Estimation of Shallow Landslide Susceptibility Using GIS Integrated Support Vector Regression

G, ANTHERJANAM and MC, PHILIPOSE and S, CHANDRAKARAN (2014) Estimation of Shallow Landslide Susceptibility Using GIS Integrated Support Vector Regression. In: Second International Conference on Advances In Civil, Structural and Environmental Engineering- ACSEE 2014, 25 - 26 October 2014, Zurich, Switzerland.

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Abstract

This paper proposes an effective method for susceptibility estimation of shallow landslides integrating the geographical information system based landslide susceptibility estimation model and a data driven paradigm. The study incorporates geotechnical properties of soil in modeling exercise along with the traditional geospatial landslide causative factors such as landuse and slope angle. The entire database is applied in SINMAP (stability index mapping) platform in the GIS environment to compute the susceptibility indices of the concerned study area in a multi-calibration mode. Then the geotechnical properties are extracted using kriging interpolation to use them as predictor variables to develop a regression model using support vector machine (SVM) and the prepared model is validated statistically. The methodology is demonstrated by applying it in Aruvikkal basin in Kerala state in India and the model is suitable for landslide susceptibility prediction problems in Western Ghats.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: landslide, GIS, support vector machines, staibility index
Depositing User: Mr. John Steve
Date Deposited: 30 May 2019 08:30
Last Modified: 30 May 2019 08:30
URI: http://publications.theired.org/id/eprint/2997

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