This dataset represents post-nourishment digital elevation models (DEMs) of the beach topography and near-shore bathymetry of Minnesota Point near the Duluth Entry of Lake Superior, Duluth, Minnesota. The Lidar DEM has a 1-meter (m; 3.28084 feet) cell size and was created from a LAS dataset of terrestrial light detection and ranging (lidar) data representing the beach topography. The topobathy DEMs have a 10-meter (m; 32.8084 feet) or a 5-meter (m; 16.4042 feet) cell size, and were created from a combined LAS dataset of lidar data representing the beach topography, and single-beam and multibeam sonar data representing the bathymetry. The survey area extends approximately 0.85 kilometers (0.5 miles) offshore, for an approximate 1.87 square kilometer surveyed area. Lidar data were collected using a boat mounted Velodyne VLP-16 unit. Multibeam sonar data were collected using a Norbit integrated wide band multibeam system compact (iWBMSc) sonar unit. Single-beam sonar data were collected using a Ceescope sonar unit. All elevation data were collected October 5-11, 2021. Methodology similar to Wagner, D.M., Lund, J.W., and Sanks, K.M., 2020 was used.

This dataset is a digital elevation model (DEM) of the beach topography of Lake Superior at the Duluth Entry, Duluth, Minnesota. The DEM has a 1-meter (m; 3.28084 feet) cell size and was created from a LAS dataset of terrestrial light detection and ranging (lidar) data representing the beach topography. Lidar data were collected September 23, 2020 using a boat mounted Velodyne unit. Multibeam sonar data were collected September 22-23, 2020 using a Norbit integrated wide band multibeam system compact (iWBMSc) sonar unit. Methodology similar to Wagner, D.M., Lund, J.W., and Sanks, K.M., 2020 was used.

2-foot and 10-foot elevation contours derived from the Spring 2012 Minnesota Department of Natural Resources (MN DNR) LiDAR dataset.

This dataset is a digital elevation model (DEM) of the beach topography of Lake Superior at Minnesota Point, Duluth, Minnesota. The DEM has a 1-meter (m; 3.28084 foot [ft]) cell size and was created from a LAS dataset of terrestrial light detection and ranging (LiDAR) data with an average point spacing of 0.137 m (0.45 ft). LiDAR data were collected August 10, 2019 using a boat-mounted Optech ILRIS scanner and methodology similar to that described by Huizinga and Wagner (2019).

This dataset is a pre-nourishment digital elevation model (DEM) of the beach topography of Minnesota Point near the Duluth Entry of Lake Superior, Duluth, Minnesota. The DEM has a 1-meter (m; 3.28084 feet) cell size and was created from a LAS dataset of terrestrial light detection and ranging (lidar) data representing the beach topography. Lidar data were collected June 24, 2021, using a boat mounted Velodyne VLP-16 unit. Methodology similar to Wagner, D.M., Lund, J.W., and Sanks, K.M., 2020 was used.

Digital Elevation Model of Scott County, Minnesota.

The elevation contours in this dataset have a 2-foot (ft) interval and were derived from a digital elevation model (DEM) of beach topography and nearshore bathymetry of Lake Superior at Minnesota Point, Duluth, Minnesota. The DEM has a 1 meter (m; 3.28084 ft) cell size and was created from Lidar data representing beach topography and sonar data representing bathymetry extending approximately 700-800 m offshore. The data cover an approximately 1.75 square kilometer survey area. Lidar data were collected August 22, 2022 using a boat mounted Velodyne VLP-16 unit and methodology similar to that described by Huizinga and Wagner (2019). Multibeam sonar data were collected August 22-23, 2022 using a Norbit integrated wide band multibeam system compact (iWBMSc) sonar unit and methodology similar to that described by Richards and Huizinga (2018). Single-beam sonar data were collected August 23, 2022 using a Ceescope echosounder and methodology similar to that described by Wilson and Richards (2006).This project followed similar methods to that of Wagner, Lund, and Sanks (2020), who completed a similar survey in 2019.

