Simulation studies on data fusion algorithms for forest structure from lidar and SAR data

The NASA´s DESDynI mission will provide global systematic lidar point-sampling data and areal coverage of L-band SAR data with polarimetric capabilities for 3-D structural studies of vegetation. The combined use of lidar´s direct sampling measurements and radar´s global areal mapping capabilities creates a real opportunity to map global ecosystem structures and functions that link to carbon dynamics. However, the relationship of the lidar point-sample data and corresponding areal SAR data is yet to be established. In this study the data fusion algorithms for the estimation of parameters of forest structure from Lidar and SAR Data is investigated. The results show that SAR intensity data is sensitive to forest biomass which is less than 15kg/m² (or 150 ton/ha) and insensitive to the maximum forest height. Lidar data can be used to provide the information of forest height and the introduction of the information of forest height is helpful in the estimation of forest biomass.