This map of Minnesota cities, townships, and counties was published by MnGeo in January 2019. The primary data set for the map is the "Cities, Townships, and Unorganized Territories" (MnCTU) data maintained by the Minnesota Department of Transportation. Other reference data on the map include County Seats and Other Cities, County Boundaries, Interstate, US Trunk, and State Trunk Highways, Major Rivers, Lakes, County and State Boundaries. The download is a PDF file with embedded layers that can be printed at E-scale (36" x 48").

This feature class is basically a representation of all cities/towns and townships within Douglas County.This is the most up to date boundary for Douglas County with annexations for Alexandria City. Current boundary used in apps.

This medium-scale (nominally 1:24,000) dataset represents the boundaries of cities, townships, and unorganized territories (CTUs) in Minnesota. The Minnesota Geospatial Information Office created the initial CTU dataset by updating a municipal boundary file maintained by the Minnesota Department of Transportation (MnDOT). Update information was gathered primarily from boundary adjustment records maintained by the Office of Administrative Hearings, Municipal Boundary Adjustment Unit. MnDOT has maintained the file since 2014.

Note: Cities and Townships represented in this dataset are political (civil) townships as recognized by the State of MN, not congressional or public land survey townships. Unorganized territory subdivisions are those defined by the U.S. Bureau of the Census, which often differ from those defined by a county.

Check other metadata records in this package for more information on CTUInformation.


Link to ESRI Feature Service:

City, Township, and Unorganized Territory in Minnesota: City, Township, and Unorganized Territory

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.

A high-resolution (1-meter) land cover classification raster dataset was completed for three different geographic areas in Minnesota: Duluth, Rochester, and the seven-county Twin Cities Metropolitan area. This classification was created using high-resolution multispectral National Agriculture Imagery Program (NAIP) leaf-on imagery (2015), spring leaf-off imagery (2011- 2014), Multispectral derived indices, LiDAR data, LiDAR derived products, and other thematic ancillary data including the updated National Wetlands Inventory, LiDAR building footprints, airport, OpenStreetMap roads and railroads centerlines. These data sets were integrated using an Object-Based Image Analysis (OBIA) approach to classify 12 land cover classes: Deciduous Tree Canopy, Coniferous Tree Canopy, Buildings, Bare Soil, other Paved surface, Extraction, Row Crop, Grass/Shrub, Lakes, Rivers, Emergent Wetland, Forest and Shrub Wetland.

We mapped the 12 classes by using an OBIA approach through the creation of customized rule sets for each area. We used the Cognition Network Language (CNL) within the software eCognition Developer to develop the customized rule sets. The eCognition Server was used to execute a batch and parallel processing which greatly reduced the amount of time to produce the classification. The classification results were evaluated for each area using independent stratified randomly generated points. Accuracy assessment estimators included overall accuracies, producers accuracy, users accuracy, and kappa coefficient. The combination of spectral data and LiDAR through an OBIA method helped to improve the overall accuracy results providing more aesthetically pleasing maps of land cover classes with highly accurate results.

Minnesota GreenStep Cities is a voluntary challenge, assistance and recognition program to help cities achieve their sustainability and quality-of-life goals. This free continuous improvement program, managed by a public-private partnership, is based upon 29 best practices. Each best practice can be implemented by completing one or more actions at a 1, 2 or 3-star level, from a list of four to eight actions. ReST service documentation for developers

Exterior boundary, Annexation boundary, and County boundary coverages are examined to remove all overshoots, unwanted intersections; insure polygons are closed; and to see that there are no missing or duplicate polygon labels. Each symbolic layer is individually examined for completeness. There is no line duplication in exterior or annexation coverages. MCD's with detached or non-contiguous units (polygons) have the same polygon link/label code in each of their units. Completeness in the checking process is examined through the examination and comparison of all detail collected by County Staff. Sources used included: City Clerks, County Auditor's Office, Washington County Historical Courthouse, MN State Historical Society, Secretary of State, Minnesota Municipal Board, and MNDOT. https://www.co.washington.mn.us/1609/Municipal-Boundaries

High resolution (10 meter) land surface temperature (LST) from September 1, 2022 is mapped for the seven-county metropolitan region of the Twin Cities. The goal of the map is to show the heat differences across the region and is not intended to show the maximum temperature that any specific area can reach. The raster dataset was computed at 30 meters using satellite imagery from Landsat 9 and downscaled to 10 meters using Copernicus Sentinel-2. These datasets were integrated using techniques modified from Ermida et al. 2020 and Onačillová et al. 2022). Open water was removed using ancillary data from OpenStreetMap and 2020 Generalized Land Use for the Twin Cities (Metropolitan Council).

