This is a polygon dataset for county boundaries as well as for city, township and unorganized territory (CTU) boundaries in the Twin Cities 7-county metropolitan area. The linework for this dataset comes from individual counties and is assembled by the Metropolitan Council for the MetroGIS community. This is a MetroGIS Regionally Endorsed dataset https://metrogis.org/.

The County CTU Lookup Table here https://gisdata.mn.gov/dataset/us-mn-state-metc-bdry-counties-and-ctus-lookup
is also included in this dataset and contains various data related to cities, townships, unorganized territories (CTUs) and any divisions created by county boundaries splitting them is also included in the dataset.

This dataset is updated quarterly. This dataset is composed of three shape files and one dbf table.
- Counties.shp = county boundaries
- CTUs.shp = city, township and unorganized territory boundaries
- CountiesAndCTUs.shp = combined county and CTU boundaries
- CountyCTULookupTable.dbf = various data related to CTUs and any divisions created by county boundaries splitting them is also included in the dataset, described here: https://gisdata.mn.gov/dataset/us-mn-state-metc-bdry-counties-and-ctus-lookup

NOTES:

- On 3/17/2011 it was discovered that the CTU ID used for the City of Lake St. Croix Beach was incorrect. It was changed from 2394379 to 2395599 to match GNIS.

- On 3/17/2011 it was discovered that the CTU ID used for the City of Lilydale was incorrect. It was changed from 2394457 to 2395708 to match GNIS.

- On 11/9/2010 it was discovered that the CTU ID used for the City of Crystal was incorrect. It was changed from 2393541 to 2393683 to match GNIS.

- Effective April 2008, a change was made in GNIS to match the FIPS place codes to the "civil" feature for each city instead of the "populated place" feature. Both cities and townships are now "civil" features within GNIS. This means that the official GNIS unique ID for every city in Minnesota has changed.

- The five digit CTU codes in this dataset are identical to the Federal Information Processing Standard (FIPS) ''Place'' codes. They are also used by the Census Bureau and many other organizations and are proposed as a MN state data coding standard.

- Cities and townships have also been referred to as ''MCDs'' (a census term), however this term technically refers to the part of each city or township within a single county. Thus, a few cities in the metro area that are split by county boundaries are actually comprised of two different MCDs. This was part of the impetus for a proposed MN state data standard that uses the ''CTU'' terminology for clarity.

- The boundary line data for this dataset comes from each county.

- A variety of civil divisions of the land exist within the United States. In Minnesota, only three types exist - cities, townships and unorganized territories. All three of these exist within the Twin Cities seven county area. The only unorganized territory is Fort Snelling (a large portion of which is occupied by the MSP International Airport).

- Some cities are split between two counties. Only those parts of cities within the 7-county area are included.

- Prior to the 2000 census, the FIPS Place code for the City of Greenwood in Hennepin County was changed from 25928 to 25918. This dataset reflects that change.

This dataset includes all 7 metro counties that have made their parcel data freely available without a license or fees.

This dataset is a compilation of tax parcel polygon and point layers assembled into a common coordinate system from Twin Cities, Minnesota metropolitan area counties. No attempt has been made to edgematch or rubbersheet between counties. A standard set of attribute fields is included for each county. The attributes are the same for the polygon and points layers. Not all attributes are populated for all counties.

NOTICE: The standard set of attributes changed to the MN Parcel Data Transfer Standard on 1/1/2019.
https://www.mngeo.state.mn.us/committee/standards/parcel_attrib/parcel_attrib.html

See section 5 of the metadata for an attribute summary.

Detailed information about the attributes can be found in the Metro Regional Parcel Attributes document.

The polygon layer contains one record for each real estate/tax parcel polygon within each county's parcel dataset. Some counties have polygons for each individual condominium, and others do not. (See Completeness in Section 2 of the metadata for more information.) The points layer includes the same attribute fields as the polygon dataset. The points are intended to provide information in situations where multiple tax parcels are represented by a single polygon. One primary example of this is the condominium, though some counties stacked polygons for condos. Condominiums, by definition, are legally owned as individual, taxed real estate units. Records for condominiums may not show up in the polygon dataset. The points for the point dataset often will be randomly placed or stacked within the parcel polygon with which they are associated.

The polygon layer is broken into individual county shape files. The points layer is provided as both individual county files and as one file for the entire metro area.

