Landslide susceptibility analysis in the Hoa Binh province of Vietnam using statistical index and logistic regression

Dieu Bui (), Owe Lofman, Inge Revhaug and Oystein Dick

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2011, vol. 59, issue 3, 1413-1444

Abstract: The purpose of this study is to evaluate and compare the results of applying the statistical index and the logistic regression methods for estimating landslide susceptibility in the Hoa Binh province of Vietnam. In order to do this, first, a landslide inventory map was constructed mainly based on investigated landslide locations from three projects conducted over the last 10 years. In addition, some recent landslide locations were identified from SPOT satellite images, fieldwork, and literature. Secondly, ten influencing factors for landslide occurrence were utilized. The slope gradient map, the slope curvature map, and the slope aspect map were derived from a digital elevation model (DEM) with resolution 20 × 20 m. The DEM was generated from topographic maps at a scale of 1:25,000. The lithology map and the distance to faults map were extracted from Geological and Mineral Resources maps. The soil type and the land use maps were extracted from National Pedology maps and National Land Use Status maps, respectively. Distance to rivers and distance to roads were computed based on river and road networks from topographic maps. In addition, a rainfall map was included in the models. Actual landslide locations were used to verify and to compare the results of landslide susceptibility maps. The accuracy of the results was evaluated by ROC analysis. The area under the curve (AUC) for the statistical index model was 0.946 and for the logistic regression model, 0.950, indicating an almost equal predicting capacity. Copyright Springer Science+Business Media B.V. 2011

Keywords: Landslide susceptibility; Logistic regression; Statistical index; Hoa Binh province (search for similar items in EconPapers)
Date: 2011
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Citations: View citations in EconPapers (27)

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DOI: 10.1007/s11069-011-9844-2

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