Landslide Susceptibility Mapping using Statistical Methods in Uatzau Catchment Area, Northwestern Ethiopia

Abstract

Uatzau basin in northwestern Ethiopia is one of the most landslide-prone regions, which characterized by frequent high landslide occurrences causing damages in farmlands, non-cultivated lands, properties, and loss of life. Preparing a Landslide susceptibility mapping is imperative to manage the landslide hazard and reduce damages of properties and loss of lives. GIS-based frequency ratio, information value, and certainty factor methods were applied. The landslide inventory map was prepared from detailed fieldwork and Google Earth imagery interpretation. Thus, 514 landslides were mapped, and out of which 359 (70%) of landslides were randomly selected keeping their spatial distribution to build landslide susceptibility models, while the remaining 155 (30%) of the landslides were used to model validation. In this study, six factors, including lithology, land use/cover, distance to stream, slope gradient, slope aspect, and slope curvature were evaluated. The effects of the landslide factor of slope instability were determined by comparing with landslide inventory raster using the GIS environment. The landslide susceptibility maps of the Uatzau area were categorized into very low, low, moderate, high and very high susceptibility classes. The landslide susceptibility maps of the three models validated by the ROC curve. The results for the area under the curve (AUC) are 88.83% for the frequency ratio model, 87.03% for certainty factor, and 84.83% of information value models, which are indicating very good accuracy in the identification of landslide susceptibility zones of a region. From these resulted maps, it is possible to recommend, the statistical methods (Frequency Ratio, Information Value, and Certainty Factor Methods) are adequate to landslide susceptibility mapping. The landslide susceptibility maps can be used for regional land use planning and landslide hazard mitigation purposes. Keywords: landslide; susceptibility; Geographic Information System (GIS); certainty factor; frequency ratio; information value; Ethiopia.

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Hazard Assessment of Earthquake-Induced Landslides Based on a Mechanical Slope Unit Extraction Method, A Case in Ghana

“…The statistical method could be bivariate methods, such as the frequency method (Chung & Fabbri, 2012;Dai & Lee, 2002;Wubalem, 2020), a multivariate statistical method such as Logistic Regression (LR) method (Atkinson & Massari, 1998;Polykretis et al, 2019), Artificial Neural Network (ANN) method, such as Back-propagation Algorithm method (Ortiz & Martínez-Graña, 2018;Tsangaratos & Benardos, 2014;Vakhshoori et al, 2019) or Machine Learning Techniques (MLTs), such as Support Vector Machine (SVM) method (Tien et al, 2012;Youssef & Pourghasemi, 2021;Kavzoglu et al, 2014). The robustness of the statistical method is, however, suspect.…”