In many places a one-to-one relationship does not exist between these parcel polygons or points and the actual buildings or occupancy units that lie within them. There may be many buildings on one parcel and there may be many occupancy units (e.g. apartments, stores or offices) within each building. Additionally, no information exists within this dataset about residents of parcels. Parcel owner and taxpayer information exists for many, but not all counties.

This is a MetroGIS Regionally Endorsed dataset.

Additional information may be available from each county at the links listed below. Also, any questions or comments about suspected errors or omissions in this dataset can be addressed to the contact person at each individual county.

Anoka = http://www.anokacounty.us/315/GIS
Caver = http://www.co.carver.mn.us/GIS
Dakota = http://www.co.dakota.mn.us/homeproperty/propertymaps/pages/default.aspx
Hennepin = https://gis-hennepin.hub.arcgis.com/pages/open-data
Ramsey = https://www.ramseycounty.us/your-government/open-government/research-data
Scott = http://opendata.gis.co.scott.mn.us/
Washington: http://www.co.washington.mn.us/index.aspx?NID=1606

High-quality GIS land use maps for the Twin Cities Metropolitan Area for 1968 that were developed from paper maps (no GIS version existed previously).The GIS shapefiles were exported using ArcGIS Quick Import Tool from the Data Interoperability Toolbox. The coverage files was imported into a file geodatabase then exported to a .shp file for long-term use without proprietary software. An example output of the final GIS file is include as a pdf, in addition, a scan of the original 1968 map (held in the UMN Borchert Map Library) is included as a pdf. Metadata was extracted as an xml file. Finally, all associated coverage files and original map scans were zipped into one file for download and reuse. Data was uploaded to ArcGIS Online 3/9/2020. Original dataset available from the Data Repository of the University of Minnesota: http://dx.doi.org/10.13020/D63W22

The Metropolitan Council routinely compiles individual land use plans and plan amendments from communities within the seven-county Twin Cities metropolitan area into a single regional data layer. A principal goal of the Regional Planned Land Use dataset is to allow users to view, analyze and display planned land use data for anywhere in the seven county metropolitan area with a consistent land use classification scheme. The Metropolitan Council uses the Regional Planned Land Use (PLU) data to help monitor growth and plan for regional services such as regional parks, transit service, and wastewater collection and treatment.

Although the planned land use data is based on the locally adopted land use plans and designations for each community, it represent only data that has been submitted to the Metropolitan Council for review per the Metropolitan Land Planning Act of 1995 (Minn. Stat 473.864, Subd 2 and 473.175, Subd 1). See Data Quality Information (Section 2 of this metadata) for specifics about the Metropolitan Land Planning Act of 1995 under Completeness information.

Since there is no official State or Regional land use coding scheme that communities must conform with, the variability of content and codes between communities' land use plans is nearly as vast as the number of communities themselves (187). Differences among communities can range from the implementation of different land use categories to conflicting definitions of similar categories. The PLU dataset attempts to effectively level out the variability among communities by translating communities land use categories and descriptions into a common classification scheme developed and endorsed by MetroGIS (a regional GIS data sharing consortium) participants while retaining each communities' original categories. Although the comparability of land use plans between communities has greatly improved as a result of this translation or "regionalization" of communities' land use codes, it is possible that not all community land use definitions have been precisely translated into the most appropriate regional land use category.

In conjunction with other regional information (i.e., land use trend data, households and jobs forecasts), the PLU data can help communities more easily understand regional and sub-regional planning goals and Council staff, working with individual local units of government, can better plan for the future needs and financing of regional services.

- Contact individual communities for more information on their locally adopted planned land use categories.

- See Data Quality Information (Section 2 of this metadata) for specifics about the development of the regional dataset and its accuracy.

- See Entities and Attributes Information (Section 5 of this metadata) for specifics about the regional land use codes and categories.

