Description
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 72.7%. A series of post-modeling steps brought the final number of land cover classes to 28.
Resources
| Name | Format | Description | Link |
|---|---|---|---|
| raster digital data | Unknown | CSDGM IMPORT ERROR: No digtinfo/formcont | Open resource |