This dataset represents the county boundaries, as recognized by the Minnesota Department of Transportation. There are 87 counties in Minnesota.

Check other metadata records in this package for more information on County Boundaries Information.


Link to ESRI Feature Service:

County Boundaries in Minnesota: County Boundaries

This is the standard Minnesota State County Boundary dataset that is used by MNDNR and many other state agencies. It is maintained by the MNDNR Lands and Minerals Division.

Please read at the accuracy and lineage sections of this metadata to make sure this dataset is appropriate for your application!

This map shows the free and open data status of county public geospatial (GIS) data across Minnesota. The accompanying data set can be used to make similar maps using GIS software.

Counties shown in this dataset as having free and open public geospatial data (with or without a policy) are: Aitkin, Anoka, Becker, Beltrami, Benton, Big Stone, Carlton, Carver, Cass, Chippewa, Chisago, Clay, Clearwater, Cook, Crow Wing, Dakota, Douglas, Grant, Hennepin, Hubbard, Isanti, Itasca, Kittson, Koochiching, Lac qui Parle, Lake, Lyon, Marshall, McLeod, Meeker, Mille Lacs, Morrison, Mower, Norman, Olmsted, Otter Tail, Pipestone, Polk, Pope, Ramsey, Renville, Rice, Scott, Sherburne, Stearns, Steele, Stevens, St. Louis, Traverse, Waseca, Washington, Wilkin, Winona, Wright and Yellow Medicine.

To see if a county's data is distributed via the Minnesota Geospatial Commons, check the Commons organizations page: https://gisdata.mn.gov/organization

To see if a county distributes data via its website, check the link(s) on the Minnesota County GIS Contacts webpage: https://www.mngeo.state.mn.us/county_contacts.html

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").

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.

The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk Information And supporting data used to develop the risk data. The primary risk; classificatons used are the 1-percent-annual-chance flood event, the 0.2-percent- annual-chance flood event, and areas of minimal flood risk. The DFIRM Database is derived from Flood Insurance Studies (FISs), previously published Flood Insurance Rate Maps (FIRMs), flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by the Federal Emergency Management Agency (FEMA). The file is georeferenced to earth's surface using the UTM projection and coordinate system. The specifications for the horizontal control of DFIRM data files are consistent with those required for mapping at a scale of 1:12,000.

FEMA Framework Basemap datasets comprise six of the seven FGDC themes of geospatial data that are used by most GIS applications (Note: the seventh framework theme, orthographic imagery, is packaged in a separate NFIP Metadata Profile): cadastral, geodetic control, governmental unit, transportation, general structures, hydrography (water areas & lines. These data include an encoding of the geographic extent of the features and a minimal number of attributes needed to identify and describe the features. (Source: Circular A16, p. 13) This data set contains 3-band natural color imagery from the National Agricultural Imagery Program (NAIP). NAIP acquires digital ortho imagery during the agricultural growing seasons in the continental U.S. A primary goal of the NAIP program is to enable availability of ortho imagery within one year of acquisition. The source files are 1 meter ground sample distance (GSD) ortho imagery rectified to a horizontal accuracy of within +/- 5 meters of reference digital ortho quarter quads (DOQQ's) from the National Digital Ortho Program (NDOP) or from NAIP. The tiling format of NAIP imagery is based on a 3.75' x 3.75' quarter quadrangle with a 300 meter buffer on all four sides. NAIP imagery is formatted to the UTM coordinate system using NAD83. NAIP imagery may contain as much as 10% cloud cover per tile. This file was generated by compressing NAIP imagery that cover the county extent. MrSID compression was used. Target values for the compression ratio are (15:1). (Note: The Minnesota Geospatial Information Office (MnGeo) has created this metadata record to describe the entire NAIP2009 dataset, using information from Farm Service Agency metadata. Each county file is accompanied by the original FSA metadata for that county.)

