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 layer is a component of Natural resources interactive map.

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.

The 2022 cartographic boundary KMLs are simplified representations of selected geographic areas from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). These boundary files are specifically designed for small-scale thematic mapping. When possible, generalization is performed with the intent to maintain the hierarchical relationships among geographies and to maintain the alignment of geographies within a file set for a given year. Geographic areas may not align with the same areas from another year. Some geographies are available as nation-based files while others are available only as state-based files. The cartographic boundary files include both incorporated places (legal entities) and census designated places or CDPs (statistical entities). An incorporated place is established to provide governmental functions for a concentration of people as opposed to a minor civil division (MCD), which generally is created to provide services or administer an area without regard, necessarily, to population. Places always nest within a state, but may extend across county and county subdivision boundaries. An incorporated place usually is a city, town, village, or borough, but can have other legal descriptions. CDPs are delineated for the decennial census as the statistical counterparts of incorporated places. CDPs are delineated to provide data for settled concentrations of population that are identifiable by name, but are not legally incorporated under the laws of the state in which they are located. The boundaries for CDPs often are defined in partnership with state, local, and/or tribal officials and usually coincide with visible features or the boundary of an adjacent incorporated place or another legal entity. CDP boundaries often change from one decennial census to the next with changes in the settlement pattern and development; a CDP with the same name as in an earlier census does not necessarily have the same boundary. The only population/housing size requirement for CDPs is that they must contain some housing and population. The generalized boundaries of most incorporated places in this file are based on those as of January 1, 2022, as reported through the Census Bureau's Boundary and Annexation Survey (BAS). The generalized boundaries of all CDPs are based on those delineated as part of the Census Bureau's Participant Statistical Areas Program (PSAP) for the 2020 Census.

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.

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.

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

A downloadable, printable 8.5 x 11 inch PDF map of the City of Victoria and surrounding area.

A dataset listing Minnesota counties by population for 2024.

The 2015 cartographic boundary shapefiles are simplified representations of selected geographic areas from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). These boundary files are specifically designed for small-scale thematic mapping. When possible, generalization is performed with the intent to maintain the hierarchical relationships among geographies and to maintain the alignment of geographies within a file set for a given year. Geographic areas may not align with the same areas from another year. Some geographies are available as nation-based files while others are available only as state-based files. The records in this file allow users to map the parts of Urban Areas that overlap a particular county. After each decennial census, the Census Bureau delineates urban areas that represent densely developed territory, encompassing residential, commercial, and other nonresidential urban land uses. In general, this territory consists of areas of high population density and urban land use resulting in a representation of the "urban footprint." There are two types of urban areas: urbanized areas (UAs) that contain 50,000 or more people and urban clusters (UCs) that contain at least 2,500 people, but fewer than 50,000 people (except in the U.S. Virgin Islands and Guam which each contain urban clusters with populations greater than 50,000). Each urban area is identified by a 5-character numeric census code that may contain leading zeroes. The primary legal divisions of most states are termed counties. In Louisiana, these divisions are known as parishes. In Alaska, which has no counties, the equivalent entities are the organized boroughs, city and boroughs, municipalities, and for the unorganized area, census areas. The latter are delineated cooperatively for statistical purposes by the State of Alaska and the Census Bureau. In four states (Maryland, Missouri, Nevada, and Virginia), there are one or more incorporated places that are independent of any county organization and thus constitute primary divisions of their states. These incorporated places are known as independent cities and are treated as equivalent entities for purposes of data presentation. The District of Columbia and Guam have no primary divisions, and each area is considered an equivalent entity for purposes of data presentation. The Census Bureau treats the following entities as equivalents of counties for purposes of data presentation: Municipios in Puerto Rico, Districts and Islands in American Samoa, Municipalities in the Commonwealth of the Northern Mariana Islands, and Islands in the U.S. Virgin Islands. The entire area of the United States, Puerto Rico, and the Island Areas is covered by counties or equivalent entities. The boundaries for counties and equivalent entities are as of January 1, 2010.

The regional bikeways dataset was created by the Minnesota Dept of Transportation (MNDOT) in 2003. It has been maintained and updated by the Land Management Information Center (LMIC) through contract with the Metropolitan Council.

Dataset includes bicycle routes within nine Twin Cities metropolitan counties: Anoka, Carver, Chisago, Dakota, Hennepin, Ramsey, Scott, Washington, and Wright. The bikeways are from a number of sources including the Metro Bicycle Network map book (2001), supplemented by information from maps published by city, state, county and regional government agencies, and city and county planning maps. The map shows on-road and off-road bikeways, proposed and existing bikeways, and includes bike lanes, bike-able road shoulders, and trails.

