GIS integration with AHP and Frequency Ratio Methodologies for Landslide Susceptibility Mapping in Choman District, Iraq

The geographic information system (GIS) and remote sensing techniques used in this study with a combination of both analytic hierarchy process (AHP) and frequency ratio (RF) techniques to produce accurate and reliable areas that are susceptible to landslides for Choman district in Kurdistan region of Iraq. Communities and infrastructures can be damaged severely by landslides, highlighting the significant need for accurate and reliable susceptibility map of landslides for effective disaster management and risk mitigation procedures. It is one of the few researches that used free high resolution imagery from Google Earth Pro and field trips to collect historical landslide data, using it for landslide identification and validation. Topographic, hydrologic, geological, and anthropogenic parameters were identified as the main contribution factors for landslides that used as to establish an effective susceptibility model. The research categorized Choman district into four vulnerability zones: low, medium, high, and very high susceptibility. The results highlighted that steep slope regions with proximity to geological faults and main roads are most vulnerable regions to landslides in Choman district. The research result of FR approach indicated that around 16% (137.5 km2) of Choman district is highly susceptible to landslides and the high, medium, low susceptible areas were 42.4% (365.4 km2), 31.7% (273.5 km2) and 9.9% (85.3 km2), respectively. Accuracy assessment for the created map using field surveys indicated high accuracy for both methods. Specifically, with accuracy of 0.78 for AHP and 0.9 for FR, the results indicated a strong agreement between the predicted susceptibility areas and historical landslide events, also the consistency ratio was less than 0.1 with 0.05. Value of 0.726 for AHP and 0.824 for FR of area under the curve (AUC) demonstrated a good accuracy and reliability of the techniques. The findings of the research could significantly contribute for risk mitigation strategies, infrastructure development, and policy-making.