Modeling radar backscattering of complex terrain at the landscape scale for retrieving forest structure parameters

The forest aboveground biomass and its dynamics are essential for researches of carbon cycling. The estimation of forest aboveground biomass is an important topic in the application of remote sensing. However, the estimation accuracy is limited by the lack of forest structures. Recent progresses over the past decade in the estimation of forest biomass from remote sensing data was mainly due to the success in the extraction of related forest structure parameters[1]. For example, LiDAR data is widely used in the estimation of forest biomass at local scales because it can directly measure the vertical structure of forests [2, 3]. Polarimetric Interferometric SAR (PolInSAR) is a another promising technique for the estimation of forest height and biomass which employs the dependence of penetration depth of SAR on polarization [4]. However, spaceborne LiDAR system cannot acquire wall-to-wall data because it mainly worked by point sampling while airborne LiDAR system only worked on at local scaled due to its cost. The P-band PolInSAR system onboard European BIOMASS satellite which is suitable for retrieval of forest biomass is still under construction and scheduled to be launched around 2020 by European space agency (ESA).