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.
|Number of pages||27|
|Early online date||9 Mar 2022|
|Publication status||Published - 1 Aug 2022|
- tsunami inundation
- Geographical Information System (GIS)
- population estimation
- areal interpolation
- dasymetric mapping
- humanitarian logistics
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The integration of Geographic Information Systems and Capacitated Vehicle Routing Problem for humanitarian logistics: a case study of preparedness for a tsunami in Phuket, ThailandAuthor: Jitt-Aer, K., Sep 2018
Supervisor: Wall, G. (Supervisor) & Jones, D. (Supervisor)
Student thesis: Doctoral ThesisFile