Assess the human and environmental vulnerability for coastal hazard by using a multi-criteria decision analysis

Maanan, Mehdi; Maanan, Mohamed; Rueff, Henri; Adouk, Nessraddine; Zourarah, Bendahhou; Rhinane, Hassan

doi:10.1080/10807039.2017.1421452

Cited by 50 publications

(26 citation statements)

References 57 publications

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“…; 2) economic vulnerability related to the resources and/or capacity of building sturdy infrastructures; 3) physical vulnerability determined by population density, settlement remoteness, and housing; along with 4) environmental vulnerability such as degradation of natural resources (UNISDR ; Michael and Samanta ; Claeys et al ). Moreover, previous studies (Esperón‐Rodríguez et al ; Liu et al ; Maanan et al ; Miao et al ) that attempted to assess disaster vulnerability highlighted climate change, rapid human population growth, inappropriate natural resources management, lack of strong weather monitoring and early warning systems, and political and administrative structures among key drivers. The above vulnerabilities are associated with the fact that regular vulnerability and capacity assessment (VCA) is not prioritized to understand the problem, underlying causes, and required mechanisms (Mikoš ; Wang et al ).…”

Section: Introductionmentioning

confidence: 99%

Estimating landslides vulnerability in Rwanda using analytic hierarchy process and geographic information system

Nahayo

Ndayisaba

Karamage

et al. 2019

Integr Envir Assess & Manag

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Landslides are among hazards that undermine the social, economic, and environmental well‐being of the vulnerable community. Assessment of landslides vulnerability reveals the damages that could be recorded, estimates the severity of the impact, and increases the preparedness, response, recovery, and mitigation as well. This study aims to estimate landslides vulnerability for the western province of Rwanda. Field survey and secondary data sources identified 96 landslides used to prepare a landslides inventory map. Ten factors—altitude, slope angles, normalized difference vegetation index (NVDI), land use, distance to roads, soil texture, rainfall, lithology, population density, and possession rate of communication tools—were analyzed. The Analytical Hierarchy Process (AHP) model was used to weight and rank the vulnerability conditioning factors. Then the Weighted Linear Combination (WLC) in geographic information system (GIS) spatially estimated landslides vulnerability over the study area. The results indicated the altitude (19.7%), slope angles (16.1%), soil texture (14.3%), lithology (13.5%), and rainfall (12.2%) as the major vulnerability conditioning parameters. The produced landslides vulnerability map is divided into 5 classes: very low, low, moderate, high and very high. The proposed method is validated by using the relative landslides density index (R‐index) method, which revealed that 35.4%, 25%, and 23.9% of past landslides are observed within moderate, high, and very high vulnerability zones, respectively. The consistency of validation indicates good performance of the methodology used and the vulnerability map prepared. The results can be used by policy makers to recognize hazard vulnerability lessening and future planning needs. Integr Environ Assess Manag 2019;00:000–000. © 2019 SETAC

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Section: Introductionmentioning

confidence: 99%

Estimating landslides vulnerability in Rwanda using analytic hierarchy process and geographic information system

Nahayo

Ndayisaba

Karamage

et al. 2019

Integr Envir Assess & Manag

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“…Suburban areas related to urban problems are very effectively analyzed by GIS (Vaz et al, 2018). GIS can analyze the vulnerability of coastal areas and help the government in making decisions related to sustainable city development strategies (Maanan et al, 2018). The results of this study are better than the studies above related to the distribution analysis of filling station services.…”

Section: The Distribution Pattern Of the Filling Stationsmentioning

confidence: 78%

Utilization of GIS Techniques as Decision Support System for Location of Filling Stations in Minna, Niger State, Nigeria

