Geospatial Analysis for Identifying Socially Vulnerable Areas to Natural Disasters

Disaster risk reduction measures are now being developed based on social vulnerability. This study aimed to identify socially vulnerable areas to disasters in Razavi Khorasan Province, Iran.

The research utilized a mixed method approach conducted in 2 stages. First, a vulnerability index was created using 8 sub-indices, and the value of the index was calculated for each of the 91 rural districts in the study area. In the second stage, spatial analysis using Anselin's Local Moran's I was performed to identify the most vulnerable districts.

Results indicated that 40 of 91 districts, covering 49% of the total area, had high social vulnerability to disasters. Anselin's Local Moran's I analysis identified 2 high-high clusters consisting of 5 districts. The study also found that areas with higher social vulnerability were more susceptible to natural hazards such as floods and earthquakes.

Nearly half of the studied areas exhibited a high level of social vulnerability and were at risk of natural disasters. Implementing general measures to improve the socio-economic status of the population, such as increasing education and income levels, along with specific actions like assisting vulnerable populations in relocating to safer areas, can help mitigate disaster risks.