Minnesota Land Cover Classification and Impervious Surface Area by Landsat and Lidar: 2013 update - Version 2

This is a 15-meter raster dataset of a land cover and impervious surface classification for 2013, level two classification. The classification was created using a combination of multitemporal Landsat 8 data and LiDAR data with Object-based image analysis. By using objects instead of pixels we were able to utilize multispectral data along with spatial and contextual information of objects such as shape, size, texture and LiDAR-derived metrics to distinguish different land cover types. While OBIA has become the standard procedure for classification of high resolution imagery we found that it works equally well with Landsat imagery. For the objects classified as 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. <br/><br/>This dataset was funded by the the Minnesota Environment and Natural Resources Trust Fund (ENRTF).

Additional Info

Field Value
Last Updated January 11, 2017, 11:02
Created October 26, 2016, 10:02
dsAccessConst The Remote Sensing and Geospatial and Analysis Laboratory, University of Minnesota, has attempted to produce accurate maps, statistics and information of land cover and impervious surface area. However, it makes no representation or warranties, either expressed or implied, for the data accuracy, currency, suitability or reliability for any particular purpose. Although every effort has been made to ensure the accuracy of information, errors and conditions originating from the source data and processing may be present in the data supplied. Users are reminded that all geospatial maps and data are subject to errors in positional and thematic accuracy. The user accepts the data -- as is -- and assumes all risks associated with its use. The University of Minnesota assumes no responsibility for actual or consequential damage incurred as a result of any user's reliance on the data. The data are the intellectual property of the University of Minnesota.
dsCurrentRef A multitemporal composite of Landsat imagery from the summer of 2013 and 2014 and fall of 2013, lidar data of 2008, 2009, 2010, 2011, and 2012 were classified.
dsMetadataUrl ftp://ftp.gisdata.mn.gov/pub/gdrs/data/pub/edu_umn/base_landcover_minnesota/metadata/metadata.html
dsModifiedDate 2017-01-10 23:54:41
dsOriginator Remote Sensing and Geospatial Analysis Laboratory, University of Minnesota - Version 2
dsPurpose Land cover information offers important inputs to local, regional, and state land use planning and natural resource monitoring.<br/>

Dataset extent