Restoration Assessment (GBRA) 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 the methodology used to create these parameters, view the metadata from GLCWRA: Green Bay Restoration Assessment (GBRA) and the GLCWRA webpage: https://glcwra.wim.usgs.gov/.
Great Lakes Coastal Wetland Restoration Assessment (GLCWRA) Upper Peninsula, U.S.: Dikes
공공데이터포털
This dataset is part of the U.S. Geological Survey (USGS) Great Lakes Coastal Wetland Restoration Assessment (GLCWRA) initiative. These data represent the location of dikes within the Upper Peninsula Restoration Assessment (UPRA) study area. An ArcGIS model (Python script) identified 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 each other were considered part of the same dike. Data underwent quality control (QC) procedures by having Subject Matter Experts and those familiar with the area examine the data output, comparing the proposed dike locations to aerial imagery, flowline data, and the Digital Elevation Model (DEM). Dikes that appeared to be false positives were deleted from the dataset. Please refer to the process steps and https://glcwra.wim.usgs.gov/ for further explanation on the methods. 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 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.