Landslide characteristics and slope instability modeling using GIS, Lantau Island, Hong Kong |
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Authors: | F C Dai C F Lee |
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Institution: | 1. EURAC Research, Institute for Earth Observation, Viale Druso 1, 39100 Bolzano, Italy;2. Institut de Physique du Globe de Strasbourg, UMR7516, Université de Strasbourg/EOST, CNRS, 5 rue René Descartes, 67084 Strasbourg Cedex, France;3. Consiglio Nazionale delle Ricerche, Istituto di Ricerca per la Protezione Idrogeologica, via Madonna Alta 126, 06128 Perugia, Italy;1. Key Lab of Active Tectonics and Volcano, Institute of Geology, China Earthquake Administration, Beijing 100029, China;2. China Earthquake Networks Center, Beijing 100045, China;3. Earthquake Administration of Yunnan Province, Kunming 650041, China |
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Abstract: | Steep terrain and high a frequency of tropical rainstorms make landslide occurrence on natural terrain a common phenomenon in Hong Kong. This paper reports on the use of a Geographical Information Systems (GIS) database, compiled primarily from existing digital maps and aerial photographs, to describe the physical characteristics of landslides and the statistical relations of landslide frequency with the physical parameters contributing to the initiation of landslides on Lantau Island in Hong Kong. The horizontal travel length and the angle of reach, defined as the angle of the line connecting the head of the landslide source to the distal margin of the displaced mass, are used to describe runout behavior of landslide mass. For all landslides studied, the horizontal travel length of landslide mass ranges from 5 to 785 m, with a mean value of 43 m, and the average angle of reach is 27.7°. This GIS database is then used to obtain a logistic multiple regression model for predicting slope instability. It is indicated that slope gradient, lithology, elevation, slope aspect, and land-use are statistically significant in predicting slope instability, while slope morphology and proximity to drainage lines are not important and thus excluded from the model. This model is then imported back into the GIS to produce a map of predicted slope instability. The results of this study demonstrate that slope instability can be effectively modeled by using GIS technology and logistic multiple regression analysis. |
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Keywords: | Landslides Runout Logistic multiple regression Geographical Information Systems (GIS) |
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