Investigating the Resilience of Bandar Abbas Neighborhoods against Disaster


Coastal cities, Disasters, Resilience, Urban planning


How to Cite

Salimi, M., Soltani, A., Haghighi, H. ., Taheri, M., Aminizadeh, A., Salimi, T., Nazari, S., & Ahmadi Marzaleh, M. (2023). Investigating the Resilience of Bandar Abbas Neighborhoods against Disaster. Iranian Red Crescent Medical Journal, 25(8).


Background: Urban planning and urban planning activities have increased the pressure on nature and weakened its resilience, often bringing negative and even irreparable consequences.

Objectives: One of the most important issues in urban management in recent years is the emergence of resilient cities. Hormozgan is one of the most important provinces of the country, and Bandar Abbas, in the center of this province, is considered one of the major coastal cities of Iran from a national point of view.

Methods: To identify and examine the resilience of Bandar Abbas against environmental crises, based on which an information base was created, the place and spatial information of this database was prepared in 5 criteria and 29 sub-criteria. They include 1. socio-economic criteria, 2. structural criteria, 3. access criteria, 4. physical criteria, and 5. Ecological criteria. In the next step, to weigh and value the research criteria and sub-criteria in the resilience model of Bandar Abbas, the network analysis method (ANP) was used. In this model, the first 50 questionnaires were prepared by the Delphi method and distributed among experts in the field of environment and disaster management.

Results: The findings of this study indicated that the weight and value of ecological, socio-economic, physical, accessibility, and physical-structural criteria in resilience were 0.256, 0.236, 0.194, 0.171, and 0.141, respectively. Among the ecological criteria, the sub-criterion of distance from polluted points, the socio-economic criterion, the sub-criterion of access to medical-health centers, the sub-criterion of access to medical-health centers, among the physical-structural criteria, flood risk sub-criterion, and functional zone sub-criterion, and among access criteria, the sub-criterion of access to the fire station obtained the highest values in resilience.

Conclusion: Environmental crises, such as earthquakes, floods, accidents, air pollution, and storms, have resulted in the environmental vulnerability of the city and posed serious threats to the security of Bandar Abbas. A thorough understanding of the vulnerability of Bandar Abbas against urban environmental crises will enable policymakers to propose management solutions to reduce vulnerability and risk and increase resilience. Consequently, the main goal of this study was to evaluate the resilience of Bandar Abbas against environmental crises. The results of this study can be of great help in the decision-making of city managers and the lives of city residents.


Lin Y, Bie Z. Tri-level optimal hardening plan for a resilient distribution system considering reconfiguration and

DG islanding. Appl Energy. 2018;210:1266–79. doi: 10.1016/j.apenergy.2017.06.059

Yadollahnia H, Rajaei SA, PurAhmad A, Khorasani MA. The effects of physical expansion on the environmental resilience case study: City Babol. J Geogr. 2021;19(69):131-50.

Soto Caro M, Leon Canales J, Escobar Gueguen A. Public space and urban resilience: children's perspectives. The case of the hills of Valparaíso, Chile. Child Geogr. 2022;20(2):206–19. doi: 10.1080/14733285.2021.1925633.

Asadzadeh A, Kötter T, Zebardast E. An augmented approach for measurement of disaster resilience using connective factor analysis and analytic network process (F'ANP) model. Int J Disaster Risk Reduct. 2015;14(4):504–18. doi: 10.1016/j.ijdrr.2015.10.002.

Suárez M, Gómez-Baggethun E, Benayas J, Tilbury D. Towards an urban resilience index: a case study in 50 Spanish cities. Sustainability. 2016;8(8):774. doi: 10.3390/su8080774.

Kabir MH, Sato M, Habbiba U, Yousuf T Bin. Assessment of urban disaster resilience in Dhaka North City Corporation (DNCC), Bangladesh. Procedia Eng. 2018;212:1107–14. doi: 10.1016/j.proeng.2018.01.143

Najafi M, Khankeh H, Soltani A, Atighechian G. Reliability and Validity of Household Disaster Preparedness Index (HDPI). Iran Red Crescent Med J. 2020;22(12).8. doi: 10.32592/ircmj.2020.22.12.281.

Zhang X, Song J, Peng J, Wu J. Landslides-oriented urban disaster resilience assessment—A case study in ShenZhen, China. Sci Total Environ. 2019;661:95–106. doi: 10.1016/j.scitotenv.2018.12.074. [PubMed: 30665136].

Fakhruddin BSHM, Reinen-Hamill R, Robertson R. Extent and evaluation of vulnerability for disaster risk reduction of urban Nuku'alofa, Tonga. Prog Disaster Sci. 2019;2:100017. doi: 10.1016/j.pdisas.2019.100017.

