Land Cover Classification (5-meter) - Kings River Fisher Project 2014 - 2018

These high resolution (5x5-meter pixel) categorical models of land cover were created by training random forest classification models on RapidEye (Planet Labs Inc.) satellite spectral data for each year and then predicting those models across the landscape. Training data were created by visually interpreting random plots over high resolution NAIP aerial imagery. Land cover classes include bare ground, live forest, shrub, herbaceous, and tree mortality. Class definitions generally follow California Wildlife Habitat Relationships (CWHR) categories. CWHR tree dominated habitats were combined to represent a single “live forest” category where trees were alive and “tree mortality” where dead. Shrub dominated habitats, namely Mixed and Montane Chaparral, were included in the “shrub” class. Perennial grasslands and wet meadow habitats were included in the “herbaceous” class, and non-vegetated habitats along with annual grasslands made up the “bare ground” class. We interpreted 75-125 samples per land cover class, per year. Model accuracy was evaluated using a 30% holdout of training data per class. A set of conditional rules were applied to the predictions to limit the occurrence of illogical land cover transitions through time (e.g., bare ground to tree mortality).