In order to minimize uncertainty of the inversed parameters to the largest extent by making full use of the limited information in remote sensing data, it is necessary to understand what the information flow in quantitative remote sensing model inversion is, thus control the information flow. Aiming at this, the paper takes the linear kernel-driven model inversion as an example. At first, the information flow in different inversion methods is calculated and analyzed, then the effect of information flow controlled by multi-stage inversion strategy is studied, finally, an information matrix based on USM is defined to control information flow in inversion. It shows that using Shannon entropy decrease of the inversed parameters can express information flow more properly. Changing the weight of a priori knowledge in inversion or fixing parameters and partitioning datasets in multi-stage inversion strategy can control information flow. In regularization inversion of remote sensing, information matrix based on USM may be a better tool for quantitatively controlling information flow.
YANG Hua, XU Wangli, ZHAO Hongrui, CHEN Xue & WANG Jindi Research Center for Remote Sensing and GIS, School of Geography, Beijing Normal University, State Key Laboratory of Remote Sensing Science, Beijing Key Laboratory for Remote Sensing of Environment and Digital Cities, Beijing 100875, China
互易原理是电磁学、光学的常用原理之一,是辐射传输理论的基石.当这一理论被用到遥感研究中,相当多的测量数据,尤其是野外测量数据不支持互易原理在传感器像元尺度上的有效性,因而,互易原理被当作检验遥感数据质量标准时,受到测量界的强烈反对.李小文等用几何光学模型证明了互易原理的尺度效应(Progress in Natural Science,1998,8(3):354～358).Snyder对李等的证明提出质疑(Applied Optics,2002,41(21):4307～4313),并试图证明互易原理在遥感中适用的无条件性,文中对Snyder的质疑进行了考察,指出,由于作者忽略了李小文等证明二向反射(BRDF)互易原理尺度效应的重要条件,并不能证明互易原理是无条件适用于遥感目标的研究尺度的,并再度证明,BRDF互易原理存在尺度效应.
