利用遥感信息准确估算植被生物物理化学参数是植被遥感的重要研究内容。遥感传感器获得的信号中通常会包含植物叶片及冠层所产生的镜面反射信息。这会影响遥感信息估算植被生物物理化学参数的精度。因此，如何有效剥离镜面反射是解决这一问题的关键。由于镜面反射是产生多角度及偏振信息的关键因素，项目拟基于不同植物叶片与冠层的多角度偏振反射特性，阐明多角度偏振信息与镜面反射之间的关系；随后，利用偏振反射系数与菲涅尔偏振反射系数的关系、多角度反射光学模型以及双向反射系数的累积频率方法，实现对植物叶片与冠层镜面反射的分离，创建基于漫反射信息的植被光谱指数，并且评价其在植被生物物理化学参数估算中的有效性和精度；最终建立可以提升估算植被生物物理化学参数的模型。项目不仅发挥了多角度偏振信息的作用，而且使得光学遥感技术在植被物理及生化参数监测、以及与植被相关的生态系统过程研究中发挥更大的作用，进而促进植被遥感技术的发展。

Estimating biophysical and biochemical parameters of vegetation accurately during the process of plants growth is one of the important issues in the field of vegetation remote sensing. The signals obtained by remote sensors usually contain specular reflection information from plant leaves and canopies. This will affect the accuracy of remotely estimating the biophysical and biochemical parameters of vegetation. Therefore, how to effectively remove specular reflection is the key to solve this problem. Since specular reflection is a key factor in generating polarization information, we will clarify the relationship between multi-angle polarization information and specular reflection, based on the multi-angle polarization reflection characteristics of different plant leaves or canopies; subsequently, the specular reflection will be separated from the total reflection of leaves or canopies, using the relationship between the polarization reflection coefficient and the Fresnel polarization reflection coefficient, the photometric model of multi-angle reflection, and the cumulative frequency of the bidirectional reflection coefficient; then, the spectral index solely based on diffuse reflection will be developed and validated in estimating the biophysical and biochemical parameters of vegetation; finally, the model that can improve the estimation of biophysical and biochemical parameters of vegetation will be established. This project will make optical remote sensing technology play a greater role in the monitoring of biophysical and biochemical parameters of vegetation, as well as the ecosystem process related to vegetation, and promote the development of vegetation remote sensing technology by taking advantage of multi-angle polarization information.