Landslide hazard modeling using multivariate spatial decision (Case Study: The Southern Railway West Country)

Landslide is one of the natural disasters that occur every year with the changes that humans make in natural areas. Landslide assessment event requires accurate and reliable location information. Today, despite the progress of science, landslides can be evaluated with various techniques such as remote sensing. Therefore, this study was conducted with the aim of modeling the occurrence of landslides in the southwestern region of the country using remote sensing science and AHP method. For this purpose, ground points were first prepared to control and Remote sensing information using GPS. Then, different filters were performed on the Landsat sensor images. In addition, different parameters of slope, geological formation, distance from the river, etc. were investigated. The results showed that the Kernel Size 9 * 9 filter is one of the most suitable methods for highlighting structural features and geomorphology. Then, the weight of each parameter was determined using pairwise comparison and AHP method. Results of pairwise comparison of distance from fault with weight of 0.05 maximum weight, distance from river 0.07, communication network 0.09, rainfall 0.12, land use 0.15, vegetation 0.2, geological formation 3 / 0 and a slope of 0.59 was obtained. The weighting results showed that by merging the different layers, the high and very dangerous risk classes included 32.87 and 6.68 km of the length of the railway lines, respectively, with a total of 39.55 km or 92.8% of the total 39.55 km of the total length of Andimeshk-Doroud railway line.