Application of frequency ratio, statistical index, and weights-of-evidence models and their comparison in landslide susceptibility mapping in Central Nepal Himalaya

The Mugling–Narayanghat road section falls within the Lesser Himalaya and Siwalik zones of Central Nepal Himalaya and is highly deformed by the presence of numerous faults and folds. Over the years, this road section and its surrounding area have experienced repeated landslide activities. For that reason, landslide susceptibility zonation is essential for roadside slope disaster management and for planning further development activities. The main goal of this study was to investigate the application of the frequency ratio (FR), statistical index (SI), and weights-of-evidence (WoE) approaches for landslide susceptibility mapping of this road section and its surrounding area. For this purpose, the input layers of the landslide conditioning factors were prepared in the first stage. A landslide inventory map was prepared using earlier reports, aerial photographs interpretation, and multiple field surveys. A total of 438 landslide locations were detected. Out these, 295 (67 %) landslides were randomly selected as training data for the modeling using FR, SI, and WoE models and the remaining 143 (33 %) were used for the validation purposes. The landslide conditioning factors considered for the study area are slope gradient, slope aspect, plan curvature, altitude, stream power index, topographic wetness index, lithology, land use, distance from faults, distance from rivers, and distance from highway. The results were validated using area under the curve (AUC) analysis. From the analysis, it is seen that the FR model with a success rate of 76.8 % and predictive accuracy of 75.4 % performs better than WoE (success rate, 75.6 %; predictive accuracy, 74.9 %) and SI (success rate, 75.5 %; predictive accuracy, 74.6 %) models. Overall, all the models showed almost similar results. The resultant susceptibility maps can be useful for general land use planning

Landslide susceptibility mapping in North-East Wales

This is an Accepted Manuscript of an article published by Taylor & Francis in Geomatics, Natural Hazards and Risk on 4th October 2011, available online: https://doi.org/10.1080/19475705.2011.600778In North-East Wales, United Kingdom, slope instability is a known environmental hazard which has caused significant damage to the built environment in the recent past. This paper reports on the creation of a digital landslide inventory for North-East Wales and the use of a Geographical Information System (GIS) to create landslide susceptibility models that are applicable to landslide hazard management in the area. The research undertaken has resulted in the most comprehensive landslide inventory of North-East Wales to date, documenting 430 landslides within the area. Landslide susceptibility models created within a GIS using a statistical (multiple logistic regression) approach, divide the landscape of North-East Wales into areas of ‘low’, ‘moderate’ and ‘high’ landslide susceptibility using calculated probability values. These models indicate that 8% of the surface exposure of drift deposits and 12% of the area of solid geology is of high or very high susceptibility to slope instability. Validation tests have demonstrated the accuracy of these models and their potential value in a predictive sense. The digital landslide database and susceptibility models created are readily available to interested stakeholders, and may be useful tools in land-use planning, development of civil contingency plans and as guidance for the insurance industry

Control of style-of-faulting on spatial pattern of earthquake-triggered landslides

Predictive mapping of susceptibility to earthquake-triggered landslides (ETLs) commonly uses distance to fault as spatial predictor, regardless of style-of-faulting. Here, we examined the hypothesis that the spatial pattern of ETLs is influenced by style-of-faulting based on distance distribution analysis and Fry analysis. The Yingxiu–Beichuan fault (YBF) in China and a huge number of landslides that ruptured and occurred, respectively, during the 2008 Wenchuan earthquake permitted this study because the style-of-faulting along the YBF varied from its southern to northern parts (i.e. mainly thrust-slip in the southern part, oblique-slip in the central part and mainly strike-slip in the northern part). On the YBF hanging-wall, ETLs at 4.4–4.7 and 10.3–11.5 km from the YBF are likely associated with strike- and thrust-slips, respectively. On the southern and central parts of the hanging-wall, ETLs at 7.5–8 km from the YBF are likely associated with oblique-slips. These findings indicate that the spatial pattern of ETLs is influenced by style-of-faulting. Based on knowledge about the style-of-faulting and by using evidential belief functions to create a predictor map based on proximity to faults, we obtained higher landslide prediction accuracy than by using unclassified faults. When distance from unclassified parts of the YBF is used as predictor, the prediction accuracy is 80%; when distance from parts of the YBF, classified according to style-of-faulting, is used as predictor, the prediction accuracy is 93%. Therefore, mapping and classification of faults and proper spatial representation of fault control on occurrence of ETLs are important in predictive mapping of susceptibility to ETLs