First, Landsat 9 imagery taken at 11:59 am CDT on September 01, 2022 was processed into 30-meter resolution LST (based on Ermida et al. 2020). At this time, the air temperature was 88° F at the Minneapolis-St. Paul International Airport (NOAA). A model predicting LST based on spectral indices of Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), and Normalized Difference Built-up Index (NDBI) was created and applied to 10-meter Sentenel-2 imagery. Sentinel-2 imagery was also taken on September 1, 2022, and this resulted in a 10-meter downscaled LST image (based on Onačillová et al. 2022). To account for anomalies in NDVI on the primary image date of September 1 (e.g., recently harvested agricultural fields), maximum NDVI occurring between July 1, 2022 and September 1, 2022 was used for both Landsat and Sentinel image processing. Water bodies were removed for all processing steps (OpenStreetMap 2023, Metropolitan Council 2021).

This dataset is an update to the 2016 LST data for the Twin Cities Region (Metropolitan Council).

The code to create and processes this dataset is available at: https://github.com/Metropolitan-Council/extreme.heat

Sources:
Ermida, S.L., Soares, P., Mantas, V., Göttsche, F.-M., Trigo, I.F., 2020. Google Earth Engine open-source code for Land Surface Temperature estimation from the Landsat series. Remote Sensing, 12 (9), 1471; https://doi.org/10.3390/rs12091471.

Metropolitan Council. 2021. Generalized Land Use 2020. Minnesota Geospatial Commons. https://gisdata.mn.gov/dataset/us-mn-state-metc-plan-generl-lnduse2020

Metropolitan Council. 2017. Land Surface Temperature for Climate Vulnerability Analysis. Minnesota Geospatial Commons. https://gisdata.mn.gov/dataset/us-mn-state-metc-env-cva-lst2016

NOAA, National Oceanic and Atmospheric Administration, National Centers for Environmental Information, station USW00014922. September 1, 2022.

Onačillová, K., Gallay, M., Paluba, D., Péliová, A., Tokarčík, O., Laubertová, D. 2022. Combining Landsat 8 and Sentinel 2 data in Google Earth Engine to derive higher resolution land surface temperature maps in urban environment. Remote Sensing, 14 (16), 4076. https://doi.org/10.3390/rs14164076.

OpenStreetMap contributors. 2023. Retrieved from https://planet.openstreetmap.org on April 12, 2023.

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 shapefiles of lakes, streams, wetlands, river bottoms, and the Mississippi River represent the hydrological landscape of Minneapolis and St. Paul as recorded in the original public land survey conducted between 1848 and 1858. The hydrologic features were digitized from scanned, georeferenced 1:24000 maps during the 2017 Faculty Research Sprint held at the University of Minnesota.

Fugro Horizons Inc. acquired highly accurate Light Detection and Ranging (lidar) elevation data for the Twin Cities metropolitan region in east-central Minnesota in Spring and Fall 2011, with some reflights in Spring 2012. The data cover Anoka, Benton, Carver, Dakota, Goodhue, Hennepin, Isanti, Kanabec, Meeker, Mille Lacs, Morrison, Ramsey, Scott, Sherburne and Washington counties.

Most of the data was collected at 1.5 points/square meter. Smaller areas were collected with 2 points/square meter and with 8 points/square meter:
1. 1.5 points/square meter covers Morrison, Mille Lacs, Benton, Isanti, Sherburne, Anoka, Meeker, Hennepin, Washington, Carver, Scott, and Goodhue counties.
2. 2 points/square meter covers the Dakota Block (southern 2/3 of Dakota County)
3. 8 points/square meter covers portions of Minneapolis/St. Paul and the City of Maple Grove
See map of block boundaries: https://www.mngeo.state.mn.us/chouse/elevation/metro_data_delivery_dates.pdf

Data are in the UTM Zone 15 coordinate system, NAD83 (HARN), NAVD88 Geoid09, meters. The tiling scheme is 16th USGS 1:24,000 quadrangle tiles.

