Integrated analysis of landslide susceptibility: geotechnical insights, frequency ratio method, and hazard mitigation strategies in a volcanic terrain

IF 1.827 Q2 Earth and Planetary Sciences Arabian Journal of Geosciences Pub Date : 2025-03-01 DOI:10.1007/s12517-025-12221-5
Brigitte Momene Tuwa, Donald Hermann Fossi, Aubin Nzeugang Nzeukou, Sylvestre Ganno, Désire Tsozue
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Abstract

This study investigates landslide susceptibility in the Baingo and Njinekejem areas with elevations ranging from 504 to 2863 m along the Cameroon Volcanic Line (CVL) in Central Africa. In this work, multifaceted approaches integrating geotechnical characterization, remote sensing data, and Geographic Information System (GIS) techniques were used to create a comprehensive landslide susceptibility map. The research methodology combines multiple factors contributing to landslide susceptibility, including topography, geology, land use, and soil properties, which are analyzed and integrated into a frequency ratio (FR) model. Detailed geotechnical analysis was conducted on soil samples from three locations (Ba1, Ba2, and NJ) to understand the mechanical behaviour of volcanic soils under saturated conditions. The soil analysis revealed significant physical and mechanical properties, including high porosity (55–61%), substantial void indices (1.228–1.561), and over-consolidation ratios around 21, indicating compressible but non-swelling characteristics. Additional parameters examined included unit weight and Atterberg limits to provide comprehensive insights into soil behaviour. The model’s accuracy was validated using the area under curve (AUC) method, achieving a value of 0.84, which demonstrates strong predictive capability. The resulting landslide susceptibility map identifies areas with varying degrees of susceptibility, from very low to very high, enabling stakeholders to develop targeted risk mitigation strategies for the region.

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滑坡易感性的综合分析:地质技术见解、频率比方法和火山地形的减灾策略
本研究调查了中非喀麦隆火山线(CVL)沿线海拔504至2863米的Baingo和Njinekejem地区的滑坡易感性。在这项工作中,采用了多方面的方法,结合岩土工程特征、遥感数据和地理信息系统(GIS)技术,创建了一个全面的滑坡易感性图。该研究方法结合了影响滑坡易感性的多种因素,包括地形、地质、土地利用和土壤性质,并将其分析并整合到频率比(FR)模型中。对Ba1、Ba2和NJ三个地点的土壤样本进行了详细的岩土分析,以了解火山土在饱和条件下的力学行为。分析结果显示,该土具有明显的物理力学特性,孔隙率高(55 ~ 61%),孔隙指数高(1.228 ~ 1.561),超固结比约为21,具有可压缩但不膨胀的特征。检查的其他参数包括单位重量和阿特伯格极限,以提供对土壤行为的全面了解。利用曲线下面积(AUC)法验证了模型的精度,AUC值为0.84,具有较强的预测能力。由此绘制的滑坡易感性图确定了易受影响程度从非常低到非常高不等的地区,使利益攸关方能够为该地区制定有针对性的风险缓解战略。
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来源期刊
Arabian Journal of Geosciences
Arabian Journal of Geosciences GEOSCIENCES, MULTIDISCIPLINARY-
自引率
0.00%
发文量
1587
审稿时长
6.7 months
期刊介绍: The Arabian Journal of Geosciences is the official journal of the Saudi Society for Geosciences and publishes peer-reviewed original and review articles on the entire range of Earth Science themes, focused on, but not limited to, those that have regional significance to the Middle East and the Euro-Mediterranean Zone. Key topics therefore include; geology, hydrogeology, earth system science, petroleum sciences, geophysics, seismology and crustal structures, tectonics, sedimentology, palaeontology, metamorphic and igneous petrology, natural hazards, environmental sciences and sustainable development, geoarchaeology, geomorphology, paleo-environment studies, oceanography, atmospheric sciences, GIS and remote sensing, geodesy, mineralogy, volcanology, geochemistry and metallogenesis.
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