Susceptibility Assessments of Landslides in Hulu Kelang Area Using a Geographic Information System-Based Prediction Model

Abstract

This study was conducted to estimate the susceptibility of landslides on a test site in Malaysia (Hulu Kelang area). A Geographic Information system (GIS)-based physical model named YS-Slope, which integrates a mechanistic infinite slope stability method and the geo-hydrological model was applied to calculate the safety factor of the test site. Input data, slopes, soil-depth, elevations, soil properties and plant covers were constructed as GIS datasets. The factor of safety of shallow landslides along the wetting front and deep-seated landslides at the bottom of the groundwater were estimated to compare with the analysis results of the existing model and actual landslides in 2008. According to the results of the study, shallow landslides mainly occurred in the central area which has many historical landslides, while deep-seated landslides were predominant in the east side of the study area. A ROC analysis was conducted and it is shown that the prediction result at the end of the northeast monsoon for shallow landslides showed relatively high accuracy compared with other predictions.

Soil moisture index estimation from landsat 8 images for prediction and monitoring landslide occurrences in Ulu Kelang, Selangor, Malaysia

“…The rainfall distribution mainly based on two monsoon seasons, known as the southwest monsoon (SWM), beginning from May to August and the northeast monsoon (NEM) which is from November to February. In Ulu Kelang, the soil moisture is mostly influenced by rainfall distribution [23][24][25][26].…”

Estimation of TRMM rainfall for landslide occurrences based on rainfall threshold analysis

“…According to the Malaysian Meteorological Department (MMD), the accumulated monthly rainfall for Ulu Kelang is between 58 and 420 mm per month, with an average of 200 rainy days per year and 2440 mm average annual rainfall. The Ulu Kelang area has suffered several fatal landslides cases due to rainfall events [19].…”

Landslides Susceptibility Assessment Based on GIS Statistical Bivariate Analysis in the Hills Surrounding a Metropolitan Area

“…The validation value of 0.854 indicates the relationship between true positive values (model sensitivity) and true negative values (model specificity) resulting in a large validation of the result, as it is known that the closer AUROC value is to 1, the more it reflects the degree of validation of the chosen method as well as of the database used [41][42][43][44]. Compared with simple statistics such as landslide percentage per susceptible zones and the proportion of correctly classified events derived from a confusion matrix used to valid landslide susceptibility maps and the inefficiency of these models, threshold-independent methods, like receiver operating characteristic (ROC), have been extensively used for validation [20,[45][46][47][48][49].…”

“…To a great degree, the territory under consideration falls into the low to medium-high susceptibility category with a larger percentage of low and medium susceptibility, territorial areas that do not require special work in terms of their operation and arrangement in terms of stabilization and to prevent landslides. Compared with simple statistics such as landslide percentage per susceptible zones and the proportion of correctly classified events derived from a confusion matrix used to valid landslide susceptibility maps and the inefficiency of these models, threshold-independent methods, like receiver operating characteristic (ROC), have been extensively used for validation [20,[45][46][47][48][49].…”