China typical forest aboveground biomass estimation by fusion of multi-platform data

摘要

China has a wide variety of forest types. It is challenging to make a reliable estimation of these forest aboveground biomass (AGB) using geo-spatial technologies. We developed a Field-Airborne-Spaceborne (FAS) comprehensive observation method for AGB estimation. According to forest ecological zones of China, we carried out three FAS campaigns in the Northeast, central, and Southwest of China. Airborne LiDAR data were collected along National Forest Inventory (NFI) plots. Then the airborne LiDAR data were used to estimate AGB after been trained by NFI plots. Then these LiDAR estimated AGB were used to train satellite data for large area biomass mapping. The stratified regression tree modeling method was used in this research. The overall estimation correlation coefficient are better than 0.8.