Analysis of the Kernel-Driven Brdf Model Over Rugged Terrains

Land-surface bidirectional reflectance distribution function (BRDF) models are used for the description of surface bidirectional effects and the estimation of surface albedo. The semi-empirical linear kernel-driven BRDF model is one of them which has been adopted by the moderate resolution imaging spectroradiometer (MODIS) operational BRDF/Albedo algorithm, due to its briefness and well-fitting ability. However, this model does not consider the topography factors, and will lead to errors over rugged terrains. However, researches seldom analyze the models' uncertainties caused by rugged terrains quantitatively, as it is difficult to directly validate models over mountain areas at coarse resolution. This letter proposes a forward topographic BRDF simulation method by combining a canopy radiative transfer model (SAILH) and a mountain radiative transfer (MRT) model to investigate the uncertainty and sensitivity of the kernel-driven model over mountain areas theoretically. Results show that the topographic effects can cause over 20% uncertainties on both red and NIR bands. Topography leads to the asymmetry of BRDF distributions on azimuth, which cannot be captured by kernel-driven model at 1km scale. Both DEM types and observation situations influence the retrieval accuracy significantly. Therefore, this work is meaningful to study the optimal inversion scale and observation requirements depending on the topography.