Extraction of Spread Surface Water Body using Supervised and Unsupervised Classification Techniques
B. Chandrababu Naik1, B. Anuradha2
1B. Chandrababu Naik*, Research Scholar, Department of Electronics and Communication Engineering, S. V University College of Engineering, Tirupati, Andhra Pradhesh, India.
2Dr B. Anuradha**, Professor, Department of Electronics and Communication Engineering, S. V University College of Engineering, Tirupati, Andhra Pradhesh, India.
Manuscript received on March 16, 2020. | Revised Manuscript received on March 24, 2020. | Manuscript published on March 30, 2020. | PP: 2345-2350 | Volume-8 Issue-6, March 2020. | Retrieval Number: F8421038620/2020©BEIESP | DOI: 10.35940/ijrte.F8421.038620
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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: In this paper different classification techniques are applied to extract spread surface water area in the Nagarjuna sagar reservoir, Andhra Pradesh from Landsat-8 (OLI) image. In addition, the separability of reservoir features are tested to evaluate the thematic correctness of the classified data. This is to evaluate the application of a supervised and unsupervised classification techniques using the ERDAS software to extract the changes of surface water features for the period of 2014 to 2019. Furthermore, the statistical parameters are evaluated for the classification techniques. In supervised and unsupervised classification methods the minimum distance classifier gives better result (overall accuracy is 98.01%) than other classification methods. These obtained results are validated with ground truth data which is provided by Central Water-board Commission(CWC).
Keywords: Landsat-8, Surface Water Area, Supervised And Unsupervised Classifications.
Scope of the Article: Classifications.