Web map displaying Wisconsin DNR-produced Digital Elevation Model (DEM) and Hillshade image services, along with their index layer, in formats that are clickable and can be symbolized and filtered. This map can also be used as a starting point to create a new map. To open the web map from DNR's GIS Open Data Portal, click the View Metadata: link to the right of the description, then click Open in Map Viewer.

Open-file report; contains unpublished data that has not yet been peer-reviewed.

Note: This service is only for using online; full resolution downloads are not supported. To enable pop ups when opening this in a new web map, then click the ellipsis (three blue dots) under the layer name in the contents, and choose Enable Pop-up.Image service created from Digital Elevation Models (DEMs) derived from county-produced LiDAR covering Wisconsin. Elevation units are in feet. This service was last updated May 2023. It can be used in conjunction with its associated Index layer, DEM and Hillshade from LiDAR - Index, to determine flight years of source LiDAR and resolution of source DEMs. Also see the Index layer item details for detailed information about counties included in this service and in related services: DEM from LiDAR (Units in Meters) and Hillshade from LiDAR.Some areas display as data gaps (white artifacts) when the service is viewed at statewide scales but display normally when zoomed in to scales of approximately 1:1,000,000 or larger. We hope to address the no-data areas and small-scale data gaps in future updates to this service. The source DEMs have not been hydrologically conditioned. The Vertical Datum for the DEMs is NAVD88.WI DNR acknowledges the USDA Natural Resources Conservation Service, USGS, FEMA, the Southeastern WI Regional Planning Commission, and the individual counties listed in DEM and Hillshade from LiDAR - Index, for making source data available. For more information, visit https://dnr.wi.gov/feedback/ and choose Geographic Information Systems Data as the subject.

This topobathymetric digital elevation model (TBDEM) mosaic represents the topography and bathymetry for the Milwaukee River Estuary in Milwaukee, Wisconsin and adjacent terrestrial and Lake Michigan nearshore coastal areas. The TBDEM was produced in support of modeling and for developing a physical habitat framework to help with understanding the effects from multidirectional currents and seiche effects associated with the mixing of river flows with Lake Michigan backwater. The TBDEM mosaic is built off existing terrestrial, nearshore, and estuary frameworks developed for other areas around the Great Lakes and the Milwaukee River Harbor. Ranging from 2008-2015, land elevations derived from lidar and historic topographic surveys and bathymetric multibeam sonar were used to generate the seamless Milwaukee River Estuary TBDEM from four different data frameworks: (1) 2015 Milwaukee River Estuary Bathymetry (Dow, 2018), (2) 2015 SEWRPC Topographic LIDAR for Southeast, Wisconsin (Office for Coastal Management (OCM) Partners, 2018), (3) 2012 NOAA Digital Coast Topographic and Bathymetric LIDAR (OCM, 2017), and (4) 2008 NOAA Digital Coast Topographic and Bathymetric LIDAR (OCM, 2008). The TBDEM is provided as a 0.6-meter resolution raster dataset in GeoTIFF format. References include: (1) Dow, Brennan,2018, Assessment and mapping of the Milwaukee Estuary Habitat, Theses and Dissertations. 1785: Milwaukee, University of Wisconsin - Milwaukee, M.S., 49 p., [Also available at https://dc.uwm.edu/etd/1785]. (2) Office for Coastal Management (OCM) Partners, 2018: 2015 SEWRPC Lidar: Southeast WI (Milwaukee, Ozaukee, Walworth, Washington, Waukesha Counties) (published 20180619): NOAA National Centers for Environmental Information, accessed January 25, 2021 at https://www.fisheries.noaa.gov/inport/item/58870 (3) Office for Coastal Management (OCM) Partners, 2017: 2012 USACE Great Lakes Topobathy Lidar: Lake Michigan (published 20170702): NOAA National Centers for Environmental Information, accessed January 25, 2021 at https://www.fisheries.noaa.gov/inport/item/49736. (4) Office for Coastal Management (OCM) Partners, 2008: 2008 USACE Great Lakes Topo/Bathy Lidar: Wisconsin (published 2008): NOAA National Centers for Environmental Information, accessed January 25, 2021, https://www.fisheries.noaa.gov/inport/item/50070.

Open-file report; contains unpublished data that has not yet been peer-reviewed.

