@article{ref1,
title="Comparative analysis of deterministic and semiquantitative approaches for shallow landslide risk modeling in Rwanda",
journal="Risk analysis",
year="2019",
author="Nsengiyumva, Jean Baptiste and Luo, Geping and Hakorimana, Egide and Mind'je, Richard and Gasirabo, Aboubakar and Mukanyandwi, Valentine",
volume="ePub",
number="ePub",
pages="ePub-ePub",
abstract="The use of appropriate approaches to produce risk maps is critical in landslide disaster management. The aim of this study was to investigate and compare the stability index mapping (SINMAP) and the spatial multicriteria evaluation (SMCE) models for landslide risk modeling in Rwanda. The SINMAP used the digital elevation model in conjunction with physical soil parameters to determine the factor of safety. The SMCE method used six layers of landslide conditioning factors. In total, 155 past landslide locations were used for training and model validation. The results showed that the SMCE performed better than the SINMAP model. Thus, the receiver operating characteristic and three statistical estimators-accuracy, precision, and the root mean square error (RMSE)-were used to validate and compare the predictive capabilities of the two models. Therefore, the area under the curve (AUC) values were 0.883 and 0.798, respectively, for the SMCE and SINMAP. In addition, the SMCE model produced the highest accuracy and precision values of 0.770 and 0.734, respectively. For the RMSE values, the SMCE produced better prediction than SINMAP (0.332 and 0.398, respectively). The overall comparison of results confirmed that both SINMAP and SMCE models are promising approaches for landslide risk prediction in central-east Africa.<br><br>© 2019 Society for Risk Analysis.<p /> <p>Language: en</p>",
language="en",
issn="0272-4332",
doi="10.1111/risa.13359",
url="http://dx.doi.org/10.1111/risa.13359"
}