This map portrays our current geologic understanding of the temporal and geographic distribution of units within major Precambrian terranes and of the Phanerozoic strata. The state wide data is mapped at a scale of 1:500,000 and the county bedrock datasets (Becker, Brown, Meeker, Isanti, Cass) are mapped at a 1:100,000 scale. A Story Map displaying this data can be found at Minnesota's Bedrock Geology story map.The western part of the mapped Precambrian terrane in the state wide dataset is inferred largely from geophysical maps, anchored locally by drilling. In many places, contacts are drawn between units of the same or similar apparent rock type (and same unit label); these are recognized as geometrically distinct, though geophysically or lithologically similar. Digital files for the state wide bedrock (http://hdl.handle.net/11299/101466) corresponding to this map allow removal of Cretaceous, Paleozoic, and some parts of Mesoproterozoic strata to reveal an interpretation of the underlying Precambrian bedrock.

For additional state wide data see: (http://hdl.handle.net/11299/98043) which contains files associated with Bedrock Topography, Depth to Bedrock, and locations of Outcrop and Geochronologic analyses. Individual county bedrock can be found and downloaded at the University of Minnesota's Digital Conservancy.

This set of GeoTIFF and EPPL7 files represents the Minnesota Department of Transportation's County Highway Map Series in georeferenced image formats. These images of the standard Mn/DOT County Highway Map product can be used in GIS systems and overlayed with other GIS information. The origin of this data is Mn/DOT's Microstation CAD system, where all linework, feature type coding, and symbolization is stored and updated. To produce these data sets, Mn/DOT exported the data from Microstation into postscript files. LMIC then imported the data into GIS systems for georeferencing and further processing. The GeoTIFF data are distributed in both County Highway Map map sheet and full county extents; EPPL7 data sets are distributed only as full county files. Map collars have been removed. This data set represents the Mn/DOT County Highway Map as of January 1, 2002.

This is the standard Minnesota State Boundary dataset that is used by MNDNR and many other state agencies. It is derived from the related dataset "County Boundaries, Minnesota" ( http://gisdata.mn.gov/dataset/bdry-counties-in-minnesota ) and is maintained by MNDNR's Lands and Minerals Divsion.

This dataset is a compilation of county parcel data from Minnesota counties that have opted-in for their parcel data to be included in this dataset.

It includes the following 55 counties that have opted-in as of the publication date of this dataset: Aitkin, Anoka, Becker, Benton, Big Stone, Carlton, Carver, Cass, Chippewa, Chisago, Clay, Clearwater, Cook, Crow Wing, Dakota, Douglas, Fillmore, Grant, Hennepin, Houston, Isanti, Itasca, Jackson, Koochiching, Lac qui Parle, Lake, Lyon, Marshall, McLeod, Mille Lacs, Morrison, Mower, Murray, Norman, Olmsted, Otter Tail, Pennington, Pipestone, Polk, Pope, Ramsey, Renville, Rice, Saint Louis, Scott, Sherburne, Stearns, Stevens, Traverse, Waseca, Washington, Wilkin, Winona, Wright, and Yellow Medicine.

If you represent a county not included in this dataset and would like to opt-in, please contact Heather Albrecht (Heather.Albrecht@hennepin.us), co-chair of the Minnesota Geospatial Advisory Council (GAC)’s Parcels and Land Records Committee's Open Data Subcommittee. County parcel data does not need to be in the GAC parcel data standard to be included. MnGeo will map the county fields to the GAC standard.

County parcel data records have been assembled into a single dataset with a common coordinate system (UTM Zone 15) and common attribute schema. The county parcel data attributes have been mapped to the GAC parcel data standard for Minnesota: https://www.mngeo.state.mn.us/committee/standards/parcel_attrib/parcel_attrib.html

This compiled parcel dataset was created using Python code developed by Minnesota state agency GIS professionals, and represents a best effort to map individual county source file attributes into the common attribute schema of the GAC parcel data standard. The attributes from counties are mapped to the most appropriate destination column. In some cases, the county source files included attributes that were not mapped to the GAC standard. Additionally, some county attribute fields were parsed and mapped to multiple GAC standard fields, such as a single line address. Each quarter, MnGeo provides a text file to counties that shows how county fields are mapped to the GAC standard. Additionally, this text file shows the fields that are not mapped to the standard and those that are parsed. If a county shares changes to how their data should be mapped, MnGeo updates the compilation. If you represent a county and would like to update how MnGeo is mapping your county attribute fields to this compiled dataset, please contact us.

