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中国科学院地质与地球物理研究所第十届(2.10年度)学术年会

作者： yanfei wang institute of geology and geophysics,chinese academy of sciences,{2.,china. {4. li research center for remote Sensing and GIS,beijing normal university,beijing,100875,{12.

To estimate structural parameters and spectral component signatures of Earth surface cover type,quantitative remote sensing seems to be an appropriate way to deal with these *** the real physical system that couples the atmosphere with the land surface is very complicated and should be continuous,sometimes it requires comprehensive parameters to describe such a system,so any practical physical model can only be approximated by a model which includes only a limited number of the most important parameters that capture the major variation of the real system. The pivot problem for quantitative remote sensing is the *** problems are typically *** ill-posed nature is characterized by(C1) the solution may not exist;(C{4. the dimension of the solution space may be infinite;(C3) the solution is not continuous with the variation of the observed *** issues exist for all quantitative remote sensing inverse problems. For example,when sampling is poor,i.e.,there are very few observations,or directions are poorly located,the inversion process would be underdetermined, which leads to the large condition number of the normalized systems and the significant noise ***(C{4. and(C3) would be the chief difficulties for quantitative remote sensing inversion. This chapter will address the theory and methods from the viewpoint that the quantitative remote sensing inverse problems can be represented by kernel-based operator equations.

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Regularizing kernel-based BRDF model inversion method for ill-posed land surface parameter retrieval using smoothness constraint

Regularizing kernel-based BRDF model inversion method for il...

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中国科学院地质与地球物理研究所2.08学术年会

作者： yanfei wang,Changchun Yang,and {2. li 1 {4. of geology and geophysics,chinese academy of sciences, beijing,china. 2.State Key Laboratory of remote Sensing Science and research {12. for remote Sensing and GIS,beijing normal university,beijing,china.

[1]In this paper,we consider the problem how to solve the kernel-based bidirectional reflectance distribution function(BRDF) models for the retrieval of land surface albedos. The above problem is an ill-posed inverse *** will employ a new regularization technique to alleviate the *** Tikhonov regularization has been discussed for BRDF model inversion,however,much study has to be done before applying it in practice(wang et al,2.07).In this paper,we thoroughly investigate this method,and propose a discrepancy method for a posteriori choice of the regularization parameter and several options for choosing the regularizing *** proposed method can alleviate difficulties in numerical computation when the discrete kernel is badly conditioned and the number of observations is *** the proposed method can always find a set of suitable BRDF coefficients for poorly sampled *** proposed method is an improvement of the traditional least squares error algorithm in AMBRALS(Algorithm for MODIS(Moderate Resolution Imaging Spectroradiometer) Bidirectional Reflectance Anisotropies of the Land Surface),see Strahler et al.(1999),and is comparable to the regularized singular value decomposition method developed by wang et al.(2.07).Hence the proposed method can be considered as a supplemental algorithm for the robust estimation of the land surface BRDF/*** performance is given in this paper for the widely used field-based 18 data sets among the 73 data sets(see {2. et al.,2.01) and for the satel{2.te data.

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

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Science china.Earth sciences 2009年第4期52卷 540-549页

作者： wang yanfei MA ShiQian YANG Hua wang JinDi li {4. Key Laboratory of Petroleum geophysics Institute of Geology and GeophysicsChinese Academy of SciencesBeijing 100029China State Key Laboratory of remote Sensing Science Jointly Sponsored by Beijing Normal University and the Institute of Remote Sensing Applications of Chinese Academy of SciencesBeijing 100875China Department of Industrial Engineering and Operations research Columbia UniversityNew YorkNY 10027-6902USA

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

关键词： ill-posed problems land surface parameter retrieval optimization regularization

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四川省泸定县Ms6.8级地震地质灾害发育规律与减灾对策

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水文地质工程地质 2022年第6期49卷 1-12页

作者：铁永波张宪政卢佳燕梁京涛王东辉马志刚李宗亮鲁拓石胜伟刘民生巴仁基何龙江张新克甘伟陈凯高延超白永健龚凌枫曾孝文徐伟中国地质调查局成都地质调查中心四川成都610081 中国地质大学(北京)工程技术学院北京100083 四川省地质调查院四川成都610084 四川省国土空间生态修复与地质灾害防治研究院四川成都610084 中国地质科学院探矿工艺研究所四川成都610031 应用地质研究中心四川成都610036

2.2.年9月5日四川省泸定县发生Ms6.8级地震,诱发大量次生地质灾害。为深入认识此次地震地质灾害发育分布规律及特征,分析地质灾害发展趋势及潜在风险,文章基于现场调查获取的一手资料,结合震区首轮地质灾害排查成果、遥感解译和区域地... 详细信息

2.2.年9月5日四川省泸定县发生Ms6.8级地震,诱发大量次生地质灾害。为深入认识此次地震地质灾害发育分布规律及特征,分析地质灾害发展趋势及潜在风险,文章基于现场调查获取的一手资料,结合震区首轮地质灾害排查成果、遥感解译和区域地质背景综合研究,对地震地质灾害的特征、控灾条件及防灾减灾对策进行了研究。结果表明:截至2.2.年9月14.2.时,地震重灾区泸定县和石棉县境内,地震共诱发有威胁对象的地质灾害隐患点565处(包括崩塌331处、滑坡2.4.),导致81处已有地质灾害隐患点加剧变形;地震诱发的地质灾害类型主要以中、小型群发性高位崩塌和滑坡为主,主要集中分布在震中附近地震烈度Ⅸ度区域,包括泸定县磨西镇、得妥乡、得妥乡—德威镇段大渡河两岸及石棉县草科乡、王岗坪乡;根据汶川地震经验,认为位于地震烈度Ⅸ度区内的湾东河等流域,在未来5 a内泥石流将处于活跃期,泥石流防治工程设计需考虑其高频率、黏性泥石流等特征;得妥乡—德威镇段大渡河两岸残留在坡面的崩滑体在降雨作用下易转化成坡面泥石流,建议在防治工程设计时要充分考虑2.灾害类型的转化形式。研究可为震区地震地质灾害防范及灾后重建规划提供科学参考。

关键词：泸定县Ms6.8级地震地震地质灾害控灾条件演化趋势减灾对策

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