Application of Improved Change-Vector Analysis for Land Cover Change Detecton
碩士 === 國立中央大學 === 土木工程研究所 === 92 === Traditionally, when Change-vector analysis (CVA) was applied to detect land cover change, the threshold of change magnitude was always determined according to empirical strategies, or from manual trial-and-error procedure. It made the result of change detection s...
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ndltd-TW-092NCU050150692015-10-13T13:04:42Z http://ndltd.ncl.edu.tw/handle/83397190716729696006 Application of Improved Change-Vector Analysis for Land Cover Change Detecton 改良式變異向量分析法於變遷偵測之探討 Wei-Jeng Hsu 徐維政 碩士 國立中央大學 土木工程研究所 92 Traditionally, when Change-vector analysis (CVA) was applied to detect land cover change, the threshold of change magnitude was always determined according to empirical strategies, or from manual trial-and-error procedure. It made the result of change detection subjective. In this study, using improve Change-vector analysis to determine the threshold of the difference image automatically. The method consist of two stages, (1) prior training set, which aims at helping to determine the threshold of change magnitude, and using Pace Search method and third power polynomial fitting method find the threshold of change magnitude quickly, (2) getting the training areas from the first image and the second image severally to build up the look-up table of direction cosine of change vectors samples, then using the look-up table help to assign “from-to” type of change pixels. In this study , the improve Change-vector analysis was applied to the detection of one simulation image and two SPOT4 satellite images, overall accuracy of “change/no-change” detection was about 85%, and overall accuracy of “from-to” types of change detection is was 82%.The experimental results indicate that the improve CVA has good potential in land cover change detection. Chi-Farn Chen 陳繼藩 2004 學位論文 ; thesis 81 zh-TW |
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碩士 === 國立中央大學 === 土木工程研究所 === 92 === Traditionally, when Change-vector analysis (CVA) was applied to detect land cover change, the threshold of change magnitude was always determined according to empirical strategies, or from manual trial-and-error procedure. It made the result of change detection subjective. In this study, using improve Change-vector analysis to determine the threshold of the difference image automatically. The method consist of two stages, (1) prior training set, which aims at helping to determine the threshold of change magnitude, and using Pace Search method and third power polynomial fitting method find the threshold of change magnitude quickly, (2) getting the training areas from the first image and the second image severally to build up the look-up table of direction cosine of change vectors samples, then using the look-up table help to assign “from-to” type of change pixels. In this study , the improve Change-vector analysis was applied to the detection of one simulation image and two SPOT4 satellite images, overall accuracy of “change/no-change” detection was about 85%, and overall accuracy of “from-to” types of change detection is was 82%.The experimental results indicate that the improve CVA has good potential in land cover change detection.
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author2 |
Chi-Farn Chen |
author_facet |
Chi-Farn Chen Wei-Jeng Hsu 徐維政 |
author |
Wei-Jeng Hsu 徐維政 |
spellingShingle |
Wei-Jeng Hsu 徐維政 Application of Improved Change-Vector Analysis for Land Cover Change Detecton |
author_sort |
Wei-Jeng Hsu |
title |
Application of Improved Change-Vector Analysis for Land Cover Change Detecton |
title_short |
Application of Improved Change-Vector Analysis for Land Cover Change Detecton |
title_full |
Application of Improved Change-Vector Analysis for Land Cover Change Detecton |
title_fullStr |
Application of Improved Change-Vector Analysis for Land Cover Change Detecton |
title_full_unstemmed |
Application of Improved Change-Vector Analysis for Land Cover Change Detecton |
title_sort |
application of improved change-vector analysis for land cover change detecton |
publishDate |
2004 |
url |
http://ndltd.ncl.edu.tw/handle/83397190716729696006 |
work_keys_str_mv |
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