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研究中，通过选择目标区的ＰＯＬＤＥＲ图象数据来估计目标的二向性反射分布函数，其主要结果可简述如下：１）我们发展了一种大气纠正算法，它适用于源自ＰＯＬＤＥＲ传感器的图象数据格式。通过这种算法，将连续的不同视角的ＰＯＬＤＥＲ陆地图象转化为一系列表面反照率图象，该过程考虑了多次散射。２）然后，选定２１个目标区，包括河流、水塘、城市、道路、森林等，其光谱二向性反射分布函数通过连续的反照率图象来估计。研究发现，水表面的二向性反射分布函数５５０ｎｍ，６５０ｎｍ，８５０ｎｍ处呈现朗伯体特征，同时发现有植被覆盖地表的二向性反射分布函数在５５０ｎｍ和６５０ｎｍ处大致为各向同性，而在８５０ｎｍ处则表现为各向异性。该文给出了所有靶区按经验二向性反射分布函数的拟合参数值。
In the study, the target’s bidirectional reflectance distribution function was estimated by selecting the POLDER image data of the target area. The main results can be summarized as follows: 1) We developed an atmospheric correction algorithm, which is suitable for POLDER sensor Image data format. Through this algorithm, continuous POLDER land images of different angles are converted into a series of surface albedo images, which considers multiple scattering. 2) Then 21 target areas, including rivers, reservoirs, cities, roads, forests, etc., are selected and their spectral bifocal reflectance distribution function is estimated by successive albedo images. It is found that the birefringence reflection distribution functions at water surface are Lambertian at 550nm, 650nm and 850nm. At the same time, it is found that the birefringence reflection distribution function at vegetation surface is roughly isotropic at 550nm and 650nm, 850nm at the performance of anisotropy. In this paper, we give the fitting parameters of all target regions according to empirical df distribution function.