مخاطرات محیط طبیعی (May 2019)

A spatial assessment of the infrastructure resilience capacity in rural communities of Bojnourd County by FAHP model and fuzzy logic in GIS

  • Aliakbar Anabestani,
  • Mahdi Javanshiri

DOI
https://doi.org/10.22111/jneh.2018.23018.1351
Journal volume & issue
Vol. 8, no. 20
pp. 167 – 196

Abstract

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The main purpose of the present study is to assess the relationship between environmental vulnerability and infrastructure resilience of rural communities (in Bojnourd County), so that one can improve the resilience capacity in rural areas. The research was conducted in a descriptive-analytical method and in nature it is applicable in local planning and rural development systems. Research variables have been selected after reviewing theoretical foundations and literature on vulnerability and resilience assessment in Iran and other countries. Accordingly, two general indicators of vulnerability assessment and infrastructure resilience of rural communities were developed using 26 criteria in FAHP and fuzzy logic (Gamma operator with the thresholds of 0.7, 0.8 and 0.9) in the GIS environment. The results indicate that approximately 56.69% of the County’s area has a high and very high environmental vulnerability, and 47 villages were situated in this area. The survey of the resilience index indicates that there is a significant and direct relationship between low resilience in rural areas and environmental vulnerabilities in the eastern, southern and northeastern parts of Bojnourd County. In addition, based on the FAHP output, about 31 percent of the rural areas of the county, and based on the output of fuzzy logic, about 53 percent of the rural areas of the county are in a very high resilience level). The analysis of the output results of FAHP and fuzzy logic in GIS with a Kappa coefficient of 0.166 showed that the results of the two models have comparatively weak but direct correlation, which was determined by measuring the accuracy of the models using ground control points. Fuzzy logic model with a Kappa coefficient of 0.772 is more accurate than the FAHP model with a Kappa coefficient of 0.550.

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