Landslide susceptibility mapping based on landslide history and analytic hierarchy process (AHP)

Landslide phenomena are responsible for significant economic damages, loss of human lives and irreversible changes in natural environment. In this manuscript, in a landslide-prone site of Cyprus, a landslide susceptibility model was developed by coupling the popular analytic hierarchy process and the frequency ratio method in a GIS environment. Initially, 10 triggering factors and their modified Landslide Relative Frequencies (mLRF) were determined. Then, AHP was employed so as to determine the relative weights of each landslide instability factor and to omit those that were not essential for the model. Land cover was the most important parameter in the manifestation of landslides, while a 0.00404 consistency ratio index value revealed that the weights of the landslide contributing factors were well assessed. By combining the landslide instability agents along with their weights, a landslide susceptibility map emerged illustrating that almost 64.1 % of the study area was expanded on high-risk zones. The ROC curves and La.M.I. index statistic measures were generated by utilizing a binary file of 977,500 pixels, which had incorporated equal areas of landslide cells and randomly selected non-landslide ones. The above measures indicated that the overall model accuracy in the detection of landslide phenomena was 73.9 % and the model’s performance was enhanced when the parameters with the smallest weights were omitted from the model. This information could be significant in undertaking the appropriate series of measures according to landslide susceptibility zones in order to mitigate the landslide risk in the area.