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These data are digital elevation models (DEMs) of the beach topography and near-shore bathymetry of Lake Superior at Minnesota Point near the Duluth Entry, Duluth, Minnesota. A LAS dataset was used to create DEMs of 10 meter (m; 32.8084 feet) and 1 m (3.28084 feet) resolution, covering the approximately 1.75 square kilometer surveyed area. Average point spacing of the LAS files in the dataset are as follows: lidar, 0.094 meters (m); multibeam sonar, 0.501 m; single-beam sonar, 1.876 m. Lidar data were collected August 22, 2022 using a boat mounted Velodyne VLP-16 unit and methodology similar to that described by Huizinga and Wagner (2019). Multibeam sonar data were collected August 22-23, 2022 using a Norbit integrated wide band multibeam system compact (iWBMSc) sonar unit and methodology similar to that described by Richards and Huizinga (2018). Single-beam sonar data were collected August 23, 2022 using a Ceescope echosounder and methodology similar to that described by Wilson and Richards (2006). This project followed similar methods to that of Wagner, Lund, and Sanks (2020), who completed a similar survey in 2019.

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 Itasca and St. Louis counties in the northern Minnesota Mesabi Iron Range. 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. Mining (vector) features were obtained from the Minnesota Department of Natural Resources and St. Louis Government Services Center. These features were used to spatially locate the study areas within Itasca and St. Louis counties. Previously developed differencing methods (Gesch, 2006) were used to develop difference raster datasets of NED/SRTM (1947-2000 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.High-resolution (1-3 m) DEMs, generated from lidar point cloud data, were acquired for Itasca and St. Louis counties in Minnesota from the Minnesota Department of Natural Resources. 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 occurring for Itasca County between April 5, 2012 to April 28, 2012 and St. Louis County between May 3, 2011 to June 1, 2011. A recent difference raster dataset time span (2007-2012 date range) was analyzed by differencing the Minnesota 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 lidar/IFSAR difference dataset. Itasca County included metadata describing vertical root mean square error (RMSE) values for different land cover types. This allowed additional refinement of the spatially explicit threshold values. A single RMSE value was used for St. Louis County because RMSE values for land cover types were not provided.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.

10 foot topography map of Scott County, Minnesota.

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This dataset is a digital elevation model (DEM) of the beach topography and near-shore bathymetry of Lake Superior at the Duluth Entry, Duluth, Minnesota. The DEM has a 5-meter (m; 16.404 feet) cell size and was created from a LAS dataset of terrestrial light detection and ranging (lidar) data representing the beach topography, and multibeam sonar data representing the bathymetry. The survey area extends approximately 0.85 kilometers (0.5 miles) offshore, for an approximately 1.87 square kilometer surveyed area. Lidar data were collected September 23, 2020 using a boat mounted Velodyne unit. Multibeam sonar data were collected September 22-23, 2020 using a Norbit integrated wide band multibeam system compact (iWBMSc) sonar unit. Methodology similar to Wagner, D.M., Lund, J.W., and Sanks, K.M., 2020 was used.

The Minnesota Department of Natural Resources contracted with Sanborn Map Co., Inc. to provide lidar (Light Detection and Ranging) mapping services for the South Dakota portion of the Minnesota River Basin. Utilizing multi-return systems, lidar data in the form of 3-dimensional positions of a dense set of mass points was collected for approximately 1,946 square miles.

The vendor delivered the data to the DNR in several formats:

1) One-meter digital elevation model
2) Edge-of-water breaklines
3) Classified LAS formatted point cloud data

DNR staff created three additional products: two-foot contours, building outlines and hillshades.

The data are in UTM Zone 14 coordinates.

This metadata record was created at the Minnesota Geospatial Information Office by combining information supplied by Sanborn and the DNR.

