XIE Dong-hui1, WANG Pei-juan2, ZHU Qi-jiang1, ZHOU Hong-min1
1. State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Beijing Normal University and the Institute of Remote Sensing Applications, Chinese Academy of Sciences, Beijing Key Laboratory for Remote Sensing of Environment and Digital Cities, Beijing Normal University, School of Geography and Remote Sensing Science, Beijing Normal University, Beijing 100875, China 2. Chinese Academy of Meteorological Sciences 100081, China
摘要： 利用长春光机所研制的多角度观测装置测量了玉米嫩叶、玉米成熟叶和一品红叶表面的二向偏振反射率分布，发现叶片表面反射具有明显的非朗伯性。通过借鉴Cook-Torrance光照模型的形式，将不同偏振态的菲涅尔因子耦合到模型中，推导得到用于叶片表面偏振的二向性反射分布函数模型(pBRDF-polarimetric bidirectional reflectance distribution function)。将建立的pBRDF模型与实测数据拟合，利用遗传算法进行参数反演，获得叶片漫反射率、等效折射率和表面粗糙度。通过实测值和模拟值的比较，发现该pBRDF模型可以用于叶片表面方向偏振反射特性的模拟。同时，该模型还有助于对植物叶片生理生态特性的定量分析。
关键词：叶片;二向性反射分布函数;偏振;玉米;表面粗糙度
Abstract：The purpose of the present paper is to model a physical polarimetric bidirectional reflectance distribution function (pBRDF), which can character not only the non-Lambertian but also the polarized features in order that the pBRDF can be applied to analyze the relationship between the degree of polarization and the physiological and biochemical parameters of leaves quantitatively later. Firstly, the bidirectional polarized reflectance distributions from several leaves surfaces were measured by the polarized goniometer developed by Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences. The samples of leaves include two pieces of zea mays L. leaves (young leaf and mature leaf) and a piece of E. palcherrima wild leaf. Non-Lambertian characteristics of directional reflectance from the surfaces of these three leaves are obvious. A Cook-Torrance model was modified by coupling the polarized Fresnel equations to simulate the bidirectional polarized reflectance properties of leaves surfaces. The three parameters in the modified pBRDF model, such as diffuse reflectivity, refractive index and roughness of leaf surface were inversed with genetic algorithm (GA). It was found that the pBRDF model can fit with the measured data well. In addition, these parameters in the model are related with both the physiological and biochemical properties and the polarized characteristics of leaves, therefore it is possible to build the relationships between them later.
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