36 datasets found
  1. Wisconsin DEM and Hillshade from LiDAR - Web Map

    • hub.arcgis.com
    • data-wi-dnr.opendata.arcgis.com
    • +1more
    Updated Jan 17, 2019
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    Wisconsin Department of Natural Resources (2019). Wisconsin DEM and Hillshade from LiDAR - Web Map [Dataset]. https://hub.arcgis.com/maps/wi-dnr::wisconsin-dem-and-hillshade-from-lidar-web-map/about
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    Dataset updated
    Jan 17, 2019
    Dataset authored and provided by
    Wisconsin Department of Natural Resourceshttp://dnr.wi.gov/
    Area covered
    Description

    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.

  2. U

    Topobathymetric Digital Elevation Model (TBDEM) of the Milwaukee River...

    • data.usgs.gov
    • datasets.ai
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    Jana Stewart; Faith Fitzpatrick; Brennan Dow; Brandon Krumwiede, Topobathymetric Digital Elevation Model (TBDEM) of the Milwaukee River Estuary, Milwaukee, Wisconsin and adjacent terrestrial and Lake Michigan nearshore coastal areas [Dataset]. http://doi.org/10.5066/P984MLKX
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    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Authors
    Jana Stewart; Faith Fitzpatrick; Brennan Dow; Brandon Krumwiede
    License

    U.S. Government Workshttps://www.usa.gov/government-works
    License information was derived automatically

    Time period covered
    Jan 1, 2008 - Dec 31, 2015
    Area covered
    Lake Michigan, Michigan, Milwaukee, Milwaukee River, Wisconsin
    Description

    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 (Offi ...

  3. 2015 FEMA Lidar: Marinette County, WI

    • fisheries.noaa.gov
    las/laz - laser
    Updated Aug 30, 2015
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    OCM Partners (2015). 2015 FEMA Lidar: Marinette County, WI [Dataset]. https://www.fisheries.noaa.gov/inport/item/58940
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    las/laz - laserAvailable download formats
    Dataset updated
    Aug 30, 2015
    Dataset provided by
    OCM Partners, LLC
    Time period covered
    Apr 15, 2015 - Apr 24, 2015
    Area covered
    Description

    The collection area consists of 1,430 square miles, the entirety of Marinette County in Wisconsin.. Specifications listed below are based on FEMA Procedure Memorandum No. 61 Standards for LiDAR and Other High Quality Digital Topography. This collection specification is the equivalent of a 2 foot contour accuracy, and was collected with a nominal pulse spacing of 1.3 meters. The airbo...

  4. d

    Vertical Land Change, Chippewa, Eau Claire, Jackson, Monroe, Trempealeau,...

    • search.dataone.org
    • data.usgs.gov
    • +3more
    Updated Jun 29, 2017
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    U.S. Geological Survey; Earth Resources Observation & Science (EROS) Center (2017). Vertical Land Change, Chippewa, Eau Claire, Jackson, Monroe, Trempealeau, and Wood Counties, Wisconsin [Dataset]. https://search.dataone.org/view/b36dbcfa-794e-4e4d-982d-643dc5daf674
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    Dataset updated
    Jun 29, 2017
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Authors
    U.S. Geological Survey; Earth Resources Observation & Science (EROS) Center
    Time period covered
    Jan 1, 1961 - Apr 30, 2015
    Area covered
    Variables measured
    VOLUME, MINE_ID, SRTM_CUT, IFSAR_CUT, LIDAR_CUT, POLY_AREA, SRTM_FILL, IFSAR_FILL, LIDAR_FILL
    Description

    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.

  5. a

    Wisconsin Hillshade from LiDAR

    • data-wi-dnr.opendata.arcgis.com
    Updated Jan 10, 2019
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    Wisconsin Department of Natural Resources (2019). Wisconsin Hillshade from LiDAR [Dataset]. https://data-wi-dnr.opendata.arcgis.com/datasets/d5a4498fe0294f92a8b6729948a7d71d
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    Dataset updated
    Jan 10, 2019
    Dataset authored and provided by
    Wisconsin Department of Natural Resources
    Area covered
    Description

    Note: This service is only for using online; full resolution downloads are not supported. Hillshade image service created from Digital Elevation Models (DEMs) derived from county-produced LiDAR covering several Wisconsin counties, with a vertical exaggeration factor of 2. This service was last updated in 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 DEM from LiDAR (Units in Feet).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.