The majority of the bikeways follow road centerlines of the MNDOT BaseMap 2002-Roads. A description of the bikeways attributes and sources of data are included in Section 5 of this document - Entity and Attribute Overview.

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.

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

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

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

The goal of the Composite Image Service is to provide a single layer image service with the 'best' air photo or satellite image available for a certain extent. The images are provided as a WMS (web map service). The primary focus is the Twin Cities Metropolitan Area and the State of Minnesota. The secondary interest is the areas bordering Minnesota, especially Wisconsin counties close to the metro area. Imagery is evaluated based on criteria of color, currency, resolution, coverage, season, leaf cover and image quality in order to determine which imagery to include at which scale. See the Lineage field for a list of imagery layers that are visible at different scales. More information about this map service and the imagery resources displayed at various scales is available on the MnGeo Composite Image Service webpage: http://www.mngeo.state.mn.us/chouse/wms/composite_image.html

A downloadable, printable 8.5 x 11 inch PDF map of the City of Chanhassen and surrounding area.

This is the authoritative public subset of the compiled Minnesota statewide parcel dataset. By authoritative, we mean this is the official source of statewide parcel data compiled from the counties that have opted-in to be included. Counties are the authoritative source and owner of parcel data. Quarterly, MnGeo compiles and standardizes the county data using the Minnesota Geospatial Advisory Council's parcel data standard. In the compilation process, some data content is standardized or otherwise modified (capitalization and address parsing are the most common changes). The full opt-in compiled parcel metadata record can be found on the Minnesota Geospatial Commons.To obtain the most current and authoritative data in its original form, users are referred back to the respective county. Links to each county's downloadable and/or web-viewable data, where known, are available in the accompanying spatial metadata dataset.Known limitations:Data provided by counties are often limited to a subset of fields and may not be the same fields across all counties. The fields provided by a given county may change by quarter.The USECLASS and XUSECLASS fields, while often consistent within a county, are not standardized between counties.The OWN_ADDR_# and TAX_ADDR_# fields are often populated in ways not consistent with the standard. In particular, an address number/street address may not be in Line 1, and city/state/zip cannot be relied on to be in Line 3. Even within a single county, the city/state/zip line may not be in a consistent field.Parcels with addresses on fractional streets (5-1/2th Ave) cause issues for our address parser when parsing is needed for aggregation and may be missing some or all of the address data. Certain other oddly named streets can also cause this behavior.A maximum record count has been set on the mapping service. This limits the number of features that can be returned in a single request. It is set to balance usability and response time.

We collected open and publicly available data resources from the web from administrative, county- or state-level institutions in the United States and integrated and harmonized cadastral parcel data, tax assessment data, and building footprint data for 33 counties, where building footprint data and building construction year information was available. The result of this effort is a unique dataset which we call the Multi-Temporal Building Footprint Dataset for 33 U.S. Counties (MTBF-33). MTBF-33 contains over 6.2 million building footprints including their construction year, and is available in ESRI Shapefile format (Spatial reference system: SR-ORG:7480), organized per county. We compared the MTBF-33 dataset quantitatively to other building footprint data sources, achieving an overall F-1 score of 0.93. Moreover, we compared the MTBF-33 dataset qualitatively to urban extents from historical maps and find high levels of agreement. The MTBF-33 dataset can be used to support historical building stock assessments, to derive retrospective depictions of built-up areas from 1900 to 2015, at fine spatial and temporal grain and can be used for data validation purposes, or to train statistical learning approaches aiming to extract historical information on human settlements from remote sensing data, historical maps, or similar data sources.

Data sources: Boulder County (Colorado) Open Data Catalog / Florida Geographic Data Library / Hillsborough County, Florida / City of Tampa / Manatee County, Florida / Sarasota County, Florida / City of Evansville, Vanderburgh County, Indiana / Baltimore County Government, Maryland / Bureau of Geographic Information (MassGIS), Commonwealth of Massachusetts, Executive Office of Technology and Security Services / City of Boston / MetroGIS, Minnesota Geospatial Commons, Minnesota Geospatial Information Office, Anoka County, Carver County, Dakota County, Hennepin County, Ramsey County, and Washington County, Minnesota / Monmouth County, New Jersey / City of New York / Mecklenburg County, North Carolina. Data scraping was performed in 2016.

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.