Automatic Water Body Extraction using Multispectral Thresholding
K.P. Sivagami1, S.K. Jayanthi2
1K.P. Sivagami, Associate Professor, Department of Computer Science, JKK Nataraja College of Arts and Science, (Tamil Nadu), India.
2S.K. Jayanthi, Associate Professor, Department of Computer Science, Vellalar College for Women, (Tamil Nadu), India.
Manuscript received on 23 April 2019 | Revised Manuscript received on 02 May 2019 | Manuscript Published on 08 May 2019 | PP: 254-260 | Volume-7 Issue-5S3 February 2019 | Retrieval Number: E11480275S19/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Industrialization and urbanization lead to change in land use patterns and increase in utilization of water resources. Timely monitoring of surface water and delivering data on the dynamics of surface water are essential for policy and decision making processes. Change detection based on multispectral and multi temporal remote sensing data is one of the most acceptable and ever growing surface water change detection mechanisms in recent years. In this paper, a study has been conducted to detect the water bodies present in Erode region of Tamil Nadu based on Resourcesat-2 LISS-III November 2011 data using Normalized Difference Water Index and Thresholding based techniques. The result illustrates the effectiveness of the Bi-level Bi-stage Multispectral Thresholding approach for identification of water bodies and hence applied to detect the changes in water bodies during the period of 2011 to 2014.
Keywords: Bi-level Bi-Stage Multispectral Thresholding, Change Detection, Surface Water Body Extraction, Water Indices.
Scope of the Article: Underwater Sensor Networks