The vertical land change activity focuses on the detection, analysis, and explanation of topographic change. These detection techniques include both quantitative methods, for example, using difference metrics derived from multi-temporal topographic digital elevation models (DEMs), such as, light detection and ranging (lidar), National Elevation Dataset (NED), Shuttle Radar Topography Mission (SRTM), and Interferometric Synthetic Aperture Radar (IFSAR), and qualitative methods, for example, using multi-temporal aerial photography to visualize topographic change. The geographic study areas of this activity are in Chippewa, Eau Claire, Jackson, Monroe, Trempealeau, and Wood counties in west central Wisconsin. Available multi-temporal lidar, NED, SRTM, IFSAR, and other topographic elevation datasets, as well as aerial photography and multi-spectral image data were identified and downloaded for these study area counties. Locations of industrial sand mines and processing plants (vector features) were obtained from the Wisconsin Department of Natural Resources at http://dnr.wi.gov/topic/Mines/ISMMap.html, and from the Wisconsin Center for Investigative Journalism, October 2012, update at https://fusiontables.google.com/DataSource?docid=17nDFI4iUPOdyDOEWU7Vu1ONMiVofa3aWR_Gs-Zk#rows:id=1. These features were used to spatially validate some of the mining locations that were predefined with Landsat-detected mining locations (polygons). Previously developed differencing methods (Gesch, 2006) were used to develop difference raster datasets of NED/SRTM (1961-2000 date range) and SRTM/IFSAR (2000-2008 date range). The difference rasters were evaluated to exclude difference values that were below a specified vertical change threshold, which was applied spatially by National Land Cover Dataset (NLCD) 1992 and 2006 land cover type, respectively. This spatial application of the vertical change threshold values improved the overall ability to detect vertical change because threshold values in bare earth areas were distinguished from threshold values in heavily vegetated areas. Lidar point cloud data and high-resolution (1-3 m) lidar DEMs were acquired for the Wisconsin six-county study area from Chippewa County Land Records Division, Chippewa Falls, WI; Eau Claire County, Eau Claire, WI; Jackson County and Jackson County Land Information Council, Black River Falls, WI; Monroe County, Sparta, WI; Trempealeau County, Whitehall, WI; and Wood County Planning and Zoning, Wisconsin Rapids, WI. ESRI Mosaic Datasets were generated from lidar point-cloud data and available topographic DEMs for the specified study areas. These data were analyzed to estimate volumetric changes on the land surface at three different periods with lidar acquisitions collected for Chippewa County, WI on May 15, 2011 and April 14, 2012; Eau Claire County, WI in 2013; Jackson County, WI in April, 2015; Monroe County, WI April 11-12, 2010; Trempealeau County, WI April 26, 2014 to May 5, 2014; and Wood County, WI March 21-31, 2015. The most recent difference analysis consisting of a raster dataset time span (2008-2015 date range) was analyzed by differencing the Wisconsin lidar-derived DEMs and an IFSAR-derived dataset. The IFSAR-derived data were resampled to the resolution of the lidar DEM (approximately 1-m resolution) and compared with the lidar-derived DEM. Land cover based threshold values were applied spatially to detect vertical change using the IFSAR/lidar difference dataset. Chippewa County lidar DEM metadata reported the root mean square error (RMSE) of 0.083 m. Eau Claire County lidar DEM metadata described an RMSE of 18.5 cm that supports 2 ft contours. Jackson County lidar DEM metadata reported that a comparison of the ground survey versus lidar model values indicated an RMSE of 0.214 ft (0.065 m). Monroe County lidar DEM metadata was obtained from the U.S. Interagency Elevation Inventory, which indicated an RMSE of 0.106 m. Trempealeau County lidar DEM included metadata describing RMSE values for different land cover types. A comparison of the Trempealeau ground survey versus lidar model values indicated an overall vertical RMSE of 0.344 ft (0.105 m). An RMSE was reported for each of the following land cover types in Trempealeau County: Urban: 0.169 US Survey Feet (0.051 m); Low Grass: 0.150 US Survey Feet (0.046 m); Tall Grass: 0.489 US Survey Feet (0.149 m); Low Trees: 0.432 US Survey Feet (0.132 m); Tall Trees: 0.342 US Survey Feet (0.104 m). This allowed additional refinement of the spatially explicit threshold values. Wood County lidar DEM RMSE was obtained from the US Interagency Elevation Inventory (0.122 m).References: Gesch, Dean B., 2006, An inventory and assessment of significant topographic changes in the United States Brookings, S. Dak., South Dakota State University, Ph.D. dissertation, 234 p, at https://topotools.cr.usgs.gov/pdfs/DGesch_dissertation_Nov2006.pdf.

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These vector contour lines are derived from the 3D Elevation Program using automated and semi-automated processes. They were created to support 1:24,000-scale topographic map products, but are also published in this GIS vector format. Contour intervals are assigned by 7.5-minute quadrangle, so this vector dataset is not visually seamless across quadrangle boundaries. The vector lines have elevation attributes (in feet above mean sea level on NAVD88), but this dataset does not carry line symbols or annotation.

Open-file report; contains unpublished data that has not yet been peer-reviewed.

Collection of most of the plates accompanying Chamberlin's four-volume Geology of Wisconsin: Survey of 1873-1879.

