Dataset for "Exploring and overcoming the effects of spatial non-stationarity on mapping forest aboveground biomass"

This dataset contains two main components used in the study “Exploring and overcoming the effects of spatial non-stationarity on mapping forest aboveground biomass in large scale by using geographically random forests”.

(1) Field-sampled aboveground biomass (AGB) data, collected through forest inventory plots, serve as the ground truth for model training and validation.

(2) Spatial predictions of AGB generated by the Geographically Random Forest (GRF) model, which account for spatial non-stationarity in biomass distribution.

Due to file size limitations, prediction results and intermediate data from other models (e.g., Random Forest, GTB, Support Vector Machine) are not included in this archive.