English  |  正體中文  |  简体中文  |  Items with full text/Total items : 26999/38800
Visitors : 2401412      Online Users : 64
RC Version 4.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Adv. Search
LoginUploadHelpAboutAdminister

Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/11043

Title: 應用合成孔徑雷達與電波散射理論於土壤含水量之反演
Inversion of the Soil Moisture by Means of Synthetic Aperature Radar Image and Microwave Scattering Model
Authors: 吳宗達
Contributors: NTOU:Department of Electrical Engineering
國立臺灣海洋大學:電機工程學系
Date: 2008
Issue Date: 2011-06-28T08:08:15Z
Abstract: 由於地表的表面幾何與土壤介電性質決定了雷達電磁波的散射與反射機制,因此合 成孔徑雷達影像所能提供的資訊包含了被觀測地表的形態以及土壤的材質。而使用合成 孔徑雷達獲得地表物理特性的技術,在許多地球科學與環境議題的領域中也就有越來越 多的應用。其中一項近年來需求頻繁的應用即是土壤含水量的反演,尤其是在大區域範 圍的地質遙測應用中這項需求越顯得重要。以往的研究大都是基於經驗模式、半經驗模 式、以及影像差異法來獲取土壤含水量,較少有針對物理性的電磁波散射理論模式來實 踐反演,最主要的原因是理論模式的數學往往複雜而不易推導與計算。本計劃將發展出 基於電磁波散射理論模式下的土壤含水量自動化反演與分析系統,並將於未來應用在台 灣的合成孔徑雷達影像上,反演並分析特定區域土壤的含水量。 本計劃首先是要以嚴謹的數學方法,將土壤含水量反演的問題架構於電磁波分析模 式上。而我們所採用的理論分析模式(積分方程模式)即是用來將電磁波在地表散射的機 制模式化。而在反演的問題上除了使用查詢表之外,我們將使用一些正規的反演演算 法,如the Tikhonov-Phillips Method, The Truncated Singular Value Decomposition, Iterative Methods, Regularization by Discretization, and Maximum Entropy 等等方法。土壤含水量反 演的成果將可用來產生各影像點的介電常數,進而得到SAR 影像的土壤含水量的分佈。 因此本計劃將可發展出架構在理論模式上,專為土壤含水量反演與分析的SAR 影像處 理軟體,而且具備有去雜訊以及含水量分佈切割等影像處理技術能力。 在儘量降低計算時間且保有高度正確性的情況下,本系統預期將可成為改善SAR 影像解讀的重要工具,並且可用來重建地表土壤含水量的特徵。在整合遙測資料與現場 量測資料之後,我們將致力於確認並降低本系統預測值與現場實際量測值之間的誤差。
Synthetic Aperture Radar (SAR) images contain information about morphology and ground conductivity of the observed terrain since the geometric and dielectric properties of the surface influence the reflection or backscattering of the emitted electromagnetic wave. The ability of SAR techniques to obtain information about physical properties of the surface has led to many innovative applications in geoscientific research and concerning environmental issues. One of these applications in greatly demand recently is the inversion of the soil moisture, which has been very important for the application of remote sensing to geology, particularly over large areas. Previous studies were commonly based on empirical, semiempirical, and image difference techniques for soil moisture inversion. There has been less research carried out from physical and theoretical EM scattering models because of complex mathematics manipulation and calculation. In this project, an automatic soil moisture inversion and analysis system based on the electromagnetic scattering model will be developed and applied to the soil moisture contents analyses of the SAR images acquired in Taiwan. One of the scopes of this project is to formulate and solve, in mathematically rigorous manner, the inverse problem of the soil moisture based on an analytical EM model, the Integral Equation Model, which is chosen for the modeling of the surface scattering mechanism. Instead of look up table method, we summarize some common regularization methods for resolving the inverse problems, including the Tikhonov-Phillips Method, The Truncated Singular Value Decomposition, Iterative Methods, Regularization by Discretization, and Maximum Entropy. The results can be used to produce maps detailing the values of the dielectric constant index within the imaged sample and develop algorithms to obtain the soil contents distribution in the SAR image. The contribution to the radar signal from multiple scattering effects is also essentially taken into account for understanding and in turn optimization of the inversion system. Based on the developing theoretical model, a sophisticated image processing software dedicated to the proposed soil moisture inversion and analysis system will be developed, where the image processing techniques for noise removal and segmentation of moisture distribution are included. By decreasing computation time while preserving high accuracy this system is anticipated to serve as important tools for improving interpretation of SAR technologies, moreover, for reconstructing moisture characteristics of soil surface from SAR images. With the integration of the remote-sensing data and field observations, we will try to validate the prediction from our developed system with field works.
URI: http://ntour.ntou.edu.tw/ir/handle/987654321/11043
Appears in Collections:[電機工程學系] 研究計畫

Files in This Item:

There are no files associated with this item.



All items in NTOUR are protected by copyright, with all rights reserved.

 


著作權政策宣告: 本網站之內容為國立臺灣海洋大學所收錄之機構典藏,無償提供學術研究與公眾教育等公益性使用,請合理使用本網站之內容,以尊重著作權人之權益。
網站維護: 海大圖資處 圖書系統組
DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback