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Titlebook: Sensitivity Analysis in Remote Sensing; Eugene A. Ustinov Book 2015 The Author(s) 2015 Adjoint Partial Differential Equations and Sensitiv

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发表于 2025-3-21 16:23:39 | 显示全部楼层 |阅读模式
书目名称Sensitivity Analysis in Remote Sensing
编辑Eugene A. Ustinov
视频video
概述Includes supplementary material:
丛书名称SpringerBriefs in Earth Sciences
图书封面Titlebook: Sensitivity Analysis in Remote Sensing;  Eugene A. Ustinov Book 2015 The Author(s) 2015 Adjoint Partial Differential Equations and Sensitiv
描述.This book contains a detailed presentation of general principles of sensitivity analysis as well as their applications to sample cases of remote sensing experiments. An emphasis is made on applications of adjoint problems, because they are more efficient in many practical cases, although their formulation may seem counterintuitive to a beginner. Special attention is paid to forward problems based on higher-order partial differential equations, where a novel matrix operator approach to formulation of corresponding adjoint problems is presented..Sensitivity analysis (SA) serves for quantitative models of physical objects the same purpose, as differential calculus does for functions. SA provides derivatives of model output parameters (observables) with respect to input parameters. In remote sensing SA provides computer-efficient means to compute the jacobians, matrices of partial derivatives of observables with respect to the geophysical parameters of interest. The jacobians areused to solve corresponding inverse problems of remote sensing. They also play an important role already while designing the remote sensing experiment, where they are used to estimate the retrieval uncertainti
出版日期Book 2015
关键词Adjoint Partial Differential Equations and Sensitivity Analysis; Adjoint Problems and Sensitivity Ana
版次1
doihttps://doi.org/10.1007/978-3-319-15841-9
isbn_softcover978-3-319-15840-2
isbn_ebook978-3-319-15841-9Series ISSN 2191-5369 Series E-ISSN 2191-5377
issn_series 2191-5369
copyrightThe Author(s) 2015
The information of publication is updating

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发表于 2025-3-21 20:21:51 | 显示全部楼层
Sensitivity Analysis of Analytic Models: Applications of Differential and Variational Calculus, In this chapter we consider the sensitivity analysis of analytic models. For demonstration purposes, we first consider two simple demo models. Then a realistic model will be considered, which is actually used in practice of remote sensing of the Earth and planetary atmospheres.
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Book 2015ing experiments. An emphasis is made on applications of adjoint problems, because they are more efficient in many practical cases, although their formulation may seem counterintuitive to a beginner. Special attention is paid to forward problems based on higher-order partial differential equations, w
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2191-5369 applications to sample cases of remote sensing experiments. An emphasis is made on applications of adjoint problems, because they are more efficient in many practical cases, although their formulation may seem counterintuitive to a beginner. Special attention is paid to forward problems based on hig
发表于 2025-3-22 20:36:15 | 显示全部楼层
Introduction: Remote Sensing and Sensitivity Analysis,nterest directly, but we can measure some other quantities that are related to quantities of interest by some known relations. For example, targeted measurements of spectral radiances on top of the atmosphere in the thermal infrared spectral region provide a capability to measure atmospheric profile
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Three Approaches to Sensitivity Analysis of Models,uns of the forward model according to the number of model input parameters. Although this approach uses the forward model without any modifications and does not require any analytic work, its application results in a very computer-intensive algorithm, which may become a prohibitive factor in practic
发表于 2025-3-23 08:22:04 | 显示全部楼层
Sensitivity Analysis of Analytic Models: Applications of Differential and Variational Calculus,nes. Nevertheless, in some practical cases corresponding forward problems can be solved analytically, and resulting models become analytical. In such cases, sensitivities to discrete and continuous input parameters can be found using the conventional methods of differential and variational calculus.
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