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A feature service is also available here: https://gis.ducks.org/datasets/duinc::minnesota-restorable-wetlandsHISTORY: In October 2000, a Restorable Wetlands Working Group formed to begin mapping all of the restorable wetlands in the glaciated tallgrass Prairie Pothole Region of Minnesota and Iowa. Today, fewer than 10% of the original wetlands - once of unparalleled importance to continental waterbird populations - are left in existence. Fortunately, wetlands once drained for agriculture may be restored to many of their historic functions. Restoration of multiple wetland functions is of utmost effectiveness when focused at priority restoration landscapes, therefore data on the historic distribution of wetlands is an integral part of developing strategic regional habitat restoration plans.Opportunistic wetland restorations often fail to attain out expectations for wetland function. Nevertheless, between $70 - $100,000,000 are spent annually in Minnesota for wetland restoration. A strategic plan for wetland restoration can make these expenditures more effective; however, a strategic wetland restoration plan requires a priori information on the distribution and extent of restorable wetlands. The collective goal of the Restorable Wetlands Working Group is the eventual development of a set of multi-agency decision support tools that collectively comprise a comprehensive environmental management plan for wetlands - all based on the same base data layers and developed in joint consultation. An effort is underway to delineate restorable wetlands in all intensively farmed areas of MN and IA.A pilot project determined the best technique to map drained wetlands in agricultural landscapes was photointerpretation. This pilot project evaluated the accuracy of three potential delineation techniques: digital hydric soils databases, digital elevation models, and manual stereoscopic photointerpretation on high-altitude color infrared aerial photographs. The project covered nearly 4,000 square miles of different land forms and wetland characteristics. After mapping was completed, some 1,500 drained wetlands were observed in the field to assess the accuracy of each technique. Only photointerpretation provided reliable results.One area that fell into the pilot study was the Okabena quadrangle in east-central Jackson County in Minnesota. Okabena vividly illustrates the potential of humans to alter the natural landscape. While Okabena historically encompassed more than 8,940 acres of depressional wetland - 27% of the total area of Okabena - after nearly 100 years of agricultural drainage only 1,280 acres of those original wetlands remain, representing an 86% reduction. When empirical models used to estimate duck pairs on individual wetlands are applied to the change from historic to current wetland habitat within Okabena, they estimate a 92% reduction in the habitat potential for common dabbling duck species.The Okabena quadrangle's wetland density once exceeded that of most of the remaining U.S. Prairie Pothole Region. Without strong incentives for wetland conservation and effective methods to delineate high-priority landscapes for restoration, the Okabena quadrangle foretells one possible future for much of the mixed-grass Prairie Pothole Region further west.The Final Status map was completed in 2012.Contact Information:Rex JohnsonUnited States Fish and Wildlife Service21932 State Highway 210Fergus Falls, MN 56537(218) 736-0606rex_johnson@fws.govPhotointerpretationNational Aerial Photography Program (NAPP) (1:40,000 scale) color infrared (CIR) photographs acquired in April and May, 1991 and 1992, were viewed in stereo pairs at 5X magnification using a Cartographic Engineering stereoscope. A Mylar overlay was mounted on one photo of each stereo pair and a rectangular work area was delineated on the overlay comprising one-quarter of a USGS 7.5 min topographic quadrangle. A minimum of 4 fiduciary marks were placed on the overlay to enable geographic rectification of digital data covering the work area. One fiduciary mark was placed at the corner of the US Geological Survey (USGS) 7.5 min quadrangle and others at conspicuous road intersections near the other 3 corners of the work area. Drained depressional wetlands were delineated on the Mylar overlay within the work area using a 6X0 (.13 mm diameter) rapidograph pen and indelible ink. Collateral data was consulted during the delineation process. These data consisted of published county soil surveys and descriptions of hydric soils, USDA Farm Service Agency compliance slides (aerial 35 mm slides) acquired in 1993 (immediately after a period of intense precipitation), USGS 7.5 min topographic maps, and National Wetlands Inventory (NWI) maps. Black and white NAPP photographs (1:40,000 scale) acquired primarily in August and September, 1996, were reviewed and rejected as collateral data because they were acquired under dry conditions.Other specific photointerpretation protocols were:1. All drained depressional wetlands, regardless of size, were delineated.2. NWI-delineated wetlands with a Ad@ (partially drained) modifier in the classification code were not delineated unless the original delineation failed to encompass the complete historic wetland area.3. NWI-delineated wetlands that did not contain a Ad@ modifier in the classification code were delineated if the original delineation did not include the entire historic wetland area.4. Wetlands identified on NWI maps which did not exhibit wetland characteristics (i.e. hydrology, hydrophytes, etc) on new (1992) CIR photography were delineated even if no evidence of drainage was apparent.5. Wetlands not delineated on NWI maps, and in cropland, were delineated.6. Wetlands not delineated on NWI maps, and in grassland, were not delineated unless evidence of drainage was observed on the aerial photo.7. Wetlands not delineated on NWI maps, and in trees, were not delineated.Tolerances:Scanned line data were converted to a polygon using a 6 m fuzzy tolerance. Open polygons were manually closed and cleaned with a 1.2 m fuzzy tolerance which was used for all subsequent data processing.Datafile Description and Attribute Definitions[County_Name]_nwx - National Wetlands Inventory delineations (see https://www.fws.gov/program/national-wetlands-inventory/wetlands-mapper for NWI delineation standards). Note: Wetland classifications in these data often differ slightly from the original NWI classification. NWI wetland classifications were simplified for these data by removing mixed classes and multiple special modifiers, and by standardizing letter case. In each case of mixed classes and multiple special modifiers, the first class or special modifier was retained.AttributesRestorable - 0 = Islands and the Universal Polygon100 = Restorable depressional wetland delineated using protocols described aboveCounty Name – The name of the county in which the center of the polygon is located.State Name – The name of the state.FIPS – The FIPS code.

