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Title: Colour transformed clustering-based water body extraction using IRS-1C LISS III image

Authors: Rubina Parveen; Subhash Kulkarni; V.D. Mytri

Addresses: Research Resource Centre, Visvesvaraya Technological University, Belagavi, India ' P.E.S. Institute of Technology, Bengaluru (South Campus), India ' APPA Institute of Engineering and Technology, Sharan Nagar, Kalaburagi, Karnataka, India

Abstract: The algorithm presented in this research article extracts and delineates the water areas using IRS-1C LISS III images. Methods available in the literature are biased with user-defined thresholds. The objective of the proposed algorithm is to provide accurate information about surface water. Initially, the input image is subjected to colour transformation clustering to extract all the similar hydrological characteristics geo-spatial features in the picture. Every cluster is then submitted to surface water detection by considering spectral information. Finally, the surface water bodies are outlined with sharp inter-regional boundaries and made visually vibrant. Thus the task of identification of water bodies is made simple, accurate and easy for the user with satisfactory qualitative analysis. Results obtained are compared with statistics obtained by structural filtering, NDVI method, and spectral segmentation method. The excellent potential surface water areas can be extracted by using the proposed method.

Keywords: colour transformed clustering; LISS III data; normalised difference water index.

DOI: 10.1504/IJSTDS.2019.097609

International Journal of Spatio-Temporal Data Science, 2019 Vol.1 No.1, pp.84 - 97

Received: 18 Nov 2017
Accepted: 11 Apr 2018

Published online: 31 Jan 2019 *

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