Generalized Land Use Historical (1984, 1990, 1997, 2000, 2005, 2010, 2016, 2020)

The Historical Generalized Land Use 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 1984, 1990, 1997, 2000, 2005, 2010, 2016 and 2020 air photos and other source data, with additional assistance from county parcel data and assessor's information. <br/><br/>The Metropolitan Council has routinely developed generalized land use for the Twin Cities region since 1984 to support its statutory responsibilities and assist in long range planning for the Twin Cities area. The Council uses land use information to monitor growth and to evaluate changing trends in land consumption for various urban purposes. The Council uses the land use trend data in combination with its forecasts of households and jobs to plan for the future needs and financing of Metropolitan services (i.e. Transit, Wastewater Services, etc.). Also, in concert with individual local units of government, the land use and forecast data are used to evaluate expansions of the metropolitan urban service area (MUSA). <br/><br/>The Council does not specifically survey the rights-of-way of minor highways, local streets, parking lots, railroads, or other utility easements. The area occupied by these uses is included with the adjacent land uses, whose boundaries are extended to the centerline of the adjacent rights-of way or easements. The accuracy of Council land use survey data is suitable for regional planning purposes, but should not be used for detailed area planning, nor for engineering work. <br/><br/>Until 1997, the Metropolitan Council had manually interpreted aerial photos on mylar tracing paper into a 13-category land-use classification system to aggregate and depict changing land use data. In 1997, with technological advances in GIS and improved data, the Metropolitan Council was able to delineate land uses from digital aerial photography with counties' parcel and assessor data and captured information with straight 'heads-up' digitizing with GIS software. Also, understanding that land use data collected and maintained at the county and city level are collected at different resolutions using different classification schemes, the Metropolitan Council worked with local communities and organizations to develop a cooperative solution to integrate the Council's land use interpretation with a generally agreed upon regional classification system. By 2000, the Metropolitan Council had not only expanded their Generalized Land Use Classification system to include 22 categories, but had refined how they categorized land (removing all ownership categories) to reflect actual use. See the Entities and Atributes section of the metadata for a detailed description of each of the land use categories and available subcategories. <br/><br/>With the completion of the 2020 Generalized Land Use dataset, regional and local planners have the ability to map changes in urban growth and development in a geographic information system (GIS) database. By tracking land use changes, the Metropolitan Council and local planners can better visualize development trends and anticipate future growth needs. <br/><br/><br/>NOTE ABOUT COMPARATIVE ANALYSIS: <br/><br/>It is important to understand the changes between land use inventory years and how to compare recent land use data to historical data. <br/><br/>In general, over the land use years, more detailed land use information has been captured. Understanding these changes can help interpret land use changes and trends in land consumption. For detailed category definitions, specific land use comparisons and how best to compare the land uses between 1984 and 2020, please refer to the Attribute Accuracy or the Data Quality section of the metadata. <br/><br/>It is also important to note that changes in data collection methodology also effects the ability to compare land use years: <br/><br/>- In 2000, the land use categories were modified to more accurately reflect the use of the land rather than ownership. Although this has minimal effect on associating categories between 1997 and 2000, is may have had an affect on some particular land use. For example, land owned by a community or county but had no apparent active use could have been classified as 'Public/ Semi-Public' prior to 2000. In 2000, land with no apparent use, regardless of who owns it, is classified as 'Undeveloped.' <br/><br/>- With better resolution of air photos beginning in 2000, the incorporation of property information from county assessors and the use of more accurate political boundaries (particularly on the exterior boundaries of the region), positive impacts were made on the accuracy of new land use delineations between pre-2000 land use data and data collected between 2000 and 2020. With the improved data, beginning in 2000, a greater effort to align land use designations, both new and old, to correspond with property boundaries (county parcels) where appropriate. In addition, individual properties were reviewed to assess the extent of development. In most cases, if properties under 5 acres were assessed to be at least 75% developed, then the entire property was classified as a developed land use (not 'Undeveloped'). As a result of these realignments and development assessments, changes in land use between early land use years (1984-1997) and more recent years (2000-2020) will exist in the data that do NOT necessarily represent actual land use change. These occurrences can be found throughout the region. <br/><br/>There are also numerous known deficiencies in the datasets. Some known deficiencies are specific to a particular year while others may span the entire time series. For more details, please refer to Attribute Accuracy of the Data Quality section of the metadata.

Additional Info

Field Value
dsAccessConst None. This dataset is public domain under the Minnesota Government Data Practices Act (Minnesota Statutes Chapter 13). If the dataset is not available from the Online Linkage in Section 6, please contact the Distribution Contact Person.
dsCurrentRef Ground condition dates for the data are as follows:

2020: Aerial photography was taken April 4,5 and 10, 2020. County parcel and assessors data was from varying dates in the spring of 2020.

2016: Aerial photography was taken April 9 - 22, 2016. County parcel and assessors data was from varying dates in the spring of 2016.

2010: Aerial photography was taken April 7 - 18, 2010. County parcel and assessors data was from varying dates in the spring of 2010 with the exception of Washington County where the date was July 2010.

2005: Aerial photography was taken April 8, 13 and 14, 2005. County parcel and assessors data was from varying dates in the spring of 2005.

2000: Aerial photography was taken May 1, 2000 (West Half of the metro) and May 2, 2000 (East Half of the metro). County parcel and assessors data was from varying dates in the spring of 2000.

1997: Air photos were taken April 13th and 14th, 1997. Parcel and assessors data was from varying dates in the spring of 1997.

1990: Aerial photography was taken May 4th & 5th, 1990.

1984: Aerial photography was taken sometime in spring of 1984. Minor modifications were made in December 2020 to some of the land use classifications for 2010 and 2016 to correct for coding inconsitstencies.
dsModifiedDate 2021-09-02 00:30:38
dsOriginator Metropolitan Council
dsPeriodOfContent 4/10/2020
dsPurpose To aid in forecasting region-wide land supply and demand and to be used as a general regional planning tool. This data does not indicate developability of land, but does show the location of 'Vacant and Agricultural' land (1984, 1990 & 1997) or 'Undeveloped' land (2000, 2005, 2010, 2016, 2020) based on the definitions described in Section 5 of this metadata.
gdrsDsGuid {8f386045-e47f-45fc-a978-02f32c6f76b7}
spatial {"type":"Polygon","coordinates":[[[-94.012, 44.471],[-94.012, 45.415], [-92.732, 45.415], [-92.732, 44.471], [-94.012, 44.471]]]}

Dataset extent

Tiles © Esri — Esri, DeLorme, NAVTEQ, TomTom, Intermap, iPC, USGS, FAO, NPS, NRCAN, GeoBase, Kadaster NL, Ordnance Survey, Esri Japan, METI, Esri China (Hong Kong), and the GIS User Community