These data were created as part of the National Oceanic and Atmospheric Administration Office for Coastal Management's efforts to create an online mapping viewer called the NOAA Lake Level Viewer. It depicts potential lake level rise and fall and its associated impacts on the nation's coastal areas. The purpose of the mapping viewer is to provide coastal managers and scientists with a preliminary look at lake level change, coastal flooding impacts, and exposed lakeshore. The viewer is a screening-level tool that uses nationally consistent data sets and analyses. Data and maps provided can be used at several scales to help gauge trends and prioritize actions for different scenarios. The NOAA Lake Level Viewer may be accessed at: https://coast.noaa.gov/llv. This metadata record describes the Lake Michigan digital elevation model (DEM), which is a part of a series of DEMs produced for the National Oceanic and Atmospheric Administration Office for Coastal Management's Lake Level Viewer described above. This DEM includes the best available lidar, US Army Corps of Engineer dredge surveys, and National Park Service multibeam data known to exist at the time of DEM creation that met project specifications. This DEM includes data for Allegan, Antrim, Benzie, Berrien, Charlevoix, Delta, Emmet, Grand Traverse, Leelanau, Mackinac, Manistee, Mason, Menominee, Muskegon, Oceana, Ottawa, Schoolcraft, and Van Buren counties in Michigan; Lake, La Porte, and Porter Counties in Indiana, Cook and Lake Counties in Illinois, and Brown, Door, Kenosha, Kewaunee, Manitowoc, Marinette, Milwaukee, Oconto, Ozaukee, Racine, and Sheboygan Counties in Wisconsin. The DEM was produced from the following lidar data sets: 1. 2016 NOAA Topobathy Lidar: Upper Lake Michigan Islands 2. 2015 FEMA Marinette County 3. 2013 Indiana Statewide Lidar Collection: Lake, La Porte, Tippecanoe, Newton, Jasper and Porter County Buy-Up 4. 2013 Muskegon County, Michigan Lidar Co-Op 5. 2013 USACE NCMP Topobathy Lidar: Lake Michigan North (MI) 6. 2012 USACE NCMP Topobathy Lidar: Lake Michigan (MI,WI) 7. 2012 USACE NCMP Topobathy Lidar: Lake Michigan (IL,IN,MI,WI) 8. 2010 Brown County Lidar 9. 2008 USACE NCMP Topobathy Lidar: Lake Michigan (IN) 10. 2008 USACE NCMP Topobathy Lidar: Lake Michigan (WI) 11. 2008 USACE NCMP Topobathy Lidar: Lake Michigan (IL) 12. 2008 USACE NCMP Topobathy Lidar: Lake Michigan (MI) 13. 2007 USACE NCMP Topobathy BE Lidar: Lake Michigan (MI) and Lake Erie (PA) 14. 2007 ARRA Lidar: Lake County (IL) 15. 2006 USACE NCMP Topobathy Lidar: Lake Michigan (IN), Lake Erie (OH,PA), Lake Huron (MI) The DEM was produced from the following sonar data sets: 16. 2015 USACE Detroit District, Port Washington Harbor, WI 17. 2015 USACE Detroit District, South Haven Harbor, MI 18. 2015 USACE Detroit District, Washington Island (Detroit Harbor), WI 19. 2015 USACE Detroit District, Washington Island (Jackson Harbor), WI 20. 2015 USACE Detroit District, Grand Haven Harbor, MI 21. 2015 USACE Detroit District, Pentwater Harbor, MI 22. 2015 USACE Detroit District, Pensaukee Harbor, WI 23. 2015 USACE Detroit District, St. Joseph Harbor, MI 24. 2015 USACE Detroit District, Manistee Harbor, MI 25. 2015 USACE Detroit District, Green Bay Harbor, WI 26. 2015 USACE Detroit District, Saugatuck Harbor, MI 27. 2015 USACE Detroit District, Oconto Harbor, WI 28. 2015 USACE Detroit District, White Lake Harbor, MI 29. 2015 USACE Detroit District, Manistique Harbor, MI 30. 2014 USACE Detroit District, Milwaukee Harbor, WI 31. 2014 USACE Detroit District, Frankfort Harbor, MI 32. 2014 USACE Detroit District, St. Joseph Harbor, MI 33. 2014 USACE Detroit District, Holland Harbor, MI 34. 2014 USACE Chicago District, Burns Waterway Harbor, IN 35. 2014 USACE Chicago District, Burns Small Boat Harbor, IN 36. 2014 USACE Chicago District, Michigan City, IN 37. 2014 USACE Chicago District, Waukegan Harbor, IL 38. 2014 USACE Chicago District, Calumet River, IL 39. 2014 USACE Detroit District, Menominee Harbor, MI/WI The DEM was produced from the following NPS multibeam sonar data sets: 40. 2011, National Park Service, Sleeping Bear Dunes National Lakeshore Multibeam Sonar 41. 2012, National Park Service, Sleeping Bear Dunes National Lakeshore Multibeam Sonar The DEM is referenced vertically to the North American Vertical Datum of 1988 (NAVD88) with vertical units of meters and horizontally to the North American Datum of 1983 (NAD83). The resolution of the DEM is approximately 3 meters.