2019

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The study demonstrated that spatial analysis with relevant socio-economic sources and physical parameter from different sources can be evaluated for the filling station sites planning. This has demonstrated the importance of Geographic Information System (GIS) application in predicting and determining of site criteria for filling stations facilities development, most especially in areas where there is land uses competition which requires consumer accessibility, sustainability, environmental safety, environmentally sensitive development solutions, etc. A stratified sampling technique was used to select the sample size and administration of the questionnaire. The data collected was analyzed using descriptive statistics such as frequency distribution, bar chart, pie chart and percentage and maps showing the sampled existing filling stations in the study area. The result shows the distribution of filling stations located across the study area. This study shows that GIS and multi-criteria analysis are essential tools to assist in correct siting to national planners and decision-makers in deciding the most appropriate filling stations location pattern to apply in Minna and its environs. Keywords: GIS, filling stations, spatial distribution, location, distance. References Aklilu, A., & Necha, T. (2018). Analysis of the spatial accessibility of addis Ababa’s light rail transit: The case of East–West corridor. Urban Rail Transit, 4(1), 35-48. doi:10.1007/s40864-018-0076-6 Dhiman, R., Kalbar, P., & Inamdar, A. B. (2019). Spatial planning of coastal urban areas in india: Current practice versus quantitative approach. Ocean and Coastal Management, 182 doi:10.1016/j.ocecoaman.2019.104929 Tah, D.S (2017). GIS-based locational analysis of Petrol filling stations in Kaduna metropolis: Science World Journal, Vol 12(2): 8-12. Emakoji, M.A., and Otah K.N (2018). Managing Filling Stations Spatial Database using an innovative GIS tool- a case study of Afipko City in Nigeria: Asian Journal of Geographical Research, 1(2):1-9, 2018 Jahangiri, M., Ghaderi, R., Haghani, A., & Nematollahi, O. (2016). Finding the best locations for establishment of solar-wind power stations in middle-east using GIS: A review. Renewable and Sustainable Energy Reviews, 66, 38-52. doi:10.1016/j.rser.2016.07.069 Jelokhani-Niaraki, M., Hajiloo, F., & Samany, N. N. (2019). A web-based public participation GIS for assessing the age-friendliness of cities: A case study in tehran, iran. Cities, 95 doi:10.1016/j.cities.2019.102471 Loidl, M., Witzmann-Müller, U., & Zagel, B. (2019). A spatial framework for planning station-based bike sharing systems. European Transport Research Review, 11(1) doi:10.1186/s12544-019-0347-7 Ma, Y., & Gopal, S. (2018). Geographicallyweighted regression models in estimating median home prices in towns of massachusetts based on an urban sustainability framework. Sustainability (Switzerland), 10(4) doi:10.3390/su10041026 Maanan, M., Maanan, M., Rueff, H., Adouk, N., Zourarah, B., & Rhinane, H. (2018). Assess the human and environmental vulnerability for coastal hazard by using a multi-criteria decision analysis. Human and Ecological Risk Assessment, 24(6), 1642-1658. doi:10.1080/10807039.2017.1421452 Khahro, S. H., Matori, A. N., Chandio, I. A., & Talpur, M. A. H. (2014). Land Suitability Analysis for Installing New Petrol Filling Stations Using GIS. Procedia Engineering, 77, 28–36. doi:10.1016/j.proeng.2014.07.024 Mustapha, O.O (2016). Assessment of filling stations in Illorin, Kwara State, Nigeria using Geospatial technologies, IJSRCSEIT vol 1(2) 69-73, 2016 Naboureh, A., Feizizadeh, B., Naboureh, A., Bian, J., Blaschke, T., Ghorbanzadeh, O., & Moharrami, M. (2019). Traffic accident spatial simulation modeling for planning of road emergency services. ISPRS International Journal of Geo-Information, 8(9) doi:10.3390/ijgi8090371 Peprah (2018). Suitability analysis of siting oil and gas filling station using multi-criteria decision analysis and GIS approach- a case study of Tarkwa and environs- Ghana: Journal of Geomatics, vol 12(2): 158-166, 2018 Sacramento Gutierres, F., Torrente, A. O., & Torrent-Moreno, M. (2019). Responsive geographical information systems for spatio-temporal analysis of mobile networks in barcelona. Architecture, City and Environment, 14(40), 163-192. doi:10.5821/ace.14.40.5349 Vaz, E., Lee, K., Moonilal, V., & Pereira, K. (2018). Potential of geographic information systems for refugee crisis: Syrian refugee relocation in urban habitats. Habitat International, 72, 39-47. doi:10.1016/j.habitatint.2017.02.001 Copyright (c) 2019 Geosfera Indonesia Journal and Department of Geography Education, University of Jember This work is licensed under a Creative Commons Attribution-Share A like 4.0 International License

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“…Figure 7 shows that the overall coastal elevation and coastal geomorphology vulnerability on artificial coasts are lower than those on natural coasts. According to previous researches [25,64,86] on aspects of coastal geomorphology, artificial coasts are less vulnerable than natural coasts. The coastal erosion protection of the artificial coast also has advantages because a higher class of artificial coast defence corresponds to a higher coastal elevation, and higher elevation areas are not as easily affected by extreme events; however, overall, in the aspect of vulnerability of coastal characteristics, artificial coasts is higher than that of the natural coasts.…”

Section: Indexes Influencing the Class Of Coastal Vulnerability To Ermentioning

confidence: 99%

Coastal Vulnerability to Erosion Using a Multi-Criteria Index: A Case Study of the Xiamen Coast

et al. 2018

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The assessment of coastal vulnerability to erosion is urgently needed due to increasing coastal erosion globally. Based on the coastal characteristics of the Xiamen artificial coastline, which accounts for more than 80% of the coastline in this area, this study provides an integrated approach based on a multi-criteria index. The evaluation index system of the local coastal vulnerability to the erosion of Xiamen includes 12 indexes based on natural (coastal characteristics, coastal forcing), and socio-economic factors (coastal infrastructure, disaster reduction). The spatial differentiation characteristics of the coastal vulnerability to erosion along the Xiamen coast (2018) have been quantitatively assessed with the aid of GIS (Geographic Information System) and RS (Remote Sensing) technology. The results show that the very high vulnerability, high vulnerability, medium vulnerability, low vulnerability and very low vulnerability areas of coastal erosion accounted for 4.6%, 30.5%, 51.6%, 12.5% and 0.8% of the Xiamen coast, respectively. The coastal vulnerability to erosion classes of artificial coasts is significantly higher than those of natural coasts. This difference is mainly controlled by the coastal slope and coastal buffer ability. The results of the evaluation are basically consistent with the present situation. The rationality of the index system and the applicability of the theoretical method are well explained. The evaluation model constructed in this study can be extended to other areas with high ratios of artificial coasts.

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Assess the human and environmental vulnerability for coastal hazard by using a multi-criteria decision analysis

Cited by 50 publications

References 57 publications

Estimating landslides vulnerability in Rwanda using analytic hierarchy process and geographic information system

Estimating landslides vulnerability in Rwanda using analytic hierarchy process and geographic information system

Utilization of GIS Techniques as Decision Support System for Location of Filling Stations in Minna, Niger State, Nigeria

Coastal Vulnerability to Erosion Using a Multi-Criteria Index: A Case Study of the Xiamen Coast

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