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Use of GIS and dasymetric mapping for estimating tsunami-affected population to facilitate humanitarian relief logistics: a case study from Phuket, Thailand / Kiatkulchai Jitt-Aer in Natural Hazards, vol 113 n° 1 (August 2022)  

Public [article]  inNatural Hazards > vol 113 n° 1 (August 2022) . - pp 185 - 211 Titre : Use of GIS and dasymetric mapping for estimating tsunami-affected population to facilitate humanitarian relief logistics: a case study from Phuket, Thailand Type de document : Article/Communication Auteurs : Kiatkulchai Jitt-Aer, Auteur ; Graham Wall, Auteur ; Dylan Jones, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 185 - 211 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG [Termes IGN] analyse spatiale [Termes IGN] ArcGIS [Termes IGN] figuration de la densité [Termes IGN] gestion de crise [Termes IGN] interpolation spatiale [Termes IGN] planification côtière [Termes IGN] population [Termes IGN] prévention des risques [Termes IGN] Thaïlande [Termes IGN] tsunami Résumé : (auteur) The 2004 Indian Ocean tsunami led to improvements in Thailand’s early warning systems and evacuation procedures. However, there was no consideration of better aid delivery, which critically depends on estimates of the affected population. With the widespread use of geographical information systems (GIS), there has been renewed interest in spatial population estimation. This study has developed an application to determine the number of disaster-impacted people in a given district, by integrating GIS and population estimation algorithms, to facilitate humanitarian relief logistics. A multi-stage spatial interpolation is used for estimating the affected populations using ArcGIS software. We present a dasymetric mapping approach using a population-weighted technique coupled with remote sensing data. The results in each target area show the coordinates of each shelter location for evacuees, with the minimum and maximum numbers of people affected by the tsunami inundation. This innovative tool produces not only numerical solutions for decision makers, but also a variety of maps that improve visualisation of disaster severity across neighbourhoods. A case study in Patong, a town of Phuket, illustrates the application of this GIS-based approach. The outcomes can be used as key decision-making factors in planning and managing humanitarian relief logistics in the preparedness and response phases to improve performance with future tsunami occurrences, or with other types of flood disaster. Numéro de notice : A2022-703 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s11069-022-05295-x Date de publication en ligne : 09/03/2022 En ligne : https://doi.org/10.1007/s11069-022-05295-x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101566 [article]