    The Hillshade is intended for visualization of the landscape, rather than analysis. When queried, the Hillshade pixel values do not indicate elevation; instead, the pixel values range from 0 to 255 because the image is rendered as an 8-bit greyscale image. If elevation values are needed, use the LiDAR-Derived DEM Imagery Layer.

    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.

  6. c

    Boundaries

    • cacgeoportal.com
    Updated Dec 7, 2021
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    Living Atlas – Landscape Content (2021). Boundaries [Dataset]. https://www.cacgeoportal.com/datasets/LandscapeTeam::boundaries-2
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    Dataset updated
    Dec 7, 2021
    Dataset authored and provided by
    Living Atlas – Landscape Content
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Description

    Named Landforms of the World version 2 (NLWv2) contains four sub-layers representing geomorphological landforms, provinces, divisions, and their respective cartographic boundaries. The latter supports map making, while the first three represent basic units, such as landforms, which comprise provinces, and provinces comprise divisions. NLW is a substantial update to World Named Landforms in both compilation method and the attributes that describe each landform. For more details, please refer to our paper, Named Landforms of the World: A Geomorphological and Physiographic Compilation, in Annals of the American Association of Geographers. July 2, 2025: We have made Named Landforms of the World v3 (NLWv3) available. Please explore this group containing all of the layers and data. NLWv2 will remain available. Landforms are commonly defined as natural features on the surface of the Earth. The National Geographic Society specifies terrain as the basis for landforms and lists four major types: mountains, hills, plateaus, and plains. Here, however, we define landforms in a richer way that includes properties relating to underlying geologic structure, erosional and depositional character, and tectonic setting and processes. These characteristics were asserted by Dr. Richard E. Murphy in 1968 in his map, titled Landforms of the World. We blended Murphy"s definition for landforms with the work E.M. Bridges, who in his 1990 book, World Geomorphology, provided a globally consistent description of geomorphological divisions, provinces, and sections to give names to the landform regions of the world. AttributeDescriptionBridges Full NameFull name from E.M. Bridges" 1990 "World Geomorphology" Division and if present province and section - intended for labeling print maps of small extents. Bridges DivisionGeomorphological Division as described in E.M. Bridges" 1990 "World Geomorphology" - All Landforms have a division assigned, i.e., no nulls. Bridges ProvinceGeomorphological Province as described in E.M. Bridges" 1990 "World Geomorphology" - Not all divisions are subdivided into provinces. Bridges SectionGeomorphological Section as described in E.M. Bridges" 1990 "World Geomorphology" - Not all provinces are subdivided into sections.StructureLandform Structure as described in Richard E. Murphy"s 1968 "Landforms of the World" map. Coded Value Domain. Values include: - Alpine Systems: Area of mountains formed by orogenic (collisions of tectonic plates) processes in the past 350 to 500 million years. - Caledonian/Hercynian Shield Remnants: Area of mountains formed by orogenic (collisions of tectonic plates) processes 350 to 500 million years ago. - Gondwana or Laurasian Shields: Area underlaid by mostly crystalline rock formations fromed one billion or more years ago and unbroken by tectonic processes. - Rifted Shield Areas: fractures or spreading along or adjacent to tectonic plate edges. - Isolated Volcanic Areas: volcanic activity occurring outside of Alpine Systems and Rifted Shields. - Sedimentary: Areas of deposition occurring within the past 2.5 million years Moist or DryLandform Erosional/Depositional variable as described in Richard E. Murphy"s 1968 "Landforms of the World" map. Coded Value Domain. Values include: - Moist: where annual aridity index is 1.0 or higher, which implies precipitation is absorbed or lost via runoff. - Dry: where annual aridity index is less than 1.0, which implies more precipitation evaporates before it can be absorbed or lost via runoff. TopographicLandform Topographic type variable as described in Richard E. Murphy"s 1968 "Landforms of the World" map. Karagulle et. al. 2017 - based on rich morphometric characteristics. Coded Value Domain. Values include: - Plains: Areas with less than 90-meters of relief and slopes under 20%. - Hills: Areas with 90- to 300-meters of local relief. - Mountains: Areas with over 300-meters of relief - High Tablelands: Areas with over 300-meters of relief and 50% of highest elevation areas are of gentle slope. - Depressions or Basins: Areas of land surrounded land of higher elevation. Glaciation TypeLandform Erosional/Depositional variable as described in Richard E. Murphy"s 1968 "Landforms of the World" map. Values include: - Wisconsin/Wurm Glacial Extent: Areas of most recent glaciation which formed 115,000 years ago and ended 11,000 years ago. - Pre-Wisconsin/Wurm Glacial Extent: Areas subjected only to glaciation prior to 140,000 years ago. ContinentAssigned by Author during data compilation. Bridges Short NameThe name of the smallest of Division, Province, or Section containing this landform feature. Murphy Landform CodeCombination of Richard E. Murphy"s 1968 "Landforms of the World" variables expressed as a 3- or 4- letter notation. Used to label medium scale maps. Area_GeoGeodesic area in km2. Primary PlateName of tectonic plate that either completely underlays this landform feature or underlays the largest portion of the landform"s area.Secondary PlateWhen a landform is underlaid by two or more tectonic plates, this is the plate that underlays the second largest area.3rd PlateWhen a landform is underlaid by three or more tectonic plates, this is the plate that underlays the third largest area.4th PlateWhen a landform is underlaid by four or more tectonic plates, this is the plate that underlays the fourth largest area.5th PlateWhen a landform is underlaid by five tectonic plates, this is the plate that underlays the fifth largest area.NotesContains standard text to convey additional tectonic process characteristics. Tectonic ProcessAssigns values of orogenic, rift zone, or above subducting plate. These data are also available as an ArcGIS Pro Map Package: Named_Landforms_of_the_World_v2.0.mpkx.These data supersede the earlier v1.0: World Named Landforms. Change Log:DateDescription of ChangeJuly 20, 2022Corrected spelling of Guiana from incorrect representation, "Guyana", used by Bridges.July 27, 2022Corrected Structure coded value domain value, changing "Caledonian/Hercynian Shield" to "Caledonian , Hercynian, or Appalachian Remnants". Cite as: Frye, C., Sayre R., Pippi, M., Karagulle, Murphy, A., D. Soller, D.R., Gilbert, M., and Richards, J., 2022. Named Landforms of the World. DOI: 10.13140/RG.2.2.33178.93129. Accessed on:

  7. d

    ScienceBase Item Summary Page

    • datadiscoverystudio.org
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    U.S. Geological Survey, National Geospatial Technical Operations Center, ScienceBase Item Summary Page [Dataset]. http://datadiscoverystudio.org/geoportal/rest/metadata/item/edc8202d42c24ddb9655b9475b426da3/html
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    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Area covered
    Description

    Link to the ScienceBase Item Summary page for the item described by this metadata record. Service Protocol: Link to the ScienceBase Item Summary page for the item described by this metadata record. Application Profile: Web Browser. Link Function: information

  8. DEM and DSM Data Based on Leaf-off Lidar for the Core Area in CHEESEHEAD...

    • data.ucar.edu
    ascii
    Updated Dec 26, 2024
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    Philip Townsend; Ting Zheng (2024). DEM and DSM Data Based on Leaf-off Lidar for the Core Area in CHEESEHEAD Domain [Dataset]. http://doi.org/10.26023/19J9-8S9N-S50Y
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    asciiAvailable download formats
    Dataset updated
    Dec 26, 2024
    Dataset provided by
    University Corporation for Atmospheric Research
    Authors
    Philip Townsend; Ting Zheng
    Time period covered
    Jun 24, 2019 - Oct 11, 2019
    Area covered
    Description

