Arvind, CS and Vanjare, Ashoka and Omkar, SN and Senthilnath, J and Mani, V and Diwakar, PG (2016) Flood Assessment using Multi-Temporal Modis Satellite Images. In: 12th International Conference on Communication Networks (ICCN) / 12th International Conference on Data Mining and Warehousing (ICDMW) / 12th International Conference on Image and Signal Processing (ICISP), AUG 19-21, 2016, Bangalore, INDIA, pp. 575-586.
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Flood assessment using unsupervised techniques for multi-temporal MODIS satellite images is presented. Classical methods like mean shift algorithm is compared with artificial neural network method like self organizing maps for automatic water pixel identification and extraction. The extracted results help in identification of flooded and non-flooded places. Different methods are applied and comparative study of unsupervised methods involving mean shift and self organizing maps are carried-out. In order to evaluate the algorithmic performance, root mean square error and receiver operating characteristics is used as performance evaluation indices. The results reported will provide useful information for multi-temporal time series satellite image analysis which can be used for current and future research in disasters management. (C) 2016 The Authors. Published by Elsevier B.V.
|Item Type:||Conference Proceedings|
|Additional Information:||Copy right for this article belongs to the ELSEVIER SCIENCE BV, SARA BURGERHARTSTRAAT 25, PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS|
|Department/Centre:||Division of Mechanical Sciences > Aerospace Engineering (Formerly, Aeronautical Engineering)|
|Date Deposited:||07 Dec 2016 06:08|
|Last Modified:||07 Dec 2016 06:08|
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