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Charles M. Russell National Wildlife Refuge Spot Landcover Classification in Relation to Greater Sage Grouse This landcover raster was generated through a Random Forest predictive model developed in R using a combination of image-derived and ancillary variables, and field-derived training points grouped into 18 classes. Overall accuracy, generated internally through bootstrapping, was 75.5%. A series of post-modeling steps brought the final number of land cover classes to 28. Categories: Data; Types: Citation; Tags: Birds, CMR, Charles M. Russell National Wildlife Refuge, Data Visualization & Tools, Landcover, All tags... Montana, North Central CASC, SPOT Imagery, Science Tools For Managers, Wildlife and Plants, environment, imageryBaseMapsEarthCover, Fewer tags