An Algorithm for the Retrieval of Albedo from Space Using New GO Kernel-Driven BRDF Model
新几何光学核驱动BRDF模型反演地表反照率的算法

Multi angular remote sensing supplies reflectance of land surface in different directions. To simulate the relationship between bi directional reflectance distribution ( BRDF ) and structure of land surface and optical characteristic of objects,more models were developed. Because they are simple,rapid,grasp the main factors affecting BRDF and have some physical meaning,semi empirical models,especially,kernel driven models are applied broadly in data processing in batches. Thus,kernel driven BRDF model was the core of the AMBRALS,an algorithm for MODIS land surface BRDF and albedo products. In the onboard version of AMBRALS,the LiSparseR Gometrical Optical (GO) kernel was used. But a new derived kernel LiTransit kernel is also good at transition from LiSparse kernel to LiDense kernel when zenith angle is large,and accords more to the basic principle of GO model than LiSparseR kernel. Results of validation show:RossThick LiTransit kernels combination has more stability when extrapolated to large zenith angles with LiSparseR kernel. Therefore,we will use the Litransit kernel instead of LiSparseR kernel in the new version of AMBRALS. We introduce the algorithm based on this new kernel in this paper,including the kernel driven model and its inversion,albedo retrieval based on BRDF model,broad band albedo retrieval and realization of this algorithm. The speed requirement of tremendous data processing can't be met easily,such as MODIS data. Although we can calculate the integration of the kernel beforehand,store up and acquire through look up table method during retrieving albedo,it's inconvenient for an integrated data processing system. Thus we need to get the simple form of the integration of the kernels. Because the integrations of the kernels are approxinately independent on directions than BRDF ,it's sufficient to use a polynome dependent on the solar zenith angle to regress the integration of kernel. In this paper, we study the polynome regression of LiTransit kernel to instead LiSparseR, but not affect the systematic of the algorithm at the same time. Comparing the numerical integration of the kernel and the polynome regression result show the relationship is very well,the polynome can be used in the algorithm directly.