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Abstract
This paper addressed the problem of improving precision of malaria epidemic remote sensing by developing optimum image-fusion system, which analyses the implementation of image-fusion system through interpretation-lattice and takes into account that the benefits of image-fusion are maximized and the risk of error malaria epidemic recognition with remote sensing is minimized. We tested our RS image-fusion method with an application about monitoring malaria epidemic that is based on several TM and SPOT images and local statistical data. This method is better able to estimate the malaria epidemic level in comparison with only one single TM or SPOT image, the main method that was previously applied in this context.
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