The following layers (in reverse chronological order) are viewable on the land and water data portals . You may download them using the links below.
Land Cover & Impervious: TCMA 1-Meter 2015
A 12 class land cover classification (1-meter resolution) land cover classification of the seven-county Twin Cities Metropolitan area for 2015.
download | resolution: 1m | extent: metro
Land Cover & Impervious: Duluth 1-Meter 2015
A 12 class land cover classification (1-meter resolution) land cover classification of the city of Duluth for 2015.
download | resolution: 1m | extent: city
Land Cover & Impervious: Rochester 1-Meter 2015
A 12 class land cover classification (1-meter resolution) land cover classification of the city of Rochester for 2015.
download | resolution: 1m | extent: city
Land Cover & Impervious: Minnesota 2013 (v2)
10 classes Minnesota Land Cover Classification and Impervious Surface Area with Landsat and Lidar Remote Sensing: 2013 update.
download | resolution: 15m | extent: statewide
Land Cover & Impervious: Twin Cities 2011
This is a 7 class land classification for the Twin Cities (Minneapolis and St. Paul) of Minnesota from multispectral Landsat imagery collected in 2011.
download | resolution: 10m | extent: metro
Land Cover: Lake of the Woods change from 1990 to 2010
A 10-meter land cover change from 1990 to 2010 for the Lake of the Woods/Rainy River Basin.
metadata | download | resolution: 10m | extent: region
Land Cover: Lake of the Woods (level 2 class) 2010
A 10-meter, 18 class classification of ~2010 land cover for the Lake of the Woods/Rainy River Basin.
metadata | download | resolution: 10m | extent: region
Urban Tree Cover: Minneapolis 2009
A 6 class land cover classification for Minneapolis, Minnesota focusing on Urban Tree Cover. It was created from multispectral QuickBird satellite imagery acquired on May 28, 2009 and LIDAR imagery acquired in June 2007 was available from the U.S. Army Corps of Engineers.
download | resolution: .6m | extent: city
Urban Tree Cover: St. Paul 2009
A 6 class land cover classification for Minneapolis, Minnesota focusing on Urban Tree Cover. It was created from multispectral QuickBird satellite imagery acquired on May 28, 2009 and LIDAR imagery acquired in June 2007 was available from the U.S. Army Corps of Engineers.
download | resolution: .6m | extent: city
Urban Tree Cover: Woodbury 2009
A 6 class land cover classification for Minneapolis, Minnesota focusing on Urban Tree Cover. It was created from multispectral QuickBird satellite imagery acquired on June 9, 2009.
download | resolution: 2m | extent: city
Lake Clarity 2008 (Raster)
This GIS data set includes water clarity measurements assembled from Landsat imagery, primarily Thematic Mapper and Enhanced Thematic Mapper Plus, for Minnesota lakes and bodies of water.
metadata | download | resolution: 30m | extent: statewide
Lake Clarity Averages
This GIS data set includes water clarity measurements assembled from Landsat imagery, primarily Thematic Mapper and Enhanced Thematic Mapper Plus, for Minnesota lakes larger than eight hectares in surface area contains data on more than 10,500 lakes at five-year intervals over the period 1985-2008. Only 2008 is displayed.
metadata | download | resolution: 30m | extent: statewide
Land Cover & Impervious: TCMA 2007 (5 class)
This is a 15-meter raster dataset of a land cover and impervious surface classification for 2013, level one classification with 5 classes. The classification was created using a combination of multitemporal Landsat 8 data and LiDAR data with Object-based image analysis. For urban or developed, a regression model relating the Landsat greenness variable to percent impervious was developed to estimate and map the percent impervious surface area at the pixel level.
download | resolution: 15m | extent: metro
Land Cover & Impervious: TCMA 2007 (15 class)
This is a 15-meter raster dataset of a land cover and impervious surface classification for 2013, level two classification with 15 classes. The classification was created using a combination of multitemporal Landsat 8 data and LiDAR data with Object-based image analysis. For urban or developed, a regression model relating the Landsat greenness variable to percent impervious was developed to estimate and map the percent impervious surface area at the pixel level.
download | resolution: 15m | extent: metro
Impervious Surface: TCMA 2002
Landsat Thematic Mapper data was used to map impervious surface area for the 7 county Twin Cities Metro Area (TCMA). Impervious area is mapped as a continuous variable from 0 to 100 percent for each 30-meter pixel.
download | resolution: 30m | extent: metro
Land Cover & Impervious: Minnesota 2000
A 5 class land cover classification for all of Minnesota created from multispectral Landsat imagery collected in 2000.
download | resolution: 30m | extent: statewide
Land Cover: MN 2000
This is a level one land covertype map for the entire state of Minnesota representing the year 2000. The covertype was derived via multitemporal, multispectral supervised image classification of satellite imagery acquired by the Landsat TM and Landsat ETM+ satellites. Seven level one land covertype classes were: urban, agriculture, grassland, forest, water, wetland and shrubland.
download | resolution: 30m | extent: statewide
Impervious Surface: MN 2000
Landsat Thematic Mapper data was used to map impervious surface area for the State. Impervious area is mapped as a continuous variable from 0 to 100 percent for each 30-meter pixel.
download | resolution: 30m | extent: statewide
Land Cover: TCMA 1998
Raster-based land cover data set derived from 30 meter resolution Thematic Mapper satellite imagery. The coverage consists of 7 classes including: agriculture, extraction, forest, grass, urban, water, and wetland. The extent is of Twin City Metro Area, 7 county metro area of Minneapolis and St. Paul Minnesota.
download | resolution: 30m | extent: metro
Impervious Surface: TCMA 1998
Landsat Thematic Mapper data was used to map impervious surface area for the 7 county Twin Cities Metro Area (TCMA). Impervious area is mapped as a continuous variable from 0 to 100 percent for each 30-meter pixel.
download | resolution: 30m | extent: metro
Land Cover: TCMA 1991
Raster-based land cover data set derived from 30 meter resolution Thematic Mapper satellite imagery. The coverage consists of 7 classes including: agriculture, extraction, forest, grass, urban, water, and wetland. The extent is of Twin City Metro Area, 7 county metro area of Minneapolis and St. Paul Minnesota.
download | resolution: 30m | extent: metro
Impervious Surface: TCMA 1991
Landsat Thematic Mapper data was used to map impervious surface area for the 7 county Twin Cities Metro Area (TCMA). Impervious area is mapped as a continuous variable from 0 to 100 percent for each 30-meter pixel.
download | resolution: 30m | extent: metro
Land Cover: Lake of the Woods (level 2 class) 1990
A 10-meter, 18 class classification of ~1990 land cover for the Lake of the Woods/Rainy River Basin.
download | resolution: 10m | extent: region
Impervious Surface: MN 1990
Landsat Thematic Mapper data was used to map impervious surface area for the State. Impervious area is mapped as a continuous variable from 0 to 100 percent for each 30-meter pixel.
download | resolution: 30m | extent: statewide
Land Cover: TCMA 1986
Raster-based land cover data set derived from 30 meter resolution Thematic Mapper satellite imagery. The coverage consists of 7 classes including: agriculture, extraction, forest, grass, urban, water, and wetland. The extent is of Twin City Metro Area, 7 county metro area of Minneapolis and St. Paul Minnesota.
download | resolution: 30m | extent: metro
Impervious Surface: TCMA 1986
Landsat Thematic Mapper data was used to map impervious surface area for the 7 county Twin Cities Metro Area (TCMA). Impervious area is mapped as a continuous variable from 0 to 100 percent for each 30-meter pixel.
download | resolution: 30m | extent: metro
Lake Clarity 1975 (Raster)
This GIS data set includes water clarity measurements assembled from Landsat Multi-Spectral Scanner (MSS) imagery and should be used with caution since it may not be as reliable as the other datasets.