    This dataset provides the digital elevation model (DEM) and digital surface model (DSM) for CHEESEHEAD core study area (10km ×10km). DEM and DSM are projected to WGS 84 / UTM zone 15N (EPSG:32615) at 1m spatial resolution. The unit for the height is foot. The DEM and DSM are mosaics from tiles for three counties: Ashland (2019), Iron (2019), and Price (2018). All the tiles are derived from leaf-off lidar point cloud collected by USGS and can be found at https://geodata.wisc.edu/?f%5Bdct_provenance_s%5D%5B%5D=WisconsinView . Tiles used in this dataset and quality for each tile are recorded in tile_lookup.csv The GeoData@Wisconsin is an online geoportal that provides discovery and access to Wisconsin geospatial data, imagery, and scanned maps. It is developed and maintained by the UW-Madison Geography Department's Robinson Map Library and State Cartographer's Office.

  9. d

    ScienceBase Item Summary Page

    • datadiscoverystudio.org
    + more versions
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    U.S. Geological Survey, National Geospatial Technical Operations Center (2017). ScienceBase Item Summary Page [Dataset]. http://datadiscoverystudio.org/geoportal/rest/metadata/item/de45145802bc47f98b899e222b7cc345/html
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    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Area covered
    Description

    Link to the ScienceBase Item Summary page for the item described by this metadata record. Service Protocol: Link to the ScienceBase Item Summary page for the item described by this metadata record. Application Profile: Web Browser. Link Function: information

  10. a

    Wisconsin DEM from LiDAR (Units in Feet)

    • hub.arcgis.com
    • data-wi-dnr.opendata.arcgis.com
    Updated Jan 14, 2019
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    Wisconsin Department of Natural Resources (2019). Wisconsin DEM from LiDAR (Units in Feet) [Dataset]. https://hub.arcgis.com/datasets/2b34b918351f4e4e942a084d00f01971
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    Dataset updated
    Jan 14, 2019
    Dataset authored and provided by
    Wisconsin Department of Natural Resources
    Area covered
    Description

    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.

  11. d

    UMRR Pool 4 Bathymetry Footprint

    • search.dataone.org
    Updated Jun 1, 2017
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    Jenny Hanson; Jayme Stone (2017). UMRR Pool 4 Bathymetry Footprint [Dataset]. https://search.dataone.org/view/78420812-32ba-4897-8b0f-1aae599272c4
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    Dataset updated
    Jun 1, 2017
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Authors
    Jenny Hanson; Jayme Stone
    Time period covered
    Aug 21, 1989 - Sep 14, 2001
    Area covered
    Variables measured
    Day, DATE, Year, Acres, Month, Method, Hectares, pts_acre, pts_hect, Join_Count, and 1 more
    Description

    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.

  12. d

    ScienceBase Item Summary Page

    • datadiscoverystudio.org
    Updated Jan 14, 2017
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    U.S. Geological Survey, National Geospatial Technical Operations Center (2017). ScienceBase Item Summary Page [Dataset]. http://datadiscoverystudio.org/geoportal/rest/metadata/item/5a17864386544671a61c9f73b664e897/html
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    Dataset updated
    Jan 14, 2017
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Area covered
    Description

    Link to the ScienceBase Item Summary page for the item described by this metadata record. Service Protocol: Link to the ScienceBase Item Summary page for the item described by this metadata record. Application Profile: Web Browser. Link Function: information

  13. Orthoimagery Submission for Dodge County, WI, USA - Fox Lake Physical Map...

    • data.wu.ac.at
    • datadiscoverystudio.org
    mr sid
    Updated Nov 14, 2017
    + more versions
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    Federal Emergency Management Agency, Department of Homeland Security (2017). Orthoimagery Submission for Dodge County, WI, USA - Fox Lake Physical Map Revision [Dataset]. https://data.wu.ac.at/schema/data_gov/NmNkYjRmMGMtNGU0OS00OGI5LTliZGItYzExN2IxNWM1MjNh
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    mr sidAvailable download formats
    Dataset updated
    Nov 14, 2017
    Dataset provided by
    Federal Emergency Management Agencyhttp://www.fema.gov/
    U.S. Department of Homeland Securityhttp://www.dhs.gov/
    License