This dataset is a snapshot of parcel data, and the source date of the county data may vary. Users should consult County websites to see the most up-to-date and complete parcel data.

There have been recent changes in date/time fields, and their processing, introduced by our software vendor. In some cases, this has resulted in date fields being empty. We are aware of the issue and are working to correct it for future parcel data releases.

The State of Minnesota makes no representation or warranties, express or implied, with respect to the use or reuse of data provided herewith, regardless of its format or the means of its transmission. THE DATA IS PROVIDED “AS IS” WITH NO GUARANTEE OR REPRESENTATION ABOUT THE ACCURACY, CURRENCY, SUITABILITY, PERFORMANCE, MECHANTABILITY, RELIABILITY OR FITINESS OF THIS DATA FOR ANY PARTICULAR PURPOSE. This dataset is NOT suitable for accurate boundary determination. Contact a licensed land surveyor if you have questions about boundary determinations.

DOWNLOAD NOTES: This dataset is only provided in Esri File Geodatabase and OGC GeoPackage formats. A shapefile is not available because the size of the dataset exceeds the limit for that format. The distribution version of the fgdb is compressed to help reduce the data footprint. QGIS users should consider using the Geopackage format for better results.

This resource is a member of a series. The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and were defined by local participants as part of the 2020 Census Participant Statistical Areas Program. The Census Bureau delineated the census tracts in situations where no local participant existed or where all the potential participants declined to participate. The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of census data and comparison back to previous decennial censuses. Census tracts generally have a population size between 1,200 and 8,000 people, with an optimum size of 4,000 people. When first delineated, census tracts were designed to be homogeneous with respect to population characteristics, economic status, and living conditions. The spatial size of census tracts varies widely depending on the density of settlement. Physical changes in street patterns caused by highway construction, new development, and so forth, may require boundary revisions. In addition, census tracts occasionally are split due to population growth, or combined as a result of substantial population decline. Census tract boundaries generally follow visible and identifiable features. They may follow legal boundaries such as minor civil division (MCD) or incorporated place boundaries in some States and situations to allow for census tract-to-governmental unit relationships where the governmental boundaries tend to remain unchanged between censuses. State and county boundaries always are census tract boundaries in the standard census geographic hierarchy. In a few rare instances, a census tract may consist of noncontiguous areas. These noncontiguous areas may occur where the census tracts are coextensive with all or parts of legal entities that are themselves noncontiguous. For the 2010 Census, the census tract code range of 9400 through 9499 was enforced for census tracts that include a majority American Indian population according to Census 2000 data and/or their area was primarily covered by federally recognized American Indian reservations and/or off-reservation trust lands; the code range 9800 through 9899 was enforced for those census tracts that contained little or no population and represented a relatively large special land use area such as a National Park, military installation, or a business/industrial park; and the code range 9900 through 9998 was enforced for those census tracts that contained only water area, no land area.

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 map of the NW suburbs of the Twin Cities.

Minnesota River: 3-D topographical map of the Minnesota River Valley highlighting the river bend in Mankato.

St. Croix River: 3-D topographical map of the St. Croix extending from Taylors Falls to the Mississippi confluence.

Mississippi River, Lake Pepin: 3-D topographical map of the confluence of Chippewa Creek and the Mississippi River.

Red Wing, MN: 3-D topographical map of Redwing, MN on the Mississippi River.

Winona, Minnesota: 3-D topographical map of Winona, MN highlighting the Mississippi River.

