| Summary: | 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.
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