    U.S. Government Workshttps://www.usa.gov/government-works
    License information was derived automatically

    Area covered
    0a1571219d63753b5175001a272e064008388017, United States
    Description

    Digital orthographic imagery datasets contain georeferenced images of the Earth's surface, collected by a sensor in which object displacement has been removed for sensor distortions and orientation, and terrain relief. Digital orthoimages have the geometric characteristics of a map and image qualities of a photograph. (Source: Circular A-16, p. 16)

  14. United States: average elevation in each state or territory as of 2005

    • statista.com
    Updated Aug 9, 2024
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    Statista (2024). United States: average elevation in each state or territory as of 2005 [Dataset]. https://www.statista.com/statistics/1325529/lowest-points-united-states-state/
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    Dataset updated
    Aug 9, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2005
    Area covered
    United States
    Description

    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.

  15. d

    USGS NED 1/3 arc-second Contours for Green Bay W, Wisconsin 20150422 1 x 1...

    • datadiscoverystudio.org
    filegdb v.10.1
    Updated Apr 22, 2015
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    U.S. Geological Survey, National Geospatial Program (2015). USGS NED 1/3 arc-second Contours for Green Bay W, Wisconsin 20150422 1 x 1 degree FileGDB 10.1 [Dataset]. http://datadiscoverystudio.org/geoportal/rest/metadata/item/01032703b5ed4d2183df8ecc58277ccd/html
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    filegdb v.10.1(23.587239)Available download formats
    Dataset updated
    Apr 22, 2015
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Area covered
    Description

    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.

  16. d

    Orthoimagery Submission for Waupaca County, WI, USA - MIP Waupaca Countywide...

    • catalog.data.gov
    Updated Sep 28, 2005
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    Wisconsin Department of Natural Resources (Point of Contact) (2005). Orthoimagery Submission for Waupaca County, WI, USA - MIP Waupaca Countywide DFIRM [Dataset]. https://catalog.data.gov/is/dataset/orthoimagery-submission-for-waupaca-county-wi-usa-mip-waupaca-countywide-dfirm
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    Dataset updated
    Sep 28, 2005
    Dataset provided by
    Wisconsin Department of Natural Resources (Point of Contact)
    Area covered
    Waupaca, Waupaca County, United States, Wisconsin
    Description

    Digital orthographic imagery datasets contain georeferenced images of the Earth's surface, collected by a sensor in which object displacement has been removed for sensor distortions and orientation, and terrain relief. Digital orthimages have the geometric charactierics of a map and image qualities of a photograph. (Source: Circular A-16, p.16)

  17. d

    UMRR Pool 12 Bathymetry Footprint

    • dataone.org
    Updated Jun 1, 2017
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    Jenny Hanson; Jayme Stone (2017). UMRR Pool 12 Bathymetry Footprint [Dataset]. https://dataone.org/datasets/930cf6c4-e1f9-451b-aadb-55d3a7b80278
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    Dataset updated
    Jun 1, 2017
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Authors
    Jenny Hanson; Jayme Stone
    Time period covered
    Dec 1, 1998 - Dec 31, 2010
    Area covered
    Variables measured
    Day, DATE, Year, Acres, Month, Method, Hectares, pts_acre, pts_hect, Join_Count, and 1 more
    Description

    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.