Cannon Falls, MN: 3-D topographical map of Cannon Falls area.

Rochester, MN: 3-D topographical map of Rochester and the surrounding area.

Northfield, MN: 3-D topographical map of Northfield and the surrounding area.

St. Louis River, MN: 3-D map of the St. Louis River and Duluth, Minnesota.

Lake Itasca, MN: 3-D map of the source of the Mississippi River.

Elmore, MN: 3-D topographical map of Elmore, MN in south-central Minnesota.

Glencoe, MN: 3-D topographical map of Glencoe, MN.

New Prague, MN: 3-D topographical map of the New Prague in south-central Minnesota.

Plainview, MN: 3-D topographical map of Plainview, MN.

Waterville-Morristown: 3-D map of the Waterville-Morris area in south-central Minnesota.

Eau Claire, WI: 3-D map of Eau Claire highlighting abandon river channels.

Dubuque, IA: 3-D topographical map of Dubuque and the Mississippi River.

Londonderry, NH: 3-D topographical map of Londonderry, NH.

Santa Cruz, CA: 3-D topographical map of Santa Cruz, California.

Crater Lake, OR: 3-D topographical map of Crater Lake, Oregon.

Mt. Rainier, WA: 3-D topographical map of Mt. Rainier in Washington.

Grand Canyon, AZ: 3-D topographical map of the Grand Canyon.

District of Columbia: 3-D map highlighting the confluence of the rivers and the Mall.

Ireland: 3-D grayscale map of Ireland.

New Jersey: 3-D grayscale map of New Jersey.

SP Crater, AZ: 3-D map of random craters in the San Francisco Mountains.

Mars Water Features: 3-D grayscale map showing surface water features from Mars.

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

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.

Minnesota's original public land survey plat maps were created between 1848 and 1907 during the first government land survey of the state by the U.S. Surveyor General's Office. This collection of more than 3,600 maps includes later General Land Office (GLO) and Bureau of Land Management maps up through 2001. Scanned images of the maps are available in several digital formats and most have been georeferenced.

The survey plat maps, and the accompanying survey field notes, serve as the fundamental legal records for real estate in Minnesota; all property titles and descriptions stem from them. They also are an essential resource for surveyors and provide a record of the state's physical geography prior to European settlement. Finally, they testify to many years of hard work by the surveying community, often under very challenging conditions.

The deteriorating physical condition of the older maps (drawn on paper, linen, and other similar materials) and the need to provide wider public access to the maps, made handling the original records increasingly impractical. To meet this challenge, the Office of the Secretary of State (SOS), the State Archives of the Minnesota Historical Society (MHS), the Minnesota Department of Transportation (MnDOT), MnGeo and the Minnesota Association of County Surveyors collaborated in a digitization project which produced high quality (800 dpi), 24-bit color images of the maps in standard TIFF, JPEG and PDF formats - nearly 1.5 terabytes of data. Funding was provided by MnDOT.

In 2010-11, most of the JPEG plat map images were georeferenced. The intent was to locate the plat images to coincide with statewide geographic data without appreciably altering (warping) the image. This increases the value of the images in mapping software where they can be used as a background layer.

A dataset listing Minnesota counties by population for 2024.

