Multi-Temporal Aerial Images in Riverbed Change Detection

碩士 === 國立中興大學 === 土木工程學系所 === 102 === Due to climate and environmental changes in recent years, heavy rains or typhoons may produce changes in river environment, which is responsible for water supply and drainage tasks. However, a wide range of large-scale surveys of river changes often demand time-...

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Main Authors: Ju-Jung Ke, 柯如榕
Other Authors: Jung-Der Tsai
Format: Others
Language:zh-TW
Published: 2014
Online Access:http://ndltd.ncl.edu.tw/handle/27747598978719836881
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spelling ndltd-TW-102NCHU50150402016-11-06T04:19:32Z http://ndltd.ncl.edu.tw/handle/27747598978719836881 Multi-Temporal Aerial Images in Riverbed Change Detection 多時期航空影像於河床變遷分析之應用研究 Ju-Jung Ke 柯如榕 碩士 國立中興大學 土木工程學系所 102 Due to climate and environmental changes in recent years, heavy rains or typhoons may produce changes in river environment, which is responsible for water supply and drainage tasks. However, a wide range of large-scale surveys of river changes often demand time-consuming and laborious manual measurements on riverbed terrain for river management purposes. This study focuses on how to use the existing aerial photographs to provide information in a more convenient way to those who request. In this study, multi-temporal aerial images purchased from the Aerial Survey Office, Forestry Bureau, Council of Agriculture were used in the experiment. After geometric registration and preprocessing, the principal component analysis (PCA) was performed for transforming aerial images for use in unsupervised classification. The result was compared with the result from supervised classification of the original image. The Kappa test was applied to assess the accuracy of the two classification approaches. It was shown that the supervised classification method is better than unsupervised classification method for subsequent riverbed changes analysis. Riverbed change analysis using multi-temporal aerial images is capable to provide immediate large-scale information for those who need to master changes of rivers in some circumstances. Jung-Der Tsai 蔡榮得 2014 學位論文 ; thesis 57 zh-TW
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language zh-TW
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description 碩士 === 國立中興大學 === 土木工程學系所 === 102 === Due to climate and environmental changes in recent years, heavy rains or typhoons may produce changes in river environment, which is responsible for water supply and drainage tasks. However, a wide range of large-scale surveys of river changes often demand time-consuming and laborious manual measurements on riverbed terrain for river management purposes. This study focuses on how to use the existing aerial photographs to provide information in a more convenient way to those who request. In this study, multi-temporal aerial images purchased from the Aerial Survey Office, Forestry Bureau, Council of Agriculture were used in the experiment. After geometric registration and preprocessing, the principal component analysis (PCA) was performed for transforming aerial images for use in unsupervised classification. The result was compared with the result from supervised classification of the original image. The Kappa test was applied to assess the accuracy of the two classification approaches. It was shown that the supervised classification method is better than unsupervised classification method for subsequent riverbed changes analysis. Riverbed change analysis using multi-temporal aerial images is capable to provide immediate large-scale information for those who need to master changes of rivers in some circumstances.
author2 Jung-Der Tsai
author_facet Jung-Der Tsai
Ju-Jung Ke
柯如榕
author Ju-Jung Ke
柯如榕
spellingShingle Ju-Jung Ke
柯如榕
Multi-Temporal Aerial Images in Riverbed Change Detection
author_sort Ju-Jung Ke
title Multi-Temporal Aerial Images in Riverbed Change Detection
title_short Multi-Temporal Aerial Images in Riverbed Change Detection
title_full Multi-Temporal Aerial Images in Riverbed Change Detection
title_fullStr Multi-Temporal Aerial Images in Riverbed Change Detection
title_full_unstemmed Multi-Temporal Aerial Images in Riverbed Change Detection
title_sort multi-temporal aerial images in riverbed change detection
publishDate 2014
url http://ndltd.ncl.edu.tw/handle/27747598978719836881
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