Please use this identifier to cite or link to this item: https://idr.l3.nitk.ac.in/jspui/handle/123456789/6615
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dc.contributor.authorSenthilnath, J.
dc.contributor.authorVikram, Shenoy, H.
dc.contributor.authorOmkar, S.N.
dc.contributor.authorMani, V.
dc.date.accessioned2020-03-30T09:45:55Z-
dc.date.available2020-03-30T09:45:55Z-
dc.date.issued2013
dc.identifier.citationAdvances in Intelligent Systems and Computing, 2013, Vol.202 AISC, VOL. 2, pp.163-174en_US
dc.identifier.urihttp://idr.nitk.ac.in/jspui/handle/123456789/6615-
dc.description.abstractThis paper discusses an approach for river mapping and flood evaluation based on multi-temporal time-series analysis of satellite images utilizing pixel spectral information for image clustering and region based segmentation for extracting water covered regions. MODIS satellite images are analyzed at two stages: before flood and during flood. Multi-temporal MODIS images are processed in two steps. In the first step, clustering algorithms such as Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) are used to distinguish the water regions from the non-water based on spectral information. These algorithms are chosen since they are quite efficient in solving multi-modal optimization problems. These classified images are then segmented using spatial features of the water region to extract the river. From the results obtained, we evaluate the performance of the methods and conclude that incorporating region based image segmentation along with clustering algorithms provides accurate and reliable approach for the extraction of water covered region. � 2013 Springer.en_US
dc.titleSpectral-spatial MODIS image analysis using swarm intelligence algorithms and region based segmentation for flood assessmenten_US
dc.typeBook chapteren_US
Appears in Collections:2. Conference Papers

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