An indicator-based approach to assess social vulnerability of coastal areas to sea-level rise and flooding: A case study of Bandar Abbas city, Iran

Hadipour, Vahid; Vafaie, Freydoon; Kerle, N.

doi:10.1016/j.ocecoaman.2019.105077

Cited by 60 publications

(20 citation statements)

References 89 publications

(121 reference statements)

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“…This study adopted the FAHP to weight the criteria since FAHP assists the decisionmakers in overcoming uncertainty in providing the preferences of alternatives in the decision-making process (Kannan et al 2013;Ku et al 2010). Previous studies employed various FAHP approaches (Hadipour et al 2020;Hategekimana et al 2018;Tahri et al 2017). However, an integrated FAHP procedure was followed in this study that was developed by Chang (1996).…”

Section: Fahp and Criteria Weightingmentioning

confidence: 99%

Cyclone vulnerability assessment of the western coast of Bangladesh

Hoque

Pradhan

Ahmed

et al. 2021

Geomatics, Natural Hazards and Risk

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Section: Fahp and Criteria Weightingmentioning

confidence: 99%

Cyclone vulnerability assessment of the western coast of Bangladesh

Hoque

Pradhan

Ahmed

et al. 2021

Geomatics, Natural Hazards and Risk

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“…Studies show the population density is highly correlated to social vulnerability and might be one essential factor for social vulnerability since the higher population density represents a higher requirement during the environmental disturbance [ 45 , 46 , 47 ]. Some previous research also adopts sex as an important variable [ 48 , 49 ]. Research shows the standardized female population is a significant variable for exploring social vulnerability due to sex inequalities, social responsibility, and limited access to resources [ 50 ].…”

Section: Methodsmentioning

confidence: 99%

“…Education level significantly connects to the ability of information understanding. It also has a direct effect on the potential resources for coping with natural hazards [ 21 , 44 , 48 , 52 , 53 , 61 ]. Thus, we adopted the population without a high school diploma as a variable.…”

Section: Methodsmentioning

confidence: 99%

Using Spatial Pattern Analysis to Explore the Relationship between Vulnerability and Resilience to Natural Hazards

Sung

Liaw

2021

IJERPH

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This research aims to explore the spatial pattern of vulnerability and resilience to natural hazards in northeastern Taiwan. We apply the spatially explicit resilience-vulnerability model (SERV) to quantify the vulnerability and resilience to natural hazards, including flood and debris flow events, which are the most common natural hazards in our case study area due to the topography and precipitation features. In order to provide a concise result, we apply the principal component analysis (PCA) to aggregate the correlated variables. Moreover, we use the spatial autocorrelation analysis to analyze the spatial pattern and spatial difference. We also adopt the geographically weighted regression (GWR) to validate the effectiveness of SERV. The result of GWR shows that SERV is valid and unbiased. Moreover, the result of spatial autocorrelation analysis shows that the mountain areas are extremely vulnerable and lack enough resilience. In contrast, the urban regions in plain areas show low vulnerability and high resilience. The spatial difference between the mountain and plain areas is significant. The topography is the most significant factor for the spatial difference. The high elevation and steep slopes in mountain areas are significant obstacles for socioeconomic development. This situation causes consequences of high vulnerability and low resilience. The other regions, the urban regions in the plain areas, have favorable topography for socioeconomic development. Eventually, it forms a scenario of low vulnerability and high resilience.

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“…of weather-related natural hazards such as fire (forest fires, wildfires etc.) [16][17][18][21][22][23][24][25], flood [26][27][28][29][30][31][32], sea-level rise [33,34], landslide [35][36][37][38][39], land subsidence [40,41], drought [42,43] and erosion [44][45][46].…”

Section: Literature Review and Theoretical Foundationsmentioning

confidence: 99%

Rural Fire Risk Assessment in GIS Environment Using Fuzzy Logic and the AHP Approaches

Erdin¹,

Çağlar²

2021

Pol. J. Environ. Stud.

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Fires all around the world have caused irreparable environmental and economic losses due to the increase in global warming. Risk assessments are curial for taking measures to keep negative effects of natural hazards to a minimum and to ensure sustainability of the nature. In this regard, the aim of this study is to evaluate rural area fire risk in the seven geographical regions of Turkey. Since fire sensitive areas in rural regions are generally composed of forest areas, data on the size of forest areas, number of forest fires and temperatures are the main starting points of this study. Analysis was carried out using the Analytical Hierarchy Process and Fuzzy Logic approaches. In this study the Analytical Hierarchy Process and Fuzzy Logic approaches were integrated with the Geographical Information Systems. The results obtained from the AHP and Fuzzy Logic approaches were compared and evaluated. The results of the study show that the Aegean, Mediterranean and Marmara regions have the highest rural area fire risk levels. The fire risk assessments results obtained by the AHP and Fuzzy Logic approaches overlap on the basis of geographical regions. Integrating the AHP and Fuzzy Logic with GIS for rural area fire risk assessment provide valid, reliable and very important results in making the necessary planning and ensuring sustainability of the environment.

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An indicator-based approach to assess social vulnerability of coastal areas to sea-level rise and flooding: A case study of Bandar Abbas city, Iran

Cited by 60 publications

References 89 publications

Cyclone vulnerability assessment of the western coast of Bangladesh

Cyclone vulnerability assessment of the western coast of Bangladesh

Using Spatial Pattern Analysis to Explore the Relationship between Vulnerability and Resilience to Natural Hazards

Rural Fire Risk Assessment in GIS Environment Using Fuzzy Logic and the AHP Approaches

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