PROSAIL冠层光谱模型遥感反演区域叶面积指数

大面积区域作物叶面积指数遥感反演，对指导作物管理具有非常重要的意义，验证和发展基于物理叶面积指数遥感反演可避免基于经验模型的缺点。以北京地区青云店、魏善庄和高丽营为研究区，采用MODIS和ASTER两类不同空间分辨率遥感数据，探讨PROSAIL物理模型反演冬小麦叶面积指数的可行性，尤其在不同空间分辨率遥感数据上的稳定性，并与经验模型进行了对比分析。 与经验模型相比，物理模型模拟LAI值更具真实性;用线性组分加权的方法，对小尺度物理模型反演LAI进行尺度扩展并与基于大尺度遥感数据的LAI物理反演结果相对比，相差不大，说明LAI物理反演方法在空间尺度上的稳定性。

Estimation of Regional Leaf Area Index by Remote Sensing Inversion of PROSAIL Canopy Spectral Model

The present paper selected Qingyundian town and Weishanzhuang town in DaXing District, and C, aolingying town in Shunyi District as test areas, using MODIS data and ASTER data in different scales. The feasibility of winter wheat LAI inversion by PROSAIL physical model, especially the stability of remote sensing data in different scales, was discussed, and the results from experience model inversion were compared with that from statistical methods. The values of all samples LAI inversion from experience model are close in a region, which means experience model is a reflection of general growing trend, ignoring spatial heterogeneity of the regional leaf area index. But the value of LAI inversion from physical model can be truer in reflecting spatial heterogeneity of the regional leaf area index. The value of LAI inversion from physical model is more real, compared with experience model. With the method of linear weighing, the scale conversion was accomplished, and the LAI inversion results from different remote sensing scale data were compared, and were found similar. The result shows that in the process of largescale regional LAI inversion, physical model inversion is more valid.