Application of an evidential belief function model in landslide susceptibility mapping

Abstract

The objective of this paper is to exploit the potential application of an evidential belief function model to landslide susceptibility mapping at Kuala Lumpur city and surrounding areas using geographic information system (GIS). At first, a landslide inventory map was prepared using aerial photographs, high resolution satellite images and field survey. A total 220 landslides were mapped and an inventory map was prepared. Then the landslide inventory was randomly split into a testing dataset 70% (153 landslides) and remaining 30% (67 landslides) data was used for validation purpose. Fourteen landslide conditioning factors such as slope, aspect, curvature, altitude, surface roughness, lithology, distance from faults, ndvi (normalized difference vegetation index), land cover, distance from drainage, distance from road, spi (stream power index), soil type, precipitation, were used as thematic layers in the analysis. The Dempster-Shafer theory of evidence model was applied to prepare the landslide susceptibility maps. The validation of the resultant susceptibility maps were performed using receiver operating characteristics (ROC) and area under the curve (AUC). The validation results show that the area under the curve for the evidential belief function (the belief map) model is 0.82 (82%) with prediction accuracy 0.75 (75%). The results of this study indicated that the EBF model can be effectively used in preparation of landslide susceptibility maps.

Spatio-temporal assessment of soil erosion at Kuala Lumpur metropolitan city using remote sensing data and GIS

“…K factors were collected from soil series of the study area due to incomplete soil map as illustrated in table 2 (Althuwaynee et al 2012). Five kinds of soil series were found in the study area and all of them carried specific K factor values.…”

“…A landslide inventory map of the study area for the past 20 years (Althuwaynee et al 2012;Lee & Pradhan 2007) was laid out on actual soil erosion layer 2010 to demonstrate the spatial correlation of landslide occurrences and soil loss content (figure 5). The FR approach was applied to indicate the relationship between landslide distribution and soil erosion intensity as two related phenomena in the studied area (Pradhan 2010a;Pradhan & Lee 2010a;Pradhan & Buchroithner 2010b).…”

GIS-based spatial prediction of flood prone areas using standalone frequency ratio, logistic regression, weight of evidence and their ensemble techniques

“…This demonstrates a perfect classification where AUC = 1, and a classification by chance where AUC = 0.5. A number of studies have used AUC in susceptibility mapping efficiency evaluations (Althuwaynee et al 2012;Tien Bui et al 2012b). The technique involves dividing the probability map into equal area categories, and ranking these values in a minimum to maximum hierarchy.…”

Analytical study of the causes of the major landslide of Bukit Antarabangsa in 2008 using fault tree analysis

“…Palm oil and rubber estates have been established here through forest conversion. However, it is noted that many parts of the study area are being converted into urban, residential, recreational and industrial areas [23].…”