Forest structure estimation using SAR, LiDAR, and optical data in the Canadian Boreal forest

One of the most fundamental new technical challenges of a DES Dynl space-borne mission is the fusion of the several sensor modalities LiDAR, SAR, InSAR, and Optical in order to accurately estimate desired 3D vegetation structures and biomass parameters in areas where the sensors overlap, and to extrapolate them over continuous areas where lidar data is absent. The objective of this paper is to use measured datasets in con junction with our sensor forward models to develop and validate an estimation algorithm that fuses various remote sensing technologies with a minimal amount of ground information and yields an accurate estimate of forest structure, including biomass, canopy height, and tree species.