Public Parcels - Metro CTUsThis web map was created by Metro Transit's Transit Oriented Development (TOD) Office to showcase the newly expanded public parcel data in relation to existing and planned transit facilities across the Twin Cities Metropolitan Area. As of August, 2019, the parcels can also be viewed in relation to Federally approved Opportunity Zones. More information on the new US Department of Treasury Opportunity Zone Program can be found here. The purpose of the public parcel data is to increase awareness of the location and quantity of publicly owned lands at all levels of government. The Q-1 2020 dataset now includes more than 35,000 parcels from across 128 cities, townships, and unorganized territories (CTUs). These parcels are further classified and displayed by eight broad ownership or administrative categories. Users can view, analyze, share, and research publicly-owned lands that may be good candidates for TOD or some other higher/better use.The purpose of the original pilot project was to increase awareness of publicly owned parcel locations relative to Metro-area transit facilities and facilitate TOD analyses. While the current geographic extent of the data has been greatly expanded, the purpose remains the same; to raise awareness of publicly owned land for the highest & best use.For those with desktop GIS software, the Public Parcel shapefile and/or geodatabase can be downloaded here: https://gisdata.mn.gov/dataset/us-mn-state-metc-plan-public-parcels-metro-ctus

Urban areas in the context of this dataset includes the Twin Cities Metro Area, as well as outstate metro areas and rural downtowns, for all municipalities with more than 100 residents.

The 2020 Generalized Land Use Inventory dataset encompasses the seven county Twin Cities (Minneapolis and St. Paul) Metropolitan Area in Minnesota. The dataset was developed by the Metropolitan Council, a regional governmental organization that deals, in part, with regional issues and long range planning for the Twin Cities area. The data were interpreted from April 2020 air photos, with additional assistance from county parcel data and assessor's information, Internet information, field checks , and community review.

The following generalized land use classes are used (some of which have subclasses):

Single Family Residential
Multifamily Residential
Office
Retail and Other Commercial
Mixed Use
Industrial and Utility
Extractive
Institutional
Park, Recreational, or Preserve
Golf Course
Major Highway
Railway
Airport
Agriculture
Undeveloped
Water

See Section 5 of the metadata for a detailed description of each of these land use categories and available subcategories.

Note: Although this dataset does contain an 'Undeveloped' land category, this dataset does not attempt to delineate what lands might be considered developable. The definition of that category can be found in Section 5 of this metadata.

More information about the Metropolitan Council's generalized land use data can be found here Landuse Notes

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.

This dataset includes all 7 metro counties that have made their parcel data freely available without a license or fees. This dataset is a compilation of tax parcel polygon and point layers assembled into a common coordinate system from Twin Cities, Minnesota metropolitan area counties. No attempt has been made to edgematch or rubbersheet between counties. A standard set of attribute fields is included for each county. The attributes are the same for the polygon and points layers. Not all attributes are populated for all counties. NOTICE: The standard set of attributes changed to the MN Parcel Data Transfer Standard on 1/1/2019. https://www.mngeo.state.mn.us/committee/standards/parcel_attrib/parcel_attrib.html See section 5 of the metadata for an attribute summary. Detailed information about the attributes can be found in the Metro Regional Parcel Attributes document. The polygon layer contains one record for each real estate/tax parcel polygon within each county's parcel dataset. Some counties have polygons for each individual condominium, and others do not. (See Completeness in Section 2 of the metadata for more information.) The points layer includes the same attribute fields as the polygon dataset. The points are intended to provide information in situations where multiple tax parcels are represented by a single polygon. One primary example of this is the condominium, though some counties stacked polygons for condos. Condominiums, by definition, are legally owned as individual, taxed real estate units. Records for condominiums may not show up in the polygon dataset. The points for the point dataset often will be randomly placed or stacked within the parcel polygon with which they are associated. The polygon layer is broken into individual county shape files. The points layer is provided as both individual county files and as one file for the entire metro area. In many places a one-to-one relationship does not exist between these parcel polygons or points and the actual buildings or occupancy units that lie within them. There may be many buildings on one parcel and there may be many occupancy units (e.g. apartments, stores or offices) within each building. Additionally, no information exists within this dataset about residents of parcels. Parcel owner and taxpayer information exists for many, but not all counties. This is a MetroGIS Regionally Endorsed dataset. Additional information may be available from each county at the links listed below. Also, any questions or comments about suspected errors or omissions in this dataset can be addressed to the contact person at each individual county. Anoka = http://www.anokacounty.us/315/GIS Caver = http://www.co.carver.mn.us/GIS Dakota = http://www.co.dakota.mn.us/homeproperty/propertymaps/pages/default.aspx Hennepin = http://www.hennepin.us/gisopendata Ramsey = https://www.ramseycounty.us/your-government/open-government/research-data Scott = http://opendata.gis.co.scott.mn.us/ Washington: http://www.co.washington.mn.us/index.aspx?NID=1606

