Hopkins, Anders L. Jaenicke, Margaret E. Kowalski, Kurt P. Bozimowski, Alexandra (Sasha) A. Sanocki, Chris A. 2024 raster digital data Reston, VA U.S. Geological Survey Hopkins, A.L., Jaenicke, M.E., Kowalski, K.P., Bozimowski, A.A., and Sanocki, C.A., 2024, Saginaw Bay Restoration Assessment, Parameter 5: Impervious Surfaces (version 2.0): U.S. Geological Survey data release, https://doi.org/10.5066/P9EFH72U. https://doi.org/10.5066/P9EFH72U U.S. Geological Survey 2016 vector and raster digital data Reston, VA U.S. Geological Survey https://doi.org/10.5066/P9UAA4HY The Saginaw Bay Restoration Assessment (SBRA) Impervious Surface dataset was calculated as the fifth parameter in the U.S. Geological Survey's (USGS) Great Lakes Coastal Wetland Restoration Assessment (GLCWRA) initiative where coastal wetlands around the Great Lakes are identified and ranked for potential wetland restoration. The layer was created from the National Land Cover Database (NLCD) Impervious Surfaces raster in which each cell value represented the percentage of impervious surfaces within that 30-meter cell. Please refer to the process steps and https://glcwra.wim.usgs.gov/ for further explanation on the methods. Impervious surfaces are considered unsuitable for wetland restoration and therefore resulted in lower Index Composite scores in the SBRA composite model. The purpose for releasing version 2.0 of these datasets is that they were created with more recent and more accurate input data. For changes between versions 1.0 and 2.0, please see the Release History text file. 2024 publication date Complete None planned -84.2819 -82.4770 44.5433 43.1145 ISO 19115 Topic Category environment geoscientificInformation inlandWaters Marine Realms Information Bank (MRIB) keywords lake lakeshore wetland wetland restoration stream river hydrology resource management USGS Thesaurus hydrology natural resource management water quality remediation wetland ecosystems Holocene Common geographic areas Great Lakes Lake Huron Saginaw Michigan None. Please see 'Distribution Info' for details. None. Users are advised to read the dataset's metadata thoroughly to understand appropriate use and data limitations. Kurt P Kowalski U.S. Geological Survey, MIDCONTINENT REGION Research Ecologist mailing address

1451 Green Rd

Ann Arbor MI 48105 US 734-214-9308 734-994-8780 kkowalski@usgs.gov The GLCWRA was produced with funding provided by the Great Lakes Restoration Initiative (GLRI) and in collaboration with the New College of Florida. Digital datasets obtained from public repositories and datasets including the National Hydrography Dataset (NHD), National Wetland Index (NWI), 3D Elevation Program (3DEP), U.S. Census Bureau, National Geospatial Program, U.S. Fish and Wildlife Service, National Oceanic and Atmospheric Association (NOAA), Protected Areas Database of the U.S. (PAD-US), National Land Cover Database (NLDC), Gridded Soil Survey Geographic Database (gSSURGO), Coastal Change Analysis Program (C-CAP) U.S. Geological Survey 2016 application/service Geonarrative map website for GLCWRA study https://glcwra.wim.usgs.gov/ The attribute values of this dataset were inspected and confirmed to be within the proper range of values. The attribute values were reviewed, and spatial data was visually inspected to verify the that the data values and their locations accurately describe the purpose of the data. This dataset is considered complete for the information presented, as described in the abstract. This dataset provides coverage for the entire Saginaw Bay Restoration Assessment study area. Approximately 20% of the spatial data was visually inspected to verify the positional accuracy of its features. The review consisted of comparing the spatial data to its input datasets and to underlying GIS basemaps. While this data has been reviewed, the spatial data is only as spatially accurate as the input data sources. This dataset does not have a vertical component, so testing for vertical accuracy was not necessary. U.S. Geological Survey Jon Dewitz 20230630 raster digital data https://doi.org/10.5066/P9JZ7AO3 https://www.mrlc.gov/data https://www.mrlc.gov/data-services-page Digital and/or Hardcopy 2001 2021 observed NLCD Identified the areas with impervious surfaces within the study area. Using ArcGIS Pro 3.0.3, the NLCD Imperious Surfaces raster was clipped to the SBRA study area using the 'Clip' tool (Snap Raster = SBRA DEM, Output Coordinate System = UTM Zone 17N). 20230829 Raster Grid Cell 15480 14078 1 Universal Transverse Mercator 17 0.9996 -81.0 0.0 500000.0 0.0 row and column 10.0 10.0 meters North_American_Datum_1983 GRS 1980 6378137.0 298.2572221010042 SBRA_P5_Impervious_Surfaces.tif A raster dataset (in geoTIFF format) representing the percentage of impervious surfaces in the SBRA study area. Producer Defined Value Values represent the percent of impervious surfaces within each raster cell. Producer Defined 0 100 SBRA_P5_Impervious_Surfaces.zip contains a TIF raster image (SBRA_P5_Impervious_Surfaces.tif) and associated metadata (SBRA_P5_Impervious_Surfaces.tif.xml). NA GS ScienceBase U.S. Geological Survey mailing address

Denver Federal Center, Building 810, Mail Stop 302

Denver CO 80225 United States 1-888-275-8747 sciencebase@usgs.gov Unless otherwise stated, all data, metadata and related materials are considered to satisfy the quality standards relative to the purpose for which the data were collected. Although these data and associated metadata have been reviewed for accuracy and completeness and approved for release by the U.S. Geological Survey (USGS), no warranty expressed or implied is made regarding the display or utility of the data on any other system or for general or scientific purposes, nor shall the act of distribution constitute any such warranty. Digital Data https://doi.org/10.5066/P9EFH72U None 20240515 Kurt P Kowalski U.S. Geological Survey, MIDCONTINENT REGION Research Ecologist mailing address

1451 Green Rd

Ann Arbor MI 48105 US 734-214-9308 734-994-8780 kkowalski@usgs.gov FGDC Content Standard for Digital Geospatial Metadata FGDC-STD-001-1998 20250814 13561200 TRUE