  18. Orthoimagery Submission for Columbia County, WI, USA - MIP Columbia Portion...

    • data.wu.ac.at
    • data.amerigeoss.org
    mr sid
    Updated Nov 14, 2017
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    Federal Emergency Management Agency, Department of Homeland Security (2017). Orthoimagery Submission for Columbia County, WI, USA - MIP Columbia Portion Baraboo River RiskMap DFIRM Update [Dataset]. https://data.wu.ac.at/schema/data_gov/N2ZjYmJjOTAtYzQyMi00MDNiLWIxOWYtOWM3OTc2M2UwNzdm
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    mr sidAvailable download formats
    Dataset updated
    Nov 14, 2017
    Dataset provided by
    Federal Emergency Management Agencyhttp://www.fema.gov/
    U.S. Department of Homeland Securityhttp://www.dhs.gov/
    License

    U.S. Government Workshttps://www.usa.gov/government-works
    License information was derived automatically

    Area covered
    64e957a75e3aee5927da919f25dcef38da5c56a5, United States
    Description

    Digital orthographic imagery datasets contain georeferenced images of the Earth's surface, collected by a sensor in which object displacement has been removed for sensor distortions and orientation, and terrain relief. Digital orthimages have the geometric charactierics of a map and image qualities of a photograph. (Source: Circular A-16, p. 16)

  19. a

    Named Landforms of the World v2

    • hub.arcgis.com
    Updated Dec 7, 2021
    + more versions
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    Living Atlas – Landscape Content (2021). Named Landforms of the World v2 [Dataset]. https://hub.arcgis.com/maps/f975b762b9ca447cb4b7dd1438133d09
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    Dataset updated
    Dec 7, 2021
    Dataset authored and provided by
    Living Atlas – Landscape Content
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    World,
    Description

    Named Landforms of the World (NLW) contains four sub-layers representing geomorphological landforms, provinces, divisions, and their respective cartographic boundaries. The latter is to support map making, while the first three represent basic units such landforms comprise provinces, and provinces comprise divisions. NLW is a substantial update to World Named Landforms in both compilation method and the attributes that describe each landform.For more details, please refer to our paper, Named Landforms of the World: A Geomorphological and Physiographic Compilation, in Annals of the American Assocation of Geographers.Landforms are commonly defined as natural features on the surface of the Earth. The National Geographic Society specifies terrain as the basis for landforms and lists four major types: mountains, hills, plateaus, and plains. Here, however, we define landforms in a richer way that includes properties relating to underlying geologic structure, erosional and depositional character, and tectonic setting and processes. These characteristics were asserted by Dr. Richard E. Murphy in 1968 in his map, titled Landforms of the World. We blended Murphy's definition for landforms with the work E.M. Bridges, who in his 1990 book, World Geomorphology, provided a globally consistent description of geomorphological divisions, provinces, and sections to give names to the landform regions of the world. AttributeDescription Bridges Full NameFull name from E.M. Bridges' 1990 "World Geomorphology" Division and if present province and section - intended for labeling print maps of small extents. Bridges DivisionGeomorphological Division as described in E.M. Bridges' 1990 "World Geomorphology" - All Landforms have a division assigned, i.e., no nulls. Bridges ProvinceGeomorphological Province as described in E.M. Bridges' 1990 "World Geomorphology" - Not all divisions are subdivided into provinces. Bridges SectionGeomorphological Section as described in E.M. Bridges' 1990 "World Geomorphology" - Not all provinces are subdivided into sections. StructureLandform Structure as described in Richard E. Murphy's 1968 "Landforms of the World" map. Coded Value Domain. Values include: - Alpine Systems: Area of mountains formed by orogenic (collisions of tectonic plates) processes in the past 350 to 500 million years. - Caledonian/Hercynian Shield Remnants: Area of mountains formed by orogenic (collisions of tectonic plates) processes 350 to 500 million years ago. - Gondwana or Laurasian Shields: Area underlaid by mostly crystalline rock formations fromed one billion or more years ago and unbroken by tectonic processes. - Rifted Shield Areas: fractures or spreading along or adjacent to tectonic plate edges. - Isolated Volcanic Areas: volcanic activity occurring outside of Alpine Systems and Rifted Shields. - Sedimentary: Areas of deposition occurring within the past 2.5 million years Moist or DryLandform Erosional/Depositional variable as described in Richard E. Murphy's 1968 "Landforms of the World" map. Coded Value Domain. Values include: - Moist: where annual aridity index is 1.0 or higher, which implies precipitation is absorbed or lost via runoff. - Dry: where annual aridity index is less than 1.0, which implies more precipitation evaporates before it can be absorbed or lost via runoff. TopographicLandform Topographic type variable as described in Richard E. Murphy's 1968 "Landforms of the World" map. Karagulle et. al. 2017 - based on rich morphometric characteristics. Coded Value Domain. Values include: - Plains: Areas with less than 90-meters of relief and slopes under 20%. - Hills: Areas with 90- to 300-meters of local relief. - Mountains: Areas with over 300-meters of relief - High Tablelands: Areas with over 300-meters of relief and 50% of highest elevation areas are of gentle slope. - Depressions or Basins: Areas of land surrounded land of higher elevation. Glaciation TypeLandform Erosional/Depositional variable as described in Richard E. Murphy's 1968 "Landforms of the World" map. Values include: - Wisconsin/Wurm Glacial Extent: Areas of most recent glaciation which formed 115,000 years ago and ended 11,000 years ago. - Pre-Wisconsin/Wurm Glacial Extent: Areas subjected only to glaciation prior to 140,000 years ago. ContinentAssigned by Author during data compilation. Bridges Short NameThe name of the smallest of Division, Province, or Section containing this landform feature. Murphy Landform CodeCombination of Richard E. Murphy's 1968 "Landforms of the World" variables expressed as a 3- or 4- letter notation. Used to label medium scale maps. Area_GeoGeodesic area in km2. Primary PlateName of tectonic plate that either completely underlays this landform feature or underlays the largest portion of the landform's area. Secondary PlateWhen a landform is underlaid by two or more tectonic plates, this is the plate that underlays the second largest area. 3rd PlateWhen a landform is underlaid by three or more tectonic plates, this is the plate that underlays the third largest area. 4th PlateWhen a landform is underlaid by four or more tectonic plates, this is the plate that underlays the fourth largest area. 5th PlateWhen a landform is underlaid by five tectonic plates, this is the plate that underlays the fifth largest area. NotesContains standard text to convey additional tectonic process characteristics. Tectonic ProcessAssigns values of orogenic, rift zone, or above subducting plate.