description: The TRSQ digital data set represents the Township, Range, Section, Quarter section, and Quarter-quarter section divisions of the state. Beginning in the late 1840s, the federal government began surveying Minnesota as part of the Public Land Survey System (PLSS). The resulting network of land survey lines divided the state into townships, ranges, sections, quarter sections, quarter-quarter sections and government lots, and laid the groundwork for contemporary land ownership patterns. The quarter-quarter section remains an important subdivision for rural Minnesota since these lines are used to define local boundaries, roads, and service areas. All survey lines were extended across water bodies despite the fact that U.S. Geological Survey (USGS) base maps depict them only on land. This addition allows all sections and townships to be represented as closed areas ensuring that township and range location can be determined for any point in the state. It also means that the data is not affected if lake levels change over time. The township, range and section boundaries were digitized at MnGeo (formerly the Land Management Information Center - LMIC) from the USGS 30' x 60' map series (1:100,000-scale). Quarter section and quarter-quarter section subdivisions were calculated using the section lines. They were not digitized from original plat book survey lines or from the meandered lines that surveyors laid out around water bodies. The existence of government lots within a quarter-quarter section is recorded in the data set; however, the government lot boundaries were not digitized. If a quarter-quarter section contains more than one government lot, the number of lots is recorded -- see Lineage, Section 2, for more detail. Note: For most uses, TRSQ has been superseded by the Minnesota Department of Natural Resources (DNR) 1:24,000-scale 'Control Point Generated PLS' data set which is free online. See https://gisdata.mn.gov/dataset/plan-mndnr-public-land-survey for more information. Also, many county surveyors offices have more accurate PLS (Public Land Survey) data sets. For county webpages and contact information, see http://www.mngeo.state.mn.us/cty_contacts.html .; abstract: The TRSQ digital data set represents the Township, Range, Section, Quarter section, and Quarter-quarter section divisions of the state. Beginning in the late 1840s, the federal government began surveying Minnesota as part of the Public Land Survey System (PLSS). The resulting network of land survey lines divided the state into townships, ranges, sections, quarter sections, quarter-quarter sections and government lots, and laid the groundwork for contemporary land ownership patterns. The quarter-quarter section remains an important subdivision for rural Minnesota since these lines are used to define local boundaries, roads, and service areas. All survey lines were extended across water bodies despite the fact that U.S. Geological Survey (USGS) base maps depict them only on land. This addition allows all sections and townships to be represented as closed areas ensuring that township and range location can be determined for any point in the state. It also means that the data is not affected if lake levels change over time. The township, range and section boundaries were digitized at MnGeo (formerly the Land Management Information Center - LMIC) from the USGS 30' x 60' map series (1:100,000-scale). Quarter section and quarter-quarter section subdivisions were calculated using the section lines. They were not digitized from original plat book survey lines or from the meandered lines that surveyors laid out around water bodies. The existence of government lots within a quarter-quarter section is recorded in the data set; however, the government lot boundaries were not digitized. If a quarter-quarter section contains more than one government lot, the number of lots is recorded -- see Lineage, Section 2, for more detail. Note: For most uses, TRSQ has been superseded by the Minnesota Department of Natural Resources (DNR) 1:24,000-scale 'Control Point Generated PLS' data set which is free online. See https://gisdata.mn.gov/dataset/plan-mndnr-public-land-survey for more information. Also, many county surveyors offices have more accurate PLS (Public Land Survey) data sets. For county webpages and contact information, see http://www.mngeo.state.mn.us/cty_contacts.html .

The 2015 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 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.

Hospitals: shows all hospitals in the state of Minnesota, arranged by county. Downloaded from the Minnesota Department of Health February 24, 2013. Hospital names and health system associations updated on April 10, 2013.

http://www.health.state.mn.us/divs/fpc/directory/fpcdir.html

Addresses cleaned and geocoded by the Hennepin County Human Services and Public Health Dept (HSPHD). Match rate 100% (135). Where possible road centerline geocoded locations were improved to parcel centroid. The field NAME contains the hospital name.

Link to Attribute Table Information: http://gis.hennepin.us/OpenData/Metadata/Minnesota%20Hospitals.pdf

Use Limitations: This data (i) is furnished "AS IS" with no representation as to completeness or accuracy; (ii) is furnished with no warranty of any kind; and (iii) is not suitable for legal, engineering or surveying purposes. Hennepin County shall not be liable for any damage, injury or loss resulting from this data.

© Initial creation completed by the Hennepin County Human Services and Public Health Dept (HSPHD), with additional information provided by the Hennepin County Medical Center. Hospital names and health system association updated by HCMC on April 10, 2013. Maintenance and update stewardship responsibilities will be completed by HSPHD. This layer is a component of Health data.