This dataset was created by a joint collaborative project involving the technical and managerial GIS staff from the ten Metropolitan Counties of the Twin Cities in Minnesota (Anoka, Carver, Chisago, Dakota, Hennepin, Isanti, Ramsey, Scott, Sherburne and Washington), the Metropolitan Emergency Services Board (MESB), MetroGIS and the Metropolitan Council. Core needs this dataset are intended to satisfy include:

- Vehicular routing;
- Address geocoding;
- Next Generation 911 call routing and location validation;
- Emergency services dispatching;
- Linear referencing uses;
- Cartographic representation of road features;

For specific questions regarding centerline alignments or attributes, please contact the county below
Anoka: https://www.anokacounty.us/315/GIS
Carver: gis@co.carver.mn.us
Chisago: gisservices@chisagocountymn.gov
Dakota: gis@co.dakota.mn.us
Hennepin: gis.info@hennepin.us
Isanti: Nate.Kirkwold@co.isanti.mn.us
Ramsey: RCGISMetaData@co.ramsey.mn.us
Sherburne: gis@co.sherburne.mn.us
Scott: gis@co.scott.mn.us
Washington: gis@co.washington.mn.us

This dataset is a compilation of tax parcel polygon and point layers from the seven Twin Cities, Minnesota metropolitan area counties of Anoka, Carver, Dakota, Hennepin, Ramsey, Scott and Washington. The seven counties were assembled into a common coordinate system. No attempt has been made to edgematch or rubbersheet between counties. A standard set of attribute fields is included for each county. (See section 5 of the metadata). The attributes are the same for the polygon and points layers. Not all attributes are populated for all counties.

The polygon layer contains one record for each real estate/tax parcel polygon within each county's parcel dataset. Some counties will polygons for each individual condominium, and others do not. (See Completeness in Section 2 of the metadata for more information.) The points layer includes the same attribute fields as the polygon dataset. The points are intended to provide information in situations where multiple tax parcels are represented by a single polygon. The primary example of this is the condominium. Condominiums, by definition, are legally owned as individual, taxed real estate units. Records for condominiums may not show up in the polygon dataset. The points for the point dataset often will be randomly placed or stacked within the parcel polygon with which they are associated.

The polygon layer is broken into individual county shape files. The points layer is one file for the entire metro area.

In many places a one-to-one relationship does not exist between these parcel polygons or points and the actual buildings or occupancy units that lie within them. There may be many buildings on one parcel and there may be many occupancy units (e.g. apartments, stores or offices) within each building. Additionally, no information exists within this dataset about residents of parcels. Parcel owner and taxpayer information exists for many, but not all counties.

Polygon and point counts for each county are as follows (based on the January, 2007 dataset):

Anoka = 129,392 polygons, 129,392 points
Carver = 37,021 polygons, 37,021 points
Dakota = 135,586 polygons, 148,952 points
Hennepin = 358,064 polygons, 419,736 points
Ramsey = 148,967 polygons, 166,280 points
Scott = 54,741 polygons, 54,741 points
Washington = 97,922 polygons, 102,309 points

This is a MetroGIS Regionally Endorsed dataset.

Each of the seven Metro Area counties has entered into a multiparty agreement with the Metropolitan Council to assemble and distribute the parcel data for each county as a regional (seven county) parcel dataset.

A standard set of attribute fields is included for each county. The attributes are identical for the point and polygon datasets. Not all attributes fields are populated by each county. Detailed information about the attributes can be found in the MetroGIS Regional Parcels Attributes 2006 document.

Additional information may be available in the individual metadata for each county at the links listed below. Also, any questions or comments about suspected errors or omissions in this dataset can be addressed to the contact person listed in the individual county metadata.

