FRMOD, a Python tool for statistical landslide susceptibility assessment

Locating landslide-prone slopes is important, as landslides often threaten life or property where they occur. There is an abundance of statistical methods in the literature for estimating susceptibility to landslides, i.e., the likelihood of landslide occurrence based on the analyzed conditions. Still, there is a lack of readily available GIS tools for landslide susceptibility analysis, making it hard to reproduce or compare the results of different susceptibility assessments. The FRMOD is a Python-based tool for conducting landslide susceptibility analysis with the frequency ratio method. The frequency ratio method yields susceptibility estimates by comparing the frequency distributions of a set of variables from the sample landslide areas to the distributions for the whole study area. The estimates show the level of similarity to the sample landslides. The two main inputs of the tool are the raster grids of the analyzed continuous (e.g., elevation, slope) and thematic (e.g., lithology) variables and the mask grid that marks the landslide and the non-landslide areas. The analysis is performed with cross-validation to measure the predictive performance of the model. Data computed during the analysis is stored along the final susceptibility estimates and the supplementary statistics. The script reads and writes GDAL-compatible rasters, while the statistics can be saved as text files. Basic plotting functionalities for the grids and the statistics are also built-in to quicken the evaluation of the results. FRMOD enables the swift testing of different analysis setups and to apply the same analysis method for different areas with relative ease.

Analysis of soil permeability and C-Organic in landslide events in Tangka Sub-Watershed

One of the areas in South Sulawesi Province classified as prone to landslides is the Tangka Sub-watershed in the West Sinjai Sub-District. The factors used in making the susceptibility map in the West Sinjai area mostly use general characteristics, such as slope, slope shape, distance from the river, lithology, land cover, and rainfall. Several previous research results stated that internal soil factors significantly affect the occurrence of landslides. Therefore, this study aims to determine the internal characteristics of the soil, especially the permeability and C-organic soil, which affects the occurrence of landslides and create a susceptibility map based on the resulting frequency ratio value. Soil permeability analysis using permeameter method, C-Organic analysis using Walkley and Black method, and susceptibility maps using frequency ratio method. The results showed that the low permeability and c-organic level of the soil increased the soil susceptibility to landslide events and produced a more detailed map of the area susceptibility than using only general factors.

Analysis of the landslide susceptibility map using frequency ratio method in sub-sub-Watershed Mamasa

Landslides that often occur in the Subs watershed of Mamasa increase the sedimentation rate so that the Bakaru hydropower plant becomes less than optimal. The contributing factors to lanslide susceptibility are land closure, lithology, curve, slope direction aspect, slope, precipitation, fault distance, and river distance. The research aims to determine the most influential erosion causative factor in Mamasa Sub-watershed by building a landslide susceptibility map using the frequency ratio method. The most significant factor is land closure, with a value of 2.03, indicating a high probability of lanslide events. The model’s success rate and prediction rate’s success rate were expressed fairly well with 0.754 and 0.752. Based on the insanity map, the Region is very high and high at 23.74% and 12.52%; insanity is moderate, low, and very low consecutively at 27.44 %, 23.77, and 12.33%.