Publication Date:
2012-08-27
Description:
Landslide susceptibility maps are vital for disaster management and for planning development activities in the mountainous country like Nepal. In the present study, landslide susceptibility assessment of Mugling–Narayanghat road and its surrounding area is made using bivariate (certainty factor and index of entropy) and multivariate (logistic regression) models. At first, a landslide inventory map was prepared using earlier reports and aerial photographs as well as by carrying out field survey. As a result, 321 landslides were mapped and out of which 241 (75 %) were randomly selected for building landslide susceptibility models, while the remaining 80 (25 %) were used for validating the models. The effectiveness of landslide susceptibility assessment using GIS and statistics is based on appropriate selection of the factors which play a dominant role in slope stability. In this case study, the following landslide conditioning factors were evaluated: slope gradient; slope aspect; altitude; plan curvature; lithology; land use; distance from faults, rivers and roads; topographic wetness index; stream power index; and sediment transport index. These factors were prepared from topographic map, drainage map, road map, and the geological map. Finally, the validation of landslide susceptibility map was carried out using receiver operating characteristic (ROC) curves. The ROC plot estimation results showed that the susceptibility map using index of entropy model with AUC value of 0.9016 has highest prediction accuracy of 90.16 %. Similarly, the susceptibility maps produced using logistic regression model and certainty factor model showed 86.29 and 83.57 % of prediction accuracy, respectively. Furthermore, the ROC plot showed that the success rate of all the three models performed more than 80 % accuracy (i.e. 89.15 % for IOE model, 89.10 % for LR model and 87.21 % for CF model). Hence, it is concluded that all the models employed in this study showed reasonably good accuracy in predicting the landslide susceptibility of Mugling–Narayanghat road section. These landslide susceptibility maps can be used for preliminary land use planning and hazard mitigation purpose. Content Type Journal Article Category Original Paper Pages 1-31 DOI 10.1007/s11069-012-0347-6 Authors Krishna Chandra Devkota, Department of Geology, Kyungpook National University, 1370 Sankyuk-dong, Buk-gu, Taegu, 702-701 Korea Amar Deep Regmi, Department of Geology, Faculty of Science, Shinshu University, Asahi 3-1-1, Matsumoto, 3908621 Japan Hamid Reza Pourghasemi, College of Natural Resources and Marine Sciences, Tarbiat Modares University (TMU), Tehran, Iran Kohki Yoshida, Department of Geology, Faculty of Science, Shinshu University, Asahi 3-1-1, Matsumoto, 3908621 Japan Biswajeet Pradhan, Faculty of Engineering, Geospatial Information Science Research Centre (GIS RC), University Putra Malaysia, 43400 Serdang, Selangor Darul Ehsan, Malaysia In Chang Ryu, Department of Geology, Kyungpook National University, 1370 Sankyuk-dong, Buk-gu, Taegu, 702-701 Korea Megh Raj Dhital, Central Department of Geology, Tribhuvan Univeristy, Kritipur, Kathmandu, Nepal Omar F. Althuwaynee, Faculty of Engineering, Geospatial Information Science Research Centre (GIS RC), University Putra Malaysia, 43400 Serdang, Selangor Darul Ehsan, Malaysia Journal Natural Hazards Online ISSN 1573-0840 Print ISSN 0921-030X
Print ISSN:
0921-030X
Topics:
Energy, Environment Protection, Nuclear Power Engineering
,
Geography
,
Geosciences
Permalink