Anoka = http://www.anokacounty.us/315/GIS

Caver = http://www.co.carver.mn.us/GIS

Dakota = http://www.co.dakota.mn.us/homeproperty/propertymaps/pages/default.aspx

Hennepin: http://www.hennepin.us/gisopendata

Ramsey = https://www.ramseycounty.us/your-government/open-government/research-data

Scott = http://www.scottcountymn.gov/1183/GIS-Data-and-Maps

Washington = http://www.co.washington.mn.us/index.aspx?NID=1606

This dataset is a compilation of tax parcel polygon and point layers from the seven Twin Cities, Minnesota metropolitan area counties of Anoka, Carver, Dakota, Hennepin, Ramsey, Scott and Washington. The seven counties were assembled into a common coordinate system. No attempt has been made to edgematch or rubbersheet between counties. A standard set of attribute fields is included for each county. (See section 5 of the metadata). The attributes are the same for the polygon and points layers. Not all attributes are populated for all counties.

The polygon layer contains one record for each real estate/tax parcel polygon within each county's parcel dataset. Some counties will polygons for each individual condominium, and others do not. (See Completeness in Section 2 of the metadata for more information.) The points layer includes the same attribute fields as the polygon dataset. The points are intended to provide information in situations where multiple tax parcels are represented by a single polygon. The primary example of this is the condominium. Condominiums, by definition, are legally owned as individual, taxed real estate units. Records for condominiums may not show up in the polygon dataset. The points for the point dataset often will be randomly placed or stacked within the parcel polygon with which they are associated.

The polygon layer is broken into individual county shape files. The points layer is one file for the entire metro area.

In many places a one-to-one relationship does not exist between these parcel polygons or points and the actual buildings or occupancy units that lie within them. There may be many buildings on one parcel and there may be many occupancy units (e.g. apartments, stores or offices) within each building. Additionally, no information exists within this dataset about residents of parcels. Parcel owner and taxpayer information exists for many, but not all counties.

Polygon and point counts for each county are as follows (based on the January, 2005 dataset):

Anoka = 124,042 polygons, 124,042 points
Carver = 32,910 polygons, 32,910 points
Dakota = 130,989 polygons, 141,444 points
Hennepin = 353,759 polygons, 399,184 points
Ramsey = 148,266 polygons, 163,376 points
Scott = 49,958 polygons, 49,958 points
Washington = 93,794 polygons, 96,570 points

This is a MetroGIS Regionally Endorsed dataset.

Each of the seven Metro Area counties has entered into a multiparty agreement with the Metropolitan Council to assemble and distribute the parcel data for each county as a regional (seven county) parcel dataset.

A standard set of attribute fields is included for each county. The attributes are identical for the point and polygon datasets. Not all attributes fields are populated by each county. Detailed information about the attributes can be found in the MetroGIS Regional Parcels Attributes 2005 document.

Additional information may be available in the individual metadata for each county at the links listed below. Also, any questions or comments about suspected errors or omissions in this dataset can be addressed to the contact person listed in the individual county metadata.

Anoka = http://www.anokacounty.us/315/GIS

Caver = http://www.co.carver.mn.us/GIS

Dakota = http://www.co.dakota.mn.us/homeproperty/propertymaps/pages/default.aspx

Hennepin: http://www.hennepin.us/gisopendata

Ramsey = https://www.ramseycounty.us/your-government/open-government/research-data

Scott = http://www.scottcountymn.gov/1183/GIS-Data-and-Maps

Washington = http://www.co.washington.mn.us/index.aspx?NID=1606

The Transit Stops layer contains over 20,000 active and inactive transit stops in the Twin Cities seven county metropolitan area. The dataset includes attributes from the primary transit stop database maintained for Metro Transit and for customer information for other transit provider transit services. The locations are mapped referencing Road Centerlines (MN GAC standard) network along with streets generated internally at Metro Transit.

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 Blocks are statistical areas bounded on all sides by visible features, such as streets, roads, streams, and railroad tracks, and/or by nonvisible boundaries such as city, town, township, and county limits, and short line-of-sight extensions of streets and roads. Census blocks are relatively small in area; for example, a block in a city bounded by streets. However, census blocks in remote areas are often large and irregular and may even be many square miles in area. A common misunderstanding is that data users think census blocks are used geographically to build all other census geographic areas, rather all other census geographic areas are updated and then used as the primary constraints, along with roads and water features, to delineate the tabulation blocks. As a result, all 2020 Census blocks nest within every other 2020 Census geographic area, so that Census Bureau statistical data can be tabulated at the block level and aggregated up to the appropriate geographic areas. Census blocks cover all territory in the United States, Puerto Rico, and the Island Areas (American Samoa, Guam, the Commonwealth of the Northern Mariana Islands, and the U.S. Virgin Islands). Blocks are the smallest geographic areas for which the Census Bureau publishes data from the decennial census. A block may consist of one or more faces.

