Pettersen-Bradford, Madison R. Hopkins, Anders L. Sanocki, Chris A. Bozimowski, Alexandra A. Kowalski, Kurt P. 20231108 vector digital data Reston, VA U.S. Geological Survey Pettersen-Bradford, M.R., Hopkins A.L., Sanocki, C.A., Bozimowski, A.A., Kowalski, K.P., 2023, Great Lakes Coastal Wetland Restoration Assessment (GLCWRA) Upper Peninsula, U.S.: Dikes: U.S. Geological Survey data release, https://doi:10.5066/P9IF2ZIW. https://doi.org/10.5066/P9IF2ZIW U.S. Geological Survey 20160101 vector and raster digital data and geonarrative map Reston, VA U.S. Geological Survey https://doi.org/10.5066/P9UAA4HY 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. The purpose of the dikes dataset is to provide the extent and location of dikes within the study area, since these are an important factor in controlling water flow to coastal wetlands. Hydrologic connection between the Great Lakes and coastal land areas are an important part of restoring coastal wetlands. 20211006 publication date Complete None planned -85.8680 -83.8765 46.4040 45.8155 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 wetland functions natural resource management habitat suitability indices water quality remediation wetland ecosystems Holocene USGS Metadata Identifier USGS:636d3354d34ed907bf6ba0f1 Common geographic areas Great Lakes Lake Michigan Lake Huron Michigan Mackinac Chippewa No data access constraints No data use constraints Chris A Sanocki U.S. Geological Survey, MIDCONTINENT REGION Geographer mailing address

