Landslide sensitivity assessment using fuzzy logic approach and GIS in Neka Watershed

Landslide is an important geological hazard and one of the natural disasters that are constantly happening around the world. The factors that cause landslides are numerous and complex. Today, due to the importance of landslides and the effects of not paying attention to this issue, risk prevention has become an important tool in land use planning and management. Given the sensitivity and importance of this issue, the preparation of zoning maps of landslide sensitivity is very important and should be considered. These maps show landslide-prone areas and safe areas. Effective use of the landslide map can reduce the potential damage to the event and thus avoid many hazards. Landslides are natural events, but they can become dangerous and cause casualties and damage to man-made and natural structures.

The study area is the Neka Watershed located in the east of Mazandaran Province. To study landslides in this study, from nine maps including land use, slope, geology, slope direction, land curvature, distance from faults, communication routes, sewage from the river, and rainfall were selected and each map was extracted to produce the final landslide map. Finally, the maps were finalized in GIS software and the final map was prepared using the fuzzy logic method. In the fuzzy model, each of the pixels in the map is given a value between zero and one. To perform fuzzy in ArcGIS software the fuzzy Membership tool was applied. In this research, the Shannon entropy method was also used. Finally, the landslide map was extracted and evaluated. According to the final map and its studies, landslide-sensitive areas were identified.

Various factors, in relation to each other and in relation to local characteristics, cause domain instability. Instability factors with different contributions to the occurrence of mass movements, especially in the occurrence of landslides. To study landslides in this study, from 9 maps including land use, slope, geology, slope direction, land curvature, distance from the fault, communication paths (sewage from the road), sewage from the river and rainfall, and the map of each separately The final landslide was extracted to prepare the map. The maps were prepared in the final GIS software and the final map was prepared using the fuzzy logic method. The fuzzy model was performed using Arc GIS software and each of the pixels in the map was given a value between zero and one. The Shannon entropy method was used in this study. Finally, the landslide map was extracted and evaluated. According to the final map and its studies, landslide-sensitive areas were identified.

Based on the knowledge-based approach, the evaluation of several parameters such as geology, slope, land cover, slope direction, land curvature, rainfall, distance to flow, distance to road, and distance to fault were overlayed and the landslide map was extracted. A numerical scale (1-5) from very high to very low impact was used. Areas with high and very high sensitivity have been recorded in areas without vegetation and with high slopes and high rainfall. Sub-watersheds N2 and N1 are ranked 1st and 2nd, respectively, in terms of high landslide potential. The reason for the high intensity of landslides in these two sub-watersheds is low vegetation and a high slope.