摘要
MODIS的反照率和二向反射产品由基于核驱动模型的AMBRALS程序提供。目前AMBRALS算法系统中所用的描述几何光学散射的核为LiSparseR核。新提出的一个几何光学核—LiTransit核兼有LiSparse核向LiDense核过渡的优点 ,比LiSparseR核更符合几何光学模型的基本原理。验证结果表明 :与LiSparseR核比较 ,RossThick—LiTransit的核组合更能反映直入扇出反照率随太阳天顶角变化的趋势。因此在下一代的AM BRALS算法系统中 ,将用新的LiTransit核取代LiSparseR核。目前AMBRALS算法系统为了快速处理每天大量的数据 ,用多项式拟合核的半球积分。因此 ,为了替换LiSparseR核 ,同时又不影响整个算法的系统性 ,本文研究了LiTransit核的多项式拟合。结果表明 :拟合的多项式与核半球积分的相关性很好。
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.
出处
《遥感学报》
EI
CSCD
北大核心
2002年第4期246-251,共6页
NATIONAL REMOTE SENSING BULLETIN
基金
国家重点基础研究发展规划项目(G20000779)
国家自然科学基金项目(40171068)。