{"title":"大吉岭喜马拉雅巴拉逊河流域的地貌多样性和滑坡易感性","authors":"S. Mondal, S. Mandal","doi":"10.33430/v27n1thie2017-0054","DOIUrl":null,"url":null,"abstract":"This study attempts to assess the role of basin morphometric parameters in slope instability using a morphometric diversity (MD) model, as well as the role of drainage parameters and relief parameters in slope failure using drainage diversity (DD) and relief diversity (RD) models, respectively. For this, a total of 14 morphometric data layers were\nconsidered. The relationship of each data layer to landslide susceptibility was judged using a frequency ratio (FR) approach. Parameters like drainage density (Dd), drainage frequency (Df), relative relief (Rr), drainage texture (Dt), junction frequency (Jf), infiltration number (In), ruggedness index (Ri), dissection index (Di), elevation (E), slope (S), relief ratio (Rra) and hypsometric integral (Hi) were positively related with landslide potentiality while bifurcation ratio (Rb) and drainage intensity (Din) negatively correlated with S failure. The principal component analysis (PCA)-based weight assigned to each data layer in each model was multiplied with unidirectional reclassified data layers for each model using a weighted linear combination (WLC) approach to prepare landslide susceptibility maps. The receiver operating characteristics curve showed that the landslide prediction accuracy of the DD, RD and MD models were 71.4%, 73.9% and 76.3%, respectively. The FR plots of the aforesaid three models suggested that the chance of landslide increases from very low to very high in susceptible zones.","PeriodicalId":35587,"journal":{"name":"Transactions Hong Kong Institution of Engineers","volume":"27 1","pages":"13-24"},"PeriodicalIF":0.0000,"publicationDate":"2020-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Geomorphic diversity and landslide susceptibility in the Balason River Basin, Darjeeling Himalaya\",\"authors\":\"S. Mondal, S. Mandal\",\"doi\":\"10.33430/v27n1thie2017-0054\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study attempts to assess the role of basin morphometric parameters in slope instability using a morphometric diversity (MD) model, as well as the role of drainage parameters and relief parameters in slope failure using drainage diversity (DD) and relief diversity (RD) models, respectively. For this, a total of 14 morphometric data layers were\\nconsidered. The relationship of each data layer to landslide susceptibility was judged using a frequency ratio (FR) approach. Parameters like drainage density (Dd), drainage frequency (Df), relative relief (Rr), drainage texture (Dt), junction frequency (Jf), infiltration number (In), ruggedness index (Ri), dissection index (Di), elevation (E), slope (S), relief ratio (Rra) and hypsometric integral (Hi) were positively related with landslide potentiality while bifurcation ratio (Rb) and drainage intensity (Din) negatively correlated with S failure. The principal component analysis (PCA)-based weight assigned to each data layer in each model was multiplied with unidirectional reclassified data layers for each model using a weighted linear combination (WLC) approach to prepare landslide susceptibility maps. The receiver operating characteristics curve showed that the landslide prediction accuracy of the DD, RD and MD models were 71.4%, 73.9% and 76.3%, respectively. The FR plots of the aforesaid three models suggested that the chance of landslide increases from very low to very high in susceptible zones.\",\"PeriodicalId\":35587,\"journal\":{\"name\":\"Transactions Hong Kong Institution of Engineers\",\"volume\":\"27 1\",\"pages\":\"13-24\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-04-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Transactions Hong Kong Institution of Engineers\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.33430/v27n1thie2017-0054\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"Engineering\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transactions Hong Kong Institution of Engineers","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.33430/v27n1thie2017-0054","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Engineering","Score":null,"Total":0}
Geomorphic diversity and landslide susceptibility in the Balason River Basin, Darjeeling Himalaya
This study attempts to assess the role of basin morphometric parameters in slope instability using a morphometric diversity (MD) model, as well as the role of drainage parameters and relief parameters in slope failure using drainage diversity (DD) and relief diversity (RD) models, respectively. For this, a total of 14 morphometric data layers were
considered. The relationship of each data layer to landslide susceptibility was judged using a frequency ratio (FR) approach. Parameters like drainage density (Dd), drainage frequency (Df), relative relief (Rr), drainage texture (Dt), junction frequency (Jf), infiltration number (In), ruggedness index (Ri), dissection index (Di), elevation (E), slope (S), relief ratio (Rra) and hypsometric integral (Hi) were positively related with landslide potentiality while bifurcation ratio (Rb) and drainage intensity (Din) negatively correlated with S failure. The principal component analysis (PCA)-based weight assigned to each data layer in each model was multiplied with unidirectional reclassified data layers for each model using a weighted linear combination (WLC) approach to prepare landslide susceptibility maps. The receiver operating characteristics curve showed that the landslide prediction accuracy of the DD, RD and MD models were 71.4%, 73.9% and 76.3%, respectively. The FR plots of the aforesaid three models suggested that the chance of landslide increases from very low to very high in susceptible zones.