Senthilnath, J and Bajpai, Shivesh and Omkar, SN and Diwakar, PG and Mani, V (2012) An approach to multi-temporal MODIS image analysis using image classification and segmentation. In: ADVANCES IN SPACE RESEARCH, 50 (9). pp. 1274-1287.Full text not available from this repository.
This 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 classification and region-based segmentation for extracting water-covered regions. Analysis of MODIS satellite images is applied in three stages: before flood, during flood and after flood. Water regions are extracted from the MODIS images using image classification (based on spectral information) and image segmentation (based on spatial information). Multi-temporal MODIS images from ``normal'' (non-flood) and flood time-periods are processed in two steps. In the first step, image classifiers such as Support Vector Machines (SVMs) and Artificial Neural Networks (ANNs) separate the image pixels into water and non-water groups based on their spectral features. The classified image is then segmented using spatial features of the water pixels to remove the misclassified water. From the results obtained, we evaluate the performance of the method and conclude that the use of image classification (SVM and ANN) and region-based image segmentation is an accurate and reliable approach for the extraction of water-covered regions. (c) 2012 COSPAR. Published by Elsevier Ltd. All rights reserved.
|Item Type:||Journal Article|
|Additional Information:||Copyright for this article belongs to ELSEVIER SCI LTD, ENGLAND|
|Keywords:||MODIS image;Flood assessment;Image classification;Image segmentation;Support Vector Machine;Artificial Neural Network|
|Department/Centre:||Division of Mechanical Sciences > Aerospace Engineering (Formerly, Aeronautical Engineering)|
|Date Deposited:||07 Jan 2013 10:26|
|Last Modified:||07 Jan 2013 10:27|
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