description: The Metropolitan Area Integrated Land Use/Cover file serves as a navigation and reference tool for the LMIC Environmental Atlas and AtlasGDS desktop GIS products. It combines the 1997 Generalized Land Use data set produced by the Metropolitan Council with additional land cover classifications. The 1997 Generalized Land Use data set areas defined as 'vacant/agricutural' or 'parks and recreation areas' were integrated with natural resource features such as wetlands and forest cover from other data sets. Some ownership information was also added. The data set is in EPPL7 raster format, with a 30-meter grid cell size. The original 1997 Generalized Land Use data set encompasses the seven county Twin Cities (Minneapolis and St. Paul) Metropolitan Area in Minnesota. The data set was developed by the Metropolitan Council, a regional governmental organization that deals, in part, with regional issues and long range planning for the Twin Cities area. The data were interpreted from 1997 air photos and include the generalized land use classes of: single family residential, multi-family residential, commercial, industrial, public and semi-public, airports, parks and recreation, vacant and agricultural, major four lane highways, open water bodies, farmsteads, extractive, public industrial, industrial parks not developed, and public and semi-public not developed.; abstract: The Metropolitan Area Integrated Land Use/Cover file serves as a navigation and reference tool for the LMIC Environmental Atlas and AtlasGDS desktop GIS products. It combines the 1997 Generalized Land Use data set produced by the Metropolitan Council with additional land cover classifications. The 1997 Generalized Land Use data set areas defined as 'vacant/agricutural' or 'parks and recreation areas' were integrated with natural resource features such as wetlands and forest cover from other data sets. Some ownership information was also added. The data set is in EPPL7 raster format, with a 30-meter grid cell size. The original 1997 Generalized Land Use data set encompasses the seven county Twin Cities (Minneapolis and St. Paul) Metropolitan Area in Minnesota. The data set was developed by the Metropolitan Council, a regional governmental organization that deals, in part, with regional issues and long range planning for the Twin Cities area. The data were interpreted from 1997 air photos and include the generalized land use classes of: single family residential, multi-family residential, commercial, industrial, public and semi-public, airports, parks and recreation, vacant and agricultural, major four lane highways, open water bodies, farmsteads, extractive, public industrial, industrial parks not developed, and public and semi-public not developed.

This dataset contains City Hall locations in Hennepin County.

Link to Attribute Table Information: http://gis.hennepin.us/OpenData/Metadata/City%20Halls.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.

© Hennepin County Emergency Management, Hennepin County GIS Office This layer is a component of Datasets for Hennepin County AGOL and Hennepin County Open Data.

This layer is a component of Natural resources interactive map.

This data set includes all scooter trips for the month of July, within the City of Minneapolis for the pilot program that began in March 2019. We have removed data when trips were over 7 hours and less than 0 miles or greater than 24 miles.

Field Descriptions

TripID: a unique identifier for each trip created by the City of Minneapolis

TripDuration: trip time in seconds

TripDistance: trip distance in meters

StartTime: time the trip started, rounded to the nearest half hour

EndTime: time the trip ended, rounded to the nearest half hour

StartCenterlineID: the street centerline GBSID or trail centerline Feature Unique ID the trip started on. Refer to the Street Centerline dataset here: http://opendata.minneapolismn.gov/datasets/mpls-centerline, and the trail centerline dataset here: https://gisdata.mn.gov/dataset/us-mn-state-metrogis-trans-metro-colabtiv-trails-bike

StartCenterlineType: The type of centerline the trip started on, either street or trail.

EndCenterlineID: the street centerline GBSID or trail centerline Feature Unique ID the trip ended on. Refer to the Street Centerline dataset here: http://opendata.minneapolismn.gov/datasets/mpls-centerline, and the trail centerline dataset here: https://gisdata.mn.gov/dataset/us-mn-state-metrogis-trans-metro-colabtiv-trails-bike

EndCenterlineType: The type of centerline the trip ended on, either street or trail.

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 dataset consists of summary data for commercial, industrial, and public and institutional projects, based on building permits issued during each calendar year by cities and townships within the Region. Data is collected via an annual survey of building officials, in conjunction with collection of data on residential building permits.