Model Development

We used the random forest classifier (Breiman 2001) implemented in Google Earth Engine (GEE) to predict tree height (m), tree diameter (cm), and canopy cover (%) 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.