Combining Unmanned Aerial Vehicle Photogrammetry with Multi-Criteria Decision-Making Technique to Analyze Dengue Breeding Area in Khon Kaen University
Keywords:
Geo-spatial data, Analytical hierarchy process, Aedes mosquito breedingAbstract
This article aims to develop an approach to analyze geo-spatial data from multi-platform such as unmanned aerial vehicle and satellite imagery including Sentinel-S2 and Landsat-8 data, employing geospatial-based multi-criteria decision-making (Geo-based MCDM) techniques. Using Geo-based MCDM in Terrset Software, the weight factors obtained from literature review and health professionals were derived as follows: (1) surface-temperature with factor weight of 29.6%; (2) greenspace, 21.7%; (3) water-resource index, 19.0%; (4) building height, 18.6%; (5) land-use, 6.6%; and (6) sewerage system, 4.4%. These weight factors indicated a risk area for Aedes mosquito breeding habitat, dividing results into high, medium and low level of risk. Our finding results reflected the ability to integrate geo-spatial data at multiple resolutions.
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