NCED is currently involved in researching the effectiveness of anaglyph maps in the classroom and are working with educators and scientists to interpret various Earth-surface processes. Based on the findings of the research, various activities and interpretive information will be developed and available for educators to use in their classrooms. Keep checking back with this website because activities and maps are always being updated. We believe that anaglyph maps are an important tool in helping students see the world and are working to further develop materials and activities to support educators in their use of the maps.

This website has various 3-D maps and supporting materials that are available for download. Maps can be printed, viewed on computer monitors, or projected on to screens for larger audiences. Keep an eye on our website for more maps, activities and new information. Let us know how you use anaglyph maps in your classroom. Email any ideas or activities you have to ncedmaps@umn.edu

Anaglyph paper maps are a cost effective offshoot of the GeoWall Project. Geowall is a high end visualization tool developed for use in the University of Minnesota's Geology and Geophysics Department. Because of its effectiveness it has been expanded to 300 institutions across the United States. GeoWall projects 3-D images and allows students to see 3-D representations but is limited because of the technology. Paper maps are a cost effective solution that allows anaglyph technology to be used in classroom and field-based applications.

Maps are best when viewed with RED/CYAN anaglyph glasses!

A note on downloading: "viewable" maps are .jpg files; "high-quality downloads" are .tif files. While it is possible to view the latter in a web-browser in most cases, the download may be slow. As an alternative, try right-clicking on the link to the high-quality download and choosing "save" from the pop-up menu that results. Save the file to your own machine, then try opening the saved copy. This may be faster than clicking directly on the link to open it in the browser.

World Map: 3-D map that highlights oceanic bathymetry and plate boundaries.

Continental United States: 3-D grayscale map of the Lower 48.

Western United States: 3-D grayscale map of the Western United States with state boundaries.

Regional Map: 3-D greyscale map stretching from Hudson Bay to the Central Great Plains. This map includes the Western Great Lakes and the Canadian Shield.

Minnesota Map: 3-D greyscale map of Minnesota with county and state boundaries.

Twin Cities: 3-D map extending beyond Minneapolis and St. Paul.

Twin Cities Confluence Map: 3-D map highlighting the confluence of the Mississippi and Minnesota Rivers. This map includes most of Minneapolis and St. Paul.

Minneapolis, MN: 3-D topographical map of South Minneapolis.

Bassets Creek, Minneapolis: 3-D topographical map of the Bassets Creek watershed.

North Minneapolis: 3-D topographical map highlighting North Minneapolis and the Mississippi River.

St. Paul, MN: 3-D topographical map of St. Paul.

Western Suburbs, Twin Cities: 3-D topographical map of St. Louis Park, Hopkins and Minnetonka area.

Minnesota River Valley Suburbs, Twin Cities: 3-D topographical map of Bloomington, Eden Prairie and Edina area.

Southern Suburbs, Twin Cities: 3-D topographical map of Burnsville, Lakeville and Prior Lake area.

Southeast Suburbs, Twin Cities: 3-D topographical map of South St. Paul, Mendota Heights, Apple Valley and Eagan area.

Northeast Suburbs, Twin Cities: 3-D topographical map of White Bear Lake, Maplewood and Roseville area.

Northwest Suburbs, Mississippi River, Twin Cities: 3-D topographical map of North Minneapolis, Brooklyn Center and Maple Grove area.

Blaine, MN: 3-D map of Blaine and the Mississippi River.

White Bear Lake, MN: 3-D topographical map of White Bear Lake and the surrounding area.

Maple Grove, MN: 3-D topographical mmap of the NW suburbs of the Twin Cities.

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.

Map Catalog is powered by the Memento Server software and provides a continuous view across multiple geospatial PDFs. The PDF maps currently available are 1K USNG (topo and aerial) maps from four metro counties(Anoka, Carver, Dakota and Ramsey), 1K USNG Topo of cities and state parks in Minnesota, 10K USNG Aerial maps for Minnesota, US Topo for the metro and Dakota County Park maps, City Street maps and Half Section maps. Map update frequency varies.