The U.S. Army Corps of Engineers' Upper Mississippi River Restoration (UMRR) Program Long Term Resource Monitoring (LTRM) element has overseen the collection, processing, and serving of bathymetric data since 1989. A systemic data collection for the Upper Mississippi River System (UMRS) was completed in 2010. Water depth in aquatic systems is important for describing the physical characteristics of a river. Bathymetric maps are used for conducting spatial inventories of the aquatic habitat and detecting bed and elevation changes due to sedimentation. Bathymetric data is widely used, specifically for studies of water level management alternatives, modeling navigation impacts and hydraulic conditions, and environmental assessments such as vegetation distribution patterns. The bathymetry "footprint" is a database that can be used as a tool to provide a quick search of collection dates corresponding to bathymetric coverages within each LTRM pool.

Layered GeoPDF 7.5 Minute Quadrangle Map. Layers of geospatial data include orthoimagery, roads, grids, geographic names, elevation contours, hydrography, and other selected map features.

Layered GeoPDF 7.5 Minute Quadrangle Map. Layers of geospatial data include orthoimagery, roads, grids, geographic names, elevation contours, hydrography, and other selected map features.

Layered GeoPDF 7.5 Minute Quadrangle Map. Layers of geospatial data include orthoimagery, roads, grids, geographic names, elevation contours, hydrography, and other selected map features.

These data are part of a larger USGS project to develop an updated geospatial database of mines, mineral deposits and mineral regions in the United States. Mine and prospect-related symbols, such as those used to represent prospect pits, mines, adits, dumps, tailings, etc., hereafter referred to as “mine” symbols or features, are currently being digitized on a state-by-state basis from the 7.5-minute (1:24,000-scale) and the 15-minute (1:48,000 and 1:62,500-scale) archive of the USGS Historical Topographic Maps Collection, or acquired from available databases (California and Nevada, 1:24,000-scale only). Compilation of these features is the first phase in capturing accurate locations and general information about features related to mineral resource exploration and extraction across the U.S. To date, the compilation of 500,000-plus point and polygon mine symbols from approximately 67,000 maps of 22 western states has been completed: Arizona (AZ), Arkansas (AR), California (CA), Colorado (CO), Idaho (ID), Iowa (IA), Kansas (KS), Louisiana (LA), Minnesota (MN), Missouri (MO), Montana (MT), North Dakota (ND), Nebraska (NE), New Mexico (NM), Nevada (NV), Oklahoma (OK), Oregon (OR), South Dakota (SD), Texas (TX), Utah (UT), Washington (WA), and Wyoming (WY). The process renders not only a more complete picture of exploration and mining in the western U.S., but an approximate time line of when these activities occurred. The data may be used for land use planning, assessing abandoned mine lands and mine-related environmental impacts, assessing the value of mineral resources from Federal, State and private lands, and mapping mineralized areas and systems for input into the land management process. The data are presented as three groups of layers based on the scale of the source maps. No reconciliation between the data groups was done.

Layered GeoPDF 7.5 Minute Quadrangle Map. Layers of geospatial data include orthoimagery, roads, grids, geographic names, elevation contours, hydrography, and other selected map features.

The United States has an average elevation of roughly 2,500 feet (763m) above sea level, however there is a stark contrast in elevations across the country. Highest states Colorado is the highest state in the United States, with an average elevation of 6,800 feet (2,074m) above sea level. The 10 states with the highest average elevation are all in the western region of the country, as this is, by far, the most mountainous region in the country. The largest mountain ranges in the contiguous western states are the Rocky Mountains, Sierra Nevada, and Cascade Range, while the Appalachian Mountains is the longest range in the east - however, the highest point in the U.S. is Denali (Mount McKinley), found in Alaska. Lowest states At just 60 feet above sea level, Delaware is the state with the lowest elevation. Delaware is the second smallest state, behind Rhode Island, and is located on the east coast. Larger states with relatively low elevations are found in the southern region of the country - both Florida and Louisiana have an average elevation of just 100 feet (31m) above sea level, and large sections of these states are extremely vulnerable to flooding and rising sea levels, as well as intermittent tropical storms.

Layered GeoPDF 7.5 Minute Quadrangle Map. Layers of geospatial data include orthoimagery, roads, grids, geographic names, elevation contours, hydrography, and other selected map features.

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