Spatial Pattern of Physical Resilience of Rural Settlements in Amlash County Against Landslides

In this research, the physical resilience of the rural settlements of Amlash County against landslides was investigated using hierarchical analysis, weighted summation, and overlap index. Then, the spatial pattern of the resilience of the villages was determined using spatial statistics indicators. For this purpose, ten criteria of slope, distance from fault, building quality, materials and materials, building life, seismicity, geology, the direction of slope, width of passages, and height were used in order of importance. Also, two methods of local Moran's I statistic and hot spot analysis (G* Gettys-Ord) were used to identify patterns. The results showed that the physical resilience of rural settlements against landslides varies from very low to very high. Villages with very high resilience are in the northeastern region, and towns with very low resilience are in the northwestern region and the plains. They are located in the foothills of Amlash County. In the mountainous area of the County, villages with low and medium resilience were also visible in all three investigated models. In this regard, the results of the local population statistics show the presence of high-high (HH) and low-low (LL) clusters in the northeast and northwest of the studied area, and these patterns have also appeared in the villages of the plains and foothills. Also, the existence of hot and cold hot spots in the northeast and northwest of the County has been proven, and with three positive and negative standard deviations at the 99% confidence level, they have been shown in the plains and foothills. Most of the counties' villages have moderate resilience to landslides, and their random behavior was confirmed by local Moran's I statistics and hot spot analysis. In total, the points of villages with high and low resilience with high-high and low-low cluster patterns of local Moran's I and hot and cold spots of G* Gettys-Ord in all three models of hierarchical analysis, weighted summation, and matching overlap index were.