Land use Land Cover Change Detection using K-means Clustering and Maximum Likelihood Classification Method in the Javadi Hills, Tamil Nadu, India
M. Sam Navin1, L. Agilandeeswari2
1M. Sam Navin, Research Scholar, Department of Information Technology and Engineering, Vellore Institute of Technology, Vellore (Tamil Nadu), India.
2L. Agilandeeswari, Associate Professor, Department of Information Technology and Engineering, Vellore Institute of Technology, Vellore (Tamil Nadu), India.
Manuscript received on 14 December 2019 | Revised Manuscript received on 22 December 2019 | Manuscript Published on 31 December 2019 | PP: 51-56 | Volume-9 Issue-1S3 December 2019 | Retrieval Number: A10111291S319/19©BEIESP | DOI: 10.35940/ijeat.A1011.1291S319
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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: Land use/Land cover (LU/LC) change analysis is the present-day challenging task for the researchers in defining the environmental change across the world in the field of remote sensing and GIS (Geographic Information System). This paper analyzes the LU/LC changes between the years 2009 and 2019 in the region of Javadi Hills located in Tamil Nadu, India. Images from the Indian remote sensing satellite Resourcesat-1 LISS III and American earth observation satellite Landsat-8 were used for analyzing the LU/LC change for the study area. In this work, the classification was performed by using the hybrid approach of unsupervised and supervised classifiers. The classified LU/LC map for the study area defines forest and non-forest covered region. The key objective of this work was to identify the percentage of LU/LC change occurred in our study area for the years 2009 to 2014 and 2014 to 2019. Observing and examining the changes occurred in the study area provides a clear view to the land resources management to take effective measures in protecting the environment.
Keywords: Land Use/ Land Cover, Remote Sensing, GIS (Geographic Information System), Supervised and Unsupervised Classifiers, Accuracy Assessment, Change Analysis and Land Resource Management.
Scope of the