On the effective inversion by imposing a priori information for retrieval of land surface parameters

doi:10.1007/s11430-009-0036-9

	On the effective inversion by imposing a priori information for retrieval of land surface parameters
	Wang YanFei 1; Ma ShiQian 4; Yang Hua 2,3; Wang JinDi 2,3; Li XiaoWen 2,3
刊名	SCIENCE IN CHINA SERIES D-EARTH SCIENCES
	2009-04-01
卷号	52 期号:4 页码:540-549
关键词	ill-posed problems land surface parameter retrieval optimization regularization
ISSN号	1006-9313
DOI	10.1007/s11430-009-0036-9
文献子类	Article
英文摘要	The anisotropy of the land surface can be best described by the bidirectional reflectance distribution function (BRDF). As the field of multiangular remote sensing advances, it is increasingly probable that BRDF models can be inverted to estimate the important biological or climatological parameters of the earth surface such as leaf area index and albedo. The state-of-the-art of BRDF is the use of the linear kernel-driven models, mathematically described as the linear combination of the isotropic kernel, volume scattering kernel and geometric optics kernel. The computational stability is characterized by the algebraic operator spectrum of the kernel-matrix and the observation errors. Therefore, the retrieval of the model coefficients is of great importance for computation of the land surface albedos. We first consider the smoothing solution method of the kernel-driven BRDF models for retrieval of land surface albedos. This is known as an ill-posed inverse problem. The ill-posedness arises from that the linear kernel driven BRDF model is usually underdetermined if there are too few looks or poor directional ranges, or the observations are highly dependent. For example, a single angular observation may lead to an under-determined system whose solution is infinite (the null space of the kernel operator contains nonzero vectors) or no solution (the rank of the coefficient matrix is not equal to the augmented matrix). Therefore, some smoothing or regularization technique should be applied to suppress the ill-posedness. So far, least squares error methods with a priori knowledge, QR decomposition method for inversion of the BRDF model and regularization theories for ill-posed inversion were developed. In this paper, we emphasize on imposing a priori information in different spaces. We first propose a general a priori imposed regularization model problem, and then address two forms of regularization scheme. The first one is a regularized singular value decomposition method, and then we propose a retrieval method in I (1) space. We show that the proposed method is suitable for solving land surface parameter retrieval problem if the sampling data are poor. Numerical experiments are also given to show the efficiency of the proposed methods.
WOS关键词	BRDF MODEL INVERSION ; BIDIRECTIONAL REFLECTANCE ; REMOTE ; KNOWLEDGE
WOS研究方向	Geology
语种	英语
出版者	SCIENCE PRESS
WOS记录号	WOS:000265046100012
内容类型	期刊论文
源URL	[http://ir.iggcas.ac.cn/handle/132A11/71822]
专题	中国科学院地质与地球物理研究所
通讯作者	Wang YanFei
作者单位	1.Chinese Acad Sci, Inst Geol & Geophys, Key Lab Petr Geophys, Beijing 100029, Peoples R China 2.Beijing Normal Univ, State Key Lab Remote Sensing Sci, Beijing 100875, Peoples R China 3.Chinese Acad Sci, Inst Remote Sensing Applicat, Beijing 100875, Peoples R China 4.Columbia Univ, Dept Ind Engn & Operat Res, New York, NY 10027 USA
推荐引用方式 GB/T 7714	Wang YanFei,Ma ShiQian,Yang Hua,et al. On the effective inversion by imposing a priori information for retrieval of land surface parameters[J]. SCIENCE IN CHINA SERIES D-EARTH SCIENCES,2009,52(4):540-549.
APA	Wang YanFei,Ma ShiQian,Yang Hua,Wang JinDi,&Li XiaoWen.(2009).On the effective inversion by imposing a priori information for retrieval of land surface parameters.SCIENCE IN CHINA SERIES D-EARTH SCIENCES,52(4),540-549.
MLA	Wang YanFei,et al."On the effective inversion by imposing a priori information for retrieval of land surface parameters".SCIENCE IN CHINA SERIES D-EARTH SCIENCES 52.4(2009):540-549.