    These data are also available as an ArcGIS Pro Map Package: Named_Landforms_of_the_World_v2.0.mpkx.These data supersede the earlier v1.0: World Named Landforms.Change Log:

    DateDescription of Change July 20, 2022Corrected spelling of Guiana from incorrect representation, "Guyana", used by Bridges. July 27, 2022Corrected Structure coded value domain value, changing "Caledonian/Hercynian Shield" to "Caledonian , Hercynian, or Appalachian Remnants".

    Cite as:Frye, C., Sayre R., Pippi, M., Karagulle, Murphy, A., D. Soller, D.R., Gilbert, M., and Richards, J., 2022. Named Landforms of the World. DOI: 10.13140/RG.2.2.33178.93129. Accessed on:

  20. d

    USGS NED 1/3 arc-second Contours for Racine W, Wisconsin 20150424 1 x 1...

    • datadiscoverystudio.org
    filegdb v.10.1
    Updated Apr 24, 2015
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    U.S. Geological Survey, National Geospatial Program (2015). USGS NED 1/3 arc-second Contours for Racine W, Wisconsin 20150424 1 x 1 degree FileGDB 10.1 [Dataset]. http://datadiscoverystudio.org/geoportal/rest/metadata/item/cca9b8ae30a44f85bd83bcd4014f80c3/html
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    filegdb v.10.1(4.397803)Available download formats
    Dataset updated
    Apr 24, 2015
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Area covered
    Description

    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.

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Wisconsin Department of Natural Resources (2019). Wisconsin DEM and Hillshade from LiDAR - Web Map [Dataset]. https://hub.arcgis.com/maps/wi-dnr::wisconsin-dem-and-hillshade-from-lidar-web-map/about
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Wisconsin DEM and Hillshade from LiDAR - Web Map

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3 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Jan 17, 2019
Dataset authored and provided by
Wisconsin Department of Natural Resourceshttp://dnr.wi.gov/
Area covered
Description

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.

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