The vendor delivered the data to the Minnesota Department of Natural Resources (DNR) in several formats:

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

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

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

Circulator routes and local transportation options within Washington County, MN.Twin Cities Metro Transit route data provided by Metropolitan Council.This map is used by the Transportation Finder application

If there are any issues with the data in this map, service, or shp file please contact the Minneapolis GIS office.

A shapefile was generated from ArcINFO coverages, which were in turn created by digitizing a 1958 paper map of land use in the Twin Cities Metropolitan Area. The map was originally published by the Twin Cities Metropolitan Planning Commission.

This map provides a spatial illustration of different means by which racial segregation was historically reinforced across the cities of Minneapolis and Saint Paul. The map focuses largely on data from the 1940s, and includes the following data layers:Population by Race - Data based on 1940 US Census that shows the percentage of the non-white population at the census tract level. This data was downloaded from NHGIS, with a spatial join performed to combine the census table and historic tracts (Citation: Steven Manson, Jonathan Schroeder, David Van Riper, Katherine Knowles, Tracy Kugler, Finn Roberts, and Steven Ruggles, IPUMS National Historical Geographic Information System: Version 18.0. Minneapolis, MN: IPUMS. 2023).HOLC Map Zones by Number of Covenants - This layer displays a summary of the number of racially exclusive covenants within the area of zones designated by grade on HOLC redlining maps. The polygons of each grade zone were digitized by the Mapping Inequality Project (University of Richmond Digital Scholarship Lab) and are symbolized by the grade colors on the original maps. The data on racially exclusive covenants in Twin Cities neighborhoods was downloaded from the Mapping Prejudice Project (University of Minnesota) and is symbolized by the size of each feature.Greenbook Locations - This layer displays locations included on Greenbook travel guides from the 1940s, which indicate safe businesses for African American travelers to American Cities. This data comes from a service layer created by Shana Crosson (University of Minnesota).This spatial extent of this map is limited to the cities of Minneapolis and Saint Paul. It was created as part of an in-class exercise in February of 2024.

A shapefile was generated from ArcINFO coverages, which were in turn created by digitizing a 1978 paper map of land use in the Twin Cities Metropolitan Area. The map was originally published by the Twin Cities Metropolitan Planning Commission.

Minor Civil Divisions map showing cities and townships within Scott County.

City and Township boundaries are used to display political boundaries that are used for taxation purposes, voting districts, and general purpose maps. The boundaries are based on a combination of the original Public Land Survey System (PLSS) and municipal city boundaries that have been annexed.Layer Location Land Records and Cadastral

This layer contains boundaries of the Metropolitan Urban Service Area (MUSA) in the Twin Cities metropolitan area of Minnesota for each year from 1995 through 1998. Plans are to also add Local Urban Service Area (LUSA) boundaries to this dataset.

A MUSA boundary line is the outer edge of the urban area. It is a line agreed to jointly by the Council and local governments through local comprehensive plan reviews. It delimits the outer reaches of regional services for the specified time period.

A LUSA boundary line is the outer edge of the urban service are in rural growth centers. Rural growth centers are incorporated areas that currently provide central sewer service and that have planned long-term expansions of their urban service area. These small cities are expected to plan for a balance of housing and jobs to promote self-sufficiency. This service area boundary, like the MUSA, is agreed to jointly by the Council and local governments through local comprehensive plan reviews. It delimits the outer reaches of regional services for the specified time period.

Many of the lines that define the MUSA boundary are municipal boundaries. In this layer, these lines have been derived from the County and Minor Civil Divisions layer compiled by the Metropolitan Council. Other lines in this layer have been derived from municipal comprehensive plan maps at a variety of scales and accuracy levels.