Moghadas M, Asadzadeh A, Vafeidis A, Fekete A, Kötter T. A multi-criteria approach for assessing urban flood resilience in Tehran, Iran. Int J disaster risk Reduct. 2019;35:101069. doi: 10.1016/j.ijdrr.2019.101069.

Govindarajulu D. Strengthening institutional and financial mechanisms for building urban resilience in India. Int J Disaster Risk Reduct. 2020;47:101549. doi: 10.1016/j.ijdrr.2020.101549.

Chen C, Xu L, Zhao D, Xu T, Lei P. A new model for

describing the urban resilience considering adaptability, resistance and recovery. Saf Sci. 2020;128:104756. doi: 10.1016/j.ssci.2020.104756.

Rezaei MR, Rafieian M, Hosseini SM. Measurement and evaluation of physical resilience of urban communities against earthquake (Case study: Tehran neighborhoods). Hum Geogr. 2015;47(4):609-23. doi: 10.22059/JHGR.2015.51228.

Dadashpour H, Adeli Z. Measuring resilience capacities in Qazvin urban complex. JOEM. 2015;4(2):73-84.

Soltani A, Alaedini F, Shamspour N, Marzaleh MA. Hazard Assessment of Iran Provinces based on the Health Ministry Tool in 2019. Iran Red Crescent Med J. 2021;23(1). doi: 10.32592/ircmj.2021.23.1.204.

Delake H, Samare Mohsen Beigi H, Shahivandi A. Evaluation of social resilience in urban areas of Isfahan. J Sociol. 2017;4(9):227-52. doi: 10.22080/SSI.2017.1565.

Moradpour N, Pourahmad A, Hataminejad H, Ziari K, Sharifi A. An overview of the state of urban resilience in Iran. Int J Disaster Resil Built Environ. 2022;14(39). doi: 10.1108/IJDRBE-01-2022-0001.

Shokri Firoozjah P. Spatial analysis of resilience of babol's regions to environmental hazards. PSP. 2017;4(2):27-44.

Abdollahi A, Sharafi HA, Sabahi GY. Measurement And evaluation Resiliency Institutional and physical-environmental Urban communities to reduce natural disasters, Earthquake(Case study: Kerman city). EBTP. 2018;42(11):165-87.

Pashnezhad Sielab E, Rafieyan M, Pourtaheri M. Spatial Assessment of the relationship between environmental vulnerability and rural community resilience in east-azerbaijan province. JRRP. 2017;6(2):93-107. doi: 10.22067/JRRP.V6I2.57081.

Pour Mohammadi MR, Hadi E, Hadi E. Explaining the socio-economic aspects of urban resilience against earthquake: a case study, 4th district of Tabriz. Disaster Prev Manag Know. 2019;9(1):78-89.

Ghasem F, Shahriar K, Manijeh GT, Patel N. Effects of climate change on dynamics of agricultural lands and cultivation pattern, a case study of Urmia County, Iran. Arab J Geosci. 2022;15(21):1-1. doi: 10.1007/s12517-022-10926-5.

Parkouhi SV, Ghadikolaei AS. A resilience approach for supplier selection: Using Fuzzy Analytic Network Process and grey VIKOR techniques. J Clean Prod. 2017;161:431–51. doi: 10.1016/j.jclepro.2017.04.175.

Liu D, Qi X, Li M, Zhu W, Zhang L, Faiz MA, et al. A resilience evaluation method for a combined regional agricultural water and soil resource system based on Weighted Mahalanobis distance and a Gray-TOPSIS model. J Clean Prod. 2019;229:667–79.

Zhang W, Su S, Wang B, Hong Q, Sun L. Local k-NNs pattern in Omni-Direction graph convolution neural network for 3D point clouds. Neurocomputing. 2020;413:487–98.

Asgarian A, Jabbarian Amiri B, Alizadeh Shabani A, Feghhi J. Assessing urban growth patterns in Sari using landscape ecology approach. J Nat Environ. 2015;68(1):95-107.‎

Ghaderi Z, Aslani E, Beal L, Dehghan Pour Farashah M, Ghasemi M. Disaster-resilience of small-scale tourism businesses in the pandemic era: the case of Yazd World Heritage Site, Iran. Tour Recreat Res. 2022:1-7. doi: 10.1080/02508281.2022.2119519.

Shahabi H. Application of artificial neural network, frequency ratio and evidential belief function models in preparing of flood susceptibility map in Haraz watershed: A plan for urban flood risk studies. JUPM. 2021;12(45):181-202. doi: 10.30495/JUPM.2021.4245.