Humanitarian help organisations today may benefit on improving their location analysis when placing field hospitals in countries hit by a disasters or catastrophe. The main objective of this thesis is to develop and evaluate a spatial decision support method for strategic placing of field hospitals for two time perspectives, long term (months) and short term (weeks). Specifically, the possibility of combining existing infrastructure and satellite data is examined to derive a suitability map for placing field hospitals. Haut-Katanga in Congo is used as test area where exists a large variety of ground features and has been visited by aid organisations in the past due to epidemics and warzones. The method consists of several steps including remote sensing for estimation of population density, a Multi Criteria Evaluation (MCE) for analysis of suitability, and visualization in a webmap. The Population density is used as a parameter for an MCE operation to create a decision support map for locating field hospitals. Other related information such as road network, water source and landuse is also taken into consideration in MCE. The method can generate a thematic map that highlights the suitability value of different areas for field hospitals. By using webmap related technologies, these suitability maps are also dynamic and accessible through the Internet. This new approach using the technology of dasymetric mapping for population deprival together with an MCE process, yielded a method with the result being both a standalone population distribution and a suitability map for placing field hospitals with the population distribution taken into consideration. The use of dasymetric mapping accounted for higher resolution and the ability to derive new population distributions on demand due to changing conditions rather than using pre-existing methods with coarser resolution and a more seldom update rate. How this method can be used in other areas is also analysed. The result of the study shows that the created maps are reasonable and can be used to support the locating of field hospitals by narrowing down the available areas to be considered. The results from MCE are compared to a real field hospital scenario, and it is shown that the proposed method narrows down the localisation options and shortens the time required for planning an operation. The method is meant to be used together with other decision methods which involves non spatial factors that are beyond the scope of this thesis.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:kth-34292 |
| Date | January 2011 |
| Creators | Rydén, Magnus |
| Publisher | KTH, Geodesi och geoinformatik |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
| Relation | Trita-GIT, 1653-5227 ; 11-002 |
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