Model Development

We used the random forest classifier (Breiman 2001) implemented in Google Earth Engine (GEE) to fractional cover of sagebrush, shrubs, perennial grasses, and annual grasses from the covariates at all training data locations. We trained 10 replicate models in regression mode per variable in a k-fold approach (Fushiki 2011) with a unique 'fold' of 1/10th of the data withheld for validation. The final model was calculated as the average of the 10 replicates.

Last updated