2280 Woodale Drive

Mounds View MN 55112 US 763-783-3151 sanocki@usgs.gov Great Lakes Restoration Initiative (GLRI), USGS Great Lakes Science Center Pettersen-Bradford, Madison R. Sanocki, Chris A. Hopkins, Anders L. 2023 raster digital data Reston, VA U.S. Geological Survey https://doi.org/10.5066/P9YYDDKO Pettersen-Bradford, Madison R. Sanocki, Chris A. Hopkins, Anders L. 2023 raster digital data Reston, VA U.S. Geological Survey https://doi.org/10.5066/P9YYDDKO Pettersen-Bradford, Madison R. Sanocki, Chris A. Hopkins, Anders L. 2023 raster digital data Reston, VA U.S. Geological Survey https://doi.org/10.5066/P9YYDDKO Pettersen-Bradford, Madison R. Sanocki, Chris A. Hopkins, Anders L. 2023 raster digital data Reston, VA U.S. Geological Survey https://doi.org/10.5066/P9YYDDKO Pettersen-Bradford, Madison R. Sanocki, Chris A. Hopkins, Anders L. 2023 raster digital data Reston, VA U.S. Geological Survey https://doi.org/10.5066/P9YYDDKO Pettersen-Bradford, Madison R. Sanocki, Chris A. Hopkins, Anders L. 2023 raster digital data Reston, VA U.S. Geological Survey https://doi.org/10.5066/P9YYDDKO Pettersen-Bradford, Madison R. Sanocki, Chris A. Hopkins, Anders L. 2023 raster digital data Reston, VA U.S. Geological Survey https://doi.org/10.5066/P9YYDDKO Pettersen-Bradford, Madison R. Sanocki, Chris A. Hopkins, Anders L. 2023 raster digital data Reston, VA U.S. Geological Survey https://doi.org/10.5066/P9YYDDKO Pettersen-Bradford, Madison R. Sanocki, Chris A. Hopkins, Anders L. 2023 raster digital data Reston, VA U.S. Geological Survey https://doi.org/10.5066/P9YYDDKO Pettersen-Bradford, Madison R. Sanocki, Chris A. Hopkins, Anders L. 2023 vector digital data Reston, VA U.S. Geological Survey https://doi.org/10.5066/P9YYDDKO Pettersen-Bradford, Madison R. Sanocki, Chris A. Hopkins, Anders L. 2023 vector digital data Reston, VA U.S. Geological Survey https://doi.org/10.5066/P9YYDDKO Pettersen-Bradford, Madison R. Sanocki, Chris A. Hopkins, Anders L. 2023 vector digital data Reston, VA U.S. Geological Survey https://doi.org/10.5066/P9YYDDKO Chris Sanocki Kurt Kowalski Blake Draper Hans Vraga 2016 application/service U.S. Geological Survey https://glcwra.wim.usgs.gov/crsra/# No formal attribute accuracy tests were conducted. No formal logical accuracy tests were conducted. Dataset is considered complete for the information presented, as described in the abstract. This dataset provides coverage for the entire Upper Peninsula Restoration Assessment study area. No formal horizontal accuracy tests were conducted. The accuracy of this dataset varies based on the input sources; refer to the input source metadata files for more details. No formal vertical accuracy tests were conducted. The accuracy of this dataset varies based on the input sources; refer to the input source metadata files for more details. Pettersen-Bradford, Madison R. Sanocki, Chris A. Hopkins, Anders H. 2023 raster digital data https://doi.org/10.5066/P9YYDDKO Digital 20210812 publication date DEM Input of the slope layer used to identify land features that would inhibit lake flow inland in the UPRA Study Area. Pettersen-Bradford, Madison R. Sanocki, Chris A. Hopkins, Anders H. 2023 vector digital data https://doi.org/10.5066/P9YYDDKO Digital 20210805 publication date Study Area Identified the extent of the UPRA. New College of Florida Geospatial Analysis and Mapping McNair, Ian 20160926 GitHub Repository Python Code https://github.com/newgaminfo/GLCWRA-Code https://github.com/newgaminfo/GLCWRA-Code/blob/master/DikeLocator/DikeLocator%201.0.py Digital 20160926 publication date Dike Locator Code Code source for dike identification within the UPRA Study Area. The process steps to locate potential dikes were pulled from a Python script developed to perform the same task for GLCWRA by the New College of Florida Geospatial Analysis and Mapping (NewGAM) Lab. First, the slope raster was derived from the study area DEM. ArcGIS Pro's 'Slope' tool was used to do this; the input was the UPRA DEM, the output was call 'slope.tif', the Output Measurement was 'Degree', the Method was 'Planar', the snap raster was set to the DEM, and the coordinate system was NAD 1983 UTM Zone 16N. This snap raster and coordinate system were set as the default for all of the outputs in the following steps. 20211004 Next, the areas with slopes greater than 12 degrees were converted to polygons. First, using the 'Con' tool, all cells from the slope raster with a slope greater than 12 degrees were reclassified to '1'. Then, using the 'Extract by Attributes' tools, all the cells with a value of '1' were extracted to a new raster. Then, using the 'Raster to Polygon' tool, this raster was converted to a shapefile of polygons. In this geoprocess, 'Simplify polygons' was set to True, and 'Create multipart features' was set to 'SINGLE_OUTER_PART'. 20211004 Next, these polygons representing areas with slopes greater than 12 degrees were buffered with the ArcGIS Pro 'Buffer' tool. The buffer distance was 4 meters, the 'Side Type' was set to 'FULL', the 'End Type' was set to 'Round', 'Dissolve Type' was 'None' and the 'Method' was 'PLANAR'. These polygons were then run through the 'Generalize' tool where the tolerance was set to .5 meters. Lastly, the 'Multipart To Singlepart' tool was run on these polygons. 20211005 Finally, of all the polygons, those with an area of 500 square meters or greater were selected and written to a new shapefile was a coordinate system of NAD 1983 UTM Zone 16N. This final output identified 15,927 possible dikes within the Upper Peninsula Restoration Area. 20211006 Vector G-polygon 15927 Universal Transverse Mercator 16 0.9996 -87.0 0.0 500000.0 0.0 coordinate pair 0.6096 0.6096 meters North_American_Datum_1983 GRS_1980 6378137.0 298.257222101 UPRA_dikes.shp Vector layer (shapefile format) and table denoting dikes within the UPRA Study Area. Producer Defined FID Primary Key. ESRI Sequential unique whole numbers that are automatically generated. Shape Feature geometry. ESRI Polygon feature. Area Area of each polygon feature. Producer Defined 500.03907533 1738096.3893 Square meters U.S. Geological Survey GS ScienceBase 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 for other purposes, nor on all computer systems, nor shall the act of distribution constitute any such warranty. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. Digital Data https://doi.org/10.5066/P9IF2ZIW None 20250124 Great Lakes Science Center mailing and physical

1451 Green Road

Ann Arbor MI 48105 US 734-994-3331 GS_ASK_GLSC@usgs.gov FGDC Content Standard for Digital Geospatial Metadata FGDC-STD-001-1998