Topographic features and the formation of landslide dam

碩士 === 國立嘉義大學 === 土木與水資源工程學系研究所 === 101 === Global climate changehas increased the frequency of abnormal rainfall and high rainfall intensity in recent years in the mountainous areas in Taiwan.This study identifies historically induced earthquakes,typhoons,and landslide dams inTaiwan, andthe landsli...

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Main Author: 張峻銘
Other Authors: 陳建元
Format: Others
Language:zh-TW
Online Access:http://ndltd.ncl.edu.tw/handle/72580557377696864354
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spelling ndltd-TW-101NCYU57310152016-03-18T04:41:37Z http://ndltd.ncl.edu.tw/handle/72580557377696864354 Topographic features and the formation of landslide dam 崩塌形成堰塞湖的地形特徵分析 張峻銘 碩士 國立嘉義大學 土木與水資源工程學系研究所 101 Global climate changehas increased the frequency of abnormal rainfall and high rainfall intensity in recent years in the mountainous areas in Taiwan.This study identifies historically induced earthquakes,typhoons,and landslide dams inTaiwan, andthe landslide characteristics in the LaonongRiver basin. The analysis methodologies include spatial analysis using ArcGIS 9.3 and the topographic features modeled using the 20m × 20m digital terrain model (DTM). The Spot 6 satellite images after Typhoon Morakotwere used for an interpretation of the landslide areas.The multivariate statistical analysis was also used to find which major factors contributed to the formation of a landslide dam using SPSS. The selected 13 topographic featuresinclude the following:landslide area, slope, aspect, elevation difference, length, width, runout distance, average height, form factor of the landslide area, river width, stream power index (SPI), topographic wetness index (TWI), and elevation. The features of the 28 dammed landslides in theLaonongRiver basin and 59 landslides that did not form a dam were put into SPSS for aFisher Discriminant analysis and Logistic Regression analysis. The Principal Component analysis screened out four major topographic features as:runout distance, landslide slope, shape factor, and river width. The verification has shownthat the correct ratio by the Fisher Discriminant analysis was 71.7% and 79.2% by Logistic Regression analysis. Results of the analysis show that the Logistic Regression analysis is superior to the Fisher Discriminant analysis. This study suggestsusing the Logistic Regression analysis as the assessment model for thepotential location of a landslide dam for disaster prevention and mitigation. 陳建元 學位論文 ; thesis 0 zh-TW
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description 碩士 === 國立嘉義大學 === 土木與水資源工程學系研究所 === 101 === Global climate changehas increased the frequency of abnormal rainfall and high rainfall intensity in recent years in the mountainous areas in Taiwan.This study identifies historically induced earthquakes,typhoons,and landslide dams inTaiwan, andthe landslide characteristics in the LaonongRiver basin. The analysis methodologies include spatial analysis using ArcGIS 9.3 and the topographic features modeled using the 20m × 20m digital terrain model (DTM). The Spot 6 satellite images after Typhoon Morakotwere used for an interpretation of the landslide areas.The multivariate statistical analysis was also used to find which major factors contributed to the formation of a landslide dam using SPSS. The selected 13 topographic featuresinclude the following:landslide area, slope, aspect, elevation difference, length, width, runout distance, average height, form factor of the landslide area, river width, stream power index (SPI), topographic wetness index (TWI), and elevation. The features of the 28 dammed landslides in theLaonongRiver basin and 59 landslides that did not form a dam were put into SPSS for aFisher Discriminant analysis and Logistic Regression analysis. The Principal Component analysis screened out four major topographic features as:runout distance, landslide slope, shape factor, and river width. The verification has shownthat the correct ratio by the Fisher Discriminant analysis was 71.7% and 79.2% by Logistic Regression analysis. Results of the analysis show that the Logistic Regression analysis is superior to the Fisher Discriminant analysis. This study suggestsusing the Logistic Regression analysis as the assessment model for thepotential location of a landslide dam for disaster prevention and mitigation.
author2 陳建元
author_facet 陳建元
張峻銘
author 張峻銘
spellingShingle 張峻銘
Topographic features and the formation of landslide dam
author_sort 張峻銘
title Topographic features and the formation of landslide dam
title_short Topographic features and the formation of landslide dam
title_full Topographic features and the formation of landslide dam
title_fullStr Topographic features and the formation of landslide dam
title_full_unstemmed Topographic features and the formation of landslide dam
title_sort topographic features and the formation of landslide dam
url http://ndltd.ncl.edu.tw/handle/72580557377696864354
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