A Hierarchical Approach to Landform Classification of Satellite Images Using a Fusion Strategy
There is increasing need for effective delineation of meaningfully different landforms due to the decreasing availability of experienced landform interpreters. Any procedure for automating the process of landform segmentation from satellite images offer the promise of improved consistency and reliality. We propose a hierarchical method for landform classification for classifying a wide variety of landforms. At stage 1 an image is classified as one of the three broad categories of terrain types in terms of its geomorphology, and these are: desertic/rann of kutch, coastal or fluvial. At stage 2, all different landforms within either desertic/rann of kutch , coastal or fluvial areas are identified using suitable processing. At the final stage, all outputs are fused together to obtain a final segmented output. The proposed technique is evaluated on large number of optical band satellite images that belong to aforementioned terrain types.
KeywordsSupport Vector Machine Active Channel Alluvial Plain Hierarchical Approach Fusion Strategy
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- 1.Pennock, D.J., Zebarth, B.J., Dejong, W.: Landform classification and soil distribution in hummocky terrain, saskatchewan, canada. In: Proceedings of British Machine Vision Conference, Norwich, UK, pp. 297–315 (1987)Google Scholar
- 5.Ying Chen, Q., Yang, Q.: Segmentation of images using support vector machines. In: Proceedings of the third international conference on machine learning and cybernetics, Shanghai, pp. 3304–3306 (2004)Google Scholar
- 8.Haralick, Robert, M., Shapiro, G.L.: Computer and Robot Vision. Addison-wesley, Reading (1992)Google Scholar