Rapid identification of mosquito larval habitats. A Remote sensing and GIS based quick-scan

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20 Feb 2008 09:00 - 20 Feb 2008 09:30
Unit: Laboratory of Geo-Information Science and Remote Sensing
Location: GAIA 2
Organisation: Wageningen University

 By Dirk-Jan Bulsink   

Abstract: 
For effective control measures against malaria, it is important to know where mosquito larval habitats are located. A quick-scan is developed to map mosquito larval habitats densities. Nine habitat types, which occur in western Kenya, have been defined. Based on these habitat types conceptual models are created, to detect these types of habitats out of datasets. The conceptual models are based on processes described in literature and not taking in account available data. Not all conceptual models are applicable because of data limitations. Taking in to account these data limitations, a model has been created based on the available data. The model, consisting of 6 sub-models, calculates habitat densities. The sub-models: human settlements, drainage channels and rain pools, streambed pools, landslides, landscape fragmentation and open water and paddies. The input datasets for these sub-models are: SRTM DEM, ASTER L1A Reconstructed Unprocessed Instrument Data, Africover Spatially Aggregated Multipurpose Landcover database and MODIS Vegetation Indices 16-Day L3 Global 250m. By using the raster based weighted linear combination method the outcomes of the sub-model are aggregated to an overall habitat density map. The weight values used to aggregate the sub-models couldn’t be calibrated because there is no extensive and representative dataset for the whole study area. An expert validation via a questionnaire is compiled to validate and calibrate the model. The outcomes of the quick-scan identify mosquito larval habitat densities on a local-scale.
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