Geospatial Approaches to Landslide Susceptibility Mapping: A Study of Rangamati Sadar Upazila, Bangladesh

Landslide susceptibility mapping is one of the most effective tools for sustainable development and management in hilly regions of countries, particularly in the Chittagong Hill Tracts (CHT) of Bangladesh. An innovative approach has been taken to create a landslide inventory, and a geospatial technique has been applied to map susceptible areas using the Information Value method. The research area has been classified into five categories ranging from very low to very high susceptibility by integrating information values. The analysis reveals that high and very high susceptibility classes in the study area are influenced by higher slopes, relatively high topography, concave curvature, proximity to roads and streams, sandy and loamy soils, and exposed Tipam Sandstone and Bokabil Formation. 31.9% and 34.9% of the Rangamati Sadar Upazila area are classified as high and very highly susceptible, while 7.2% are moderately susceptible. Among the seven unions, Balukhali Union is the most susceptible to landslide occurrence, followed by Kutuk Chhari and Sapchhari, where a large portion of the area falls under high and very high susceptibility classes. The results also show that landslide occurrence is strongly controlled by the interaction of topographic, geological, hydrological, and anthropogenic factors, including road construction and deforestation. Model validation using a confusion matrix demonstrates high predictive performance, with an overall accuracy of 93.5% and a Kappa coefficient of 0.87, confirming the reliability of the susceptibility map. Due to dense vegetation, low-quality google images, and satellite viewing angles, landslides are difficult to identify from imagery alone, making detailed field surveys the most reliable technique. These findings provide a scientifically stranded framework for risk-sensitive landuse planning and disaster risk reduction in the CHT region.

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Publication Details

Journal
International Journal of Environment and Geoinformatics
Published
2026-03-27
DOI
https://doi.org/10.26650/ijegeo.1684883
Primary Topic
Landslides and related hazards
Type
article
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article

Geospatial Approaches to Landslide Susceptibility Mapping: A Study of Rangamati Sadar Upazila, Bangladesh

Farhana Tazneen, Mehedi Hasan Peas, Md Azahar Hossain, Shaheen Sultana et al.
International Journal of Environment and Geoinformatics
Landslides and related hazards
article

Geospatial Approaches to Landslide Susceptibility Mapping: A Study of Rangamati Sadar Upazila, Bangladesh

Farhana Tazneen, Mehedi Hasan Peas, Md Azahar Hossain, Shaheen Sultana, Mohammad Salam
article en

Abstract

Landslide susceptibility mapping is one of the most effective tools for sustainable development and management in hilly regions of countries, particularly in the Chittagong Hill Tracts (CHT) of Bangladesh. An innovative approach has been taken to create a landslide inventory, and a geospatial technique has been applied to map susceptible areas using the Information Value method. The research area has been classified into five categories ranging from very low to very high susceptibility by integrating information values. The analysis reveals that high and very high susceptibility classes in the study area are influenced by higher slopes, relatively high topography, concave curvature, proximity to roads and streams, sandy and loamy soils, and exposed Tipam Sandstone and Bokabil Formation. 31.9% and 34.9% of the Rangamati Sadar Upazila area are classified as high and very highly susceptible, while 7.2% are moderately susceptible. Among the seven unions, Balukhali Union is the most susceptible to landslide occurrence, followed by Kutuk Chhari and Sapchhari, where a large portion of the area falls under high and very high susceptibility classes. The results also show that landslide occurrence is strongly controlled by the interaction of topographic, geological, hydrological, and anthropogenic factors, including road construction and deforestation. Model validation using a confusion matrix demonstrates high predictive performance, with an overall accuracy of 93.5% and a Kappa coefficient of 0.87, confirming the reliability of the susceptibility map. Due to dense vegetation, low-quality google images, and satellite viewing angles, landslides are difficult to identify from imagery alone, making detailed field surveys the most reliable technique. These findings provide a scientifically stranded framework for risk-sensitive landuse planning and disaster risk reduction in the CHT region.

International Journal of Environment and GeoinformaticsVol. 13(1)
Gazipur Agricultural University (BD), Clinical Research Organization (BD)
Openalex Percentile: Top 5%
Landslides and related hazards
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