Remote Sensing and Geospatial Analysis Laboratory, University of Minnesota - Version 2This 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. This dataset was funded by the the Minnesota Environment and Natural Resources Trust Fund (ENRTF). Land cover information offers important inputs to local, regional, and state land use planning and natural resource monitoring. 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.Filesbase-landcover-minnesotaengPublicMinnesota Land Cover Classification and Impervious Surface Area by Landsat and Lidar: 2013 update - Version 2 [Minnesota]OtherMinnesotaMinnesota Geospatial Commons