NOTES:
- The lines in this layer are not expected to be as positionally accurate as parcel datasets available from most counties in the Twin Cities area.
- Significant errors have been noticed in the original 1995 dataset. These include missing polygons and lines that differ significantly from the parcel boundaries that actually define the MUSA. These errors will be fixed as they are encountered. See Horizontal Positional Accuracy for more information.
- Additionally, areas included in the MUSA in any particular year can, at times, be difficult to determine from maps submitted to the Council prior to 1998, and do not necessarily match maps from previous years.
- Some communities have 'undesignated' or 'floating' MUSAs. That is, they may have a large or undefined area within which a specific amount of land may be added to the MUSA within a given period of time. Thus, the acreage of additional MUSA has been approved by the council, but the location of that acreage will be determined in the future. These 'undesignated' or 'floating' MUSAs are not represented in this layer until specific locations are identified.

description: Raster-based land cover data sets are derived from 30-meter resolution Thematic Mapper satellite imagery. These data sets were created at the Remote Sensing and Geospatial Analysis Laboratory at the University of Minnesota. The Land Management Information Center converted these data files into EPPL7 format to be used with EPPL7 mapping products. There are currently three themes in this data set: 1. Landsat Level-1 Land Cover Classification of the Twin Cities Metropolitan Area, 2000: This coverage consists of 6 classes including: urban/developed, agriculture (planted or cultivated), forest, non-forested vegetation, water, not classified. 2. Landsat Level-2 Land Cover Classification of the Twin Cities Metropolitan Area, 2000: This coverage consists of 12 classes including: 0-4% impervious, 5-10% impervious, 11-25% impervious, 26-50% impervious 51-75% impervious, 76-100% impervious, Cropland, Planted trees & grasses, Coniferous, Deciduous, Upland shrubland & herbaceous, Lowland shrubland & herbaceous, Water. Definitions for these classes are based on the Minnesota Land Cover Classification System (MLCCS). 3. Impervious Surface Classification of the Twin Cities Metropolitan Area, 2000: Landsat TM data have been used to map the percentage of impervious surface area of the seven-county TCMA for the year 2000. Impervious surfaces are defined as areas impenetrable by water - including roads, rooftops, sidewalks and parking lots. The coverage provides information on the percentage of impervious surface on a 30-meter pixel basis for all urban areas. The impervious surface layer was derived from a single date of Landsat-5 TM data. Following the classification of land cover types, a regression model relating percent impervious surface area to Landsat TM greenness values was used to estimate the percent impervious surface area for pixels classified as urban or developed. Classification of the Landsat TM data provides a means to map and quantify the degree of impervious surface area, an indicator of environmental quality, over large geographic areas and over time.; abstract: Raster-based land cover data sets are derived from 30-meter resolution Thematic Mapper satellite imagery. These data sets were created at the Remote Sensing and Geospatial Analysis Laboratory at the University of Minnesota. The Land Management Information Center converted these data files into EPPL7 format to be used with EPPL7 mapping products. There are currently three themes in this data set: 1. Landsat Level-1 Land Cover Classification of the Twin Cities Metropolitan Area, 2000: This coverage consists of 6 classes including: urban/developed, agriculture (planted or cultivated), forest, non-forested vegetation, water, not classified. 2. Landsat Level-2 Land Cover Classification of the Twin Cities Metropolitan Area, 2000: This coverage consists of 12 classes including: 0-4% impervious, 5-10% impervious, 11-25% impervious, 26-50% impervious 51-75% impervious, 76-100% impervious, Cropland, Planted trees & grasses, Coniferous, Deciduous, Upland shrubland & herbaceous, Lowland shrubland & herbaceous, Water. Definitions for these classes are based on the Minnesota Land Cover Classification System (MLCCS). 3. Impervious Surface Classification of the Twin Cities Metropolitan Area, 2000: Landsat TM data have been used to map the percentage of impervious surface area of the seven-county TCMA for the year 2000. Impervious surfaces are defined as areas impenetrable by water - including roads, rooftops, sidewalks and parking lots. The coverage provides information on the percentage of impervious surface on a 30-meter pixel basis for all urban areas. The impervious surface layer was derived from a single date of Landsat-5 TM data. Following the classification of land cover types, a regression model relating percent impervious surface area to Landsat TM greenness values was used to estimate the percent impervious surface area for pixels classified as urban or developed. Classification of the Landsat TM data provides a means to map and quantify the degree of impervious surface area, an indicator of environmental quality, over large geographic areas and over time.