Spatial pattern of physical resilience of rural settlements in Amlash County against landslides

Document Type : Thesis Article

Authors

1 PhD Candidate, Department of Geography, Faculty of Humanities, Rasht Branch, Islamic Azad University, Rasht, Iran.

2 Assistant Professor, Department of Geography, Faculty of Humanities, Rasht Branch, Islamic Azad University, Rasht, Iran.

3 Professor, Department of Geography, Faculty of Humanities, Rasht Branch, Islamic Azad University, Rasht, Iran.

Abstract

1. Introduction
Resilience against natural hazards means the level of resistance when facing natural hazards, which are caused by facing environmental and social pressures. Environmental components such as height and slope, slope direction, soil, geology, land use are among the biophysical components of resilience, and socio-economic conditions are also among the social components of resilience. In Iran, out of the 40 hazards identified, 31 of them occur. Therefore, Iran is one of the countries that are very vulnerable to natural disasters, so that 37.7% of its total area is at risk of natural disasters and 70% of the country's population lives in disaster-prone areas. Landslides are among the most common natural phenomena, which are one of the destructive types of erosion in the slopes, which disrupt the water and soil system in nature, destroy vegetation and agricultural lands, sedimentation, acceleration of erosion, etc. Therefore, the issue of environmental hazards and their planning and management is considered a basic principle and an inevitable necessity for settlements in rural areas.
2. Methodology
In order to identify the spatial pattern of physical resilience of the rural settlements of Amlash County against landslides, natural and human indicators effective in resilience were used at first. For this purpose, criteria and sub-criteria affecting the resilience of rural settlements in this area were identified by a survey of experts. The criteria and sub-criteria were finalized after the review and in addition to the selection of 10 main criteria, the sub-criteria were determined and the resilience of each criterion was divided into three sub-criteria with high, medium and low resilience. In addition, the impact of each criterion on the final resilience of rural settlements was determined according to the specific importance and the preference code of each sub-criterion, which changes from higher preference to lower preference (7, 5 and 3). The geographical territory of the present study is Amlash County in Gilan province, which has two parts, Rankuh and Central, with 145 villages.
3. Results
In this research, the spatial pattern of the physical resilience of settlements in 145 villages of Amlash County against landslides was investigated and analyzed using three methods: hierarchical analysis (AHP), weighted summation (WS) and overlap index (IO). For this purpose, 10 criteria of slope, distance from fault, building quality, materials and materials, building life, seismicity, geology, direction of slope, width of passages and height were used in order of importance. In this regard, the level of resilience of settlements in Amlash County using three models showed that villages with high resilience are located in the plains and foothills of the northeast of the County, and villages with low resilience are located in the plains and foothills of the northwest. They got. In the mountainous areas, most of the villages had good resistance to landslides in all three models.
4. Discussion
The spatial model of the resilience of rural settlements by the local Moran index I method showed that the resilience of the villages in the north-eastern part of the city in the studied models of the high-high cluster pattern (HH) and the low-low cluster pattern (LL) in the sector The north-west is the one that is completely compatible with rural areas with very high and very low resilience. Other rural areas in plain, foothills and mountainous areas of Amlash County did not follow a specific pattern and behaved randomly and senselessly. Likewise, the results obtained from the analysis of hot spots (G* Gettys -Ord) on the physical resilience of rural settlements in all three AHP, WS and IO models confirm that the hot and cold spots of resilience are respectively in the plains and There is a foothill in the northeast and northwest of the County. And this importance was also confirmed at the 99% confidence level with a standard deviation of 3 for hot spots and -3 for cold spots. Therefore, the center and main core of maximum and minimum resilience is located in the northern half of this County, so that they are relatively close to each other and in the same latitude. Therefore, the resilience conditions of villages against landslides are significantly different between swamp, foothill and mountain areas.
5. Conclusion
The results showed that the physical resilience of rural settlements against landslides varies from very low to very high resilience, and villages with very high resilience are in the northeastern region and villages with very low resilience are in the northwestern region and in plain. They are located in the foothills of Amlash County. In the mountainous area of the County, villages with low and medium resilience were visible in all three models. In this regard, the results of the I statistics of local morans indicate 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 north-east and north-west of the County has been proven and they have been shown with 3 positive and negative standard deviations at the 99% confidence level in the plains and foothills. Most of the villages in the County have moderate resilience to the phenomenon of 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 were consistent with the pattern of high-high and low-low clusters of local Moran's I and hot and cold spots of G* Gettys-Ord in all three models of hierarchical analysis, weighted sum and overlap index.

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Articles in Press, Accepted Manuscript
Available Online from 14 November 2023
  • Receive Date: 19 August 2023
  • Revise Date: 13 November 2023
  • Accept Date: 14 November 2023