Abstract
A spatial probabilistic landslide risk assessment and mapping model has been applied in a data scare region. The probabilistic model is based on a physical model based on Mohr coulomb failure criterion. A Monte Carlo simulation technique is applied to field collected data. The results are integrated and a probability of landslide is obtained at each cell level. The results are compared to a prepared landslide inventory. The overall accuracy of the model is 79.69%.
Highlights
The expansion of constructions and buildings in cities of developing countries creates new challenges in risk management of constructions and buildings and in environmental sustainable planning of peri-urban areas
The statistical approach proposed by Kubwimana et al (2018) did not take in account the physical parameters linked with slope stability analysis
The objective of this study is to develop landslide susceptibility maps using a probabilistic approach which takes in account the physical parameters of slope stability analysis and the uncertainties linked with them
Summary
The expansion of constructions and buildings in cities of developing countries creates new challenges in risk management of constructions and buildings and in environmental sustainable planning of peri-urban areas. Among the various potential risks, the landslide risk is a challenge for our study area. The Bujumbura peri-urban area has witnessed several hazards of different nature: floods, rock falls and landslides[1], [2]. The statistical approach proposed by Kubwimana et al (2018) did not take in account the physical parameters linked with slope stability analysis. Several studies assessing and mapping landslide susceptibility have been conducted worldwide using two principal approaches: deterministic and statistical. For the developed deterministic models[5]–[9], the relevant factor is the factor of safety based on slope stability analysis. Slope stability analyses of landslides in deterministic models are usually performed using conventional limit equilibrium method based on the Mohr–Coulomb failure criterion. Statistical approaches [10]–[14] have been used for landslide susceptibility assessment
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