Geoinformatics-based frequency ratio, analytic hierarchy process and hybrid models for landslide susceptibility zonation in Kurdistan Region, Northern Iraq

Landslides are among the most critical geo-environmental disasters for both humans and the environment. This study intended to create a landslide susceptibility map (LSM) for the Akre District of Kurdistan Region, Northern Iraq. In this paper, 15 landslide causative criteria including elevation, slope, curvature, aspect, topographic wetness index, topographic roughness index, steam power index, lithology, lineament density, soil types, land use/cover, normalized difference vegetation index, distance to roads, rainfall, and distance to streams were analysed. For this purpose, frequency ratio (FR), analytic hierarchy process (AHP), and ensemble FR-AHP models based on geoinformatics techniques were applied. The LSMs were then assigned into five categories based on their susceptibility levels: very low, low, medium, high, and very high. The results showed that the high and very high landslide susceptibility categories for the FR, AHP, and hybrid FR-AHP models were 27.75% (732,01 km(2)), 28.44% (750,36 km(2)), and 28.84% (761 km(2)), respectively. The results showed that the majority of historical landslide incidents occurred in mountainous terrain in the northern parts of the study area, which are classified as high and very high susceptibility zones. The predicted rate curves for the FR, AHP, and hybrid FR-AHP models had areas under curve of the receiver operating characteristic curve (AUC-ROC) values of 93.4%, 89.3%, and 93.8%, respectively, which indicate that the ensemble FR-AHP model provides more reliable and accurate results for LSM. The LSM generated via the hybrid FR-AHP model can be utilised by local authorities, managers, and decision-makers in further land use/cove planning to mitigate the devastating influences of landslides in the area.

Automated summary

Landslides in the Akre District of Kurdistan Region, Northern Iraq were analyzed using geoinformatics techniques. The study identified 15 criteria that contribute to landslide susceptibility, such as elevation, slope, and rainfall. By applying the frequency ratio (FR), analytic hierarchy process (AHP), and ensemble FR-AHP models, a landslide susceptibility map (LSM) was created. The results showed that a significant portion of the study area has a high and very high susceptibility to landslides. The hybrid FR-AHP model provided the most reliable and accurate results for LSM and can be utilized for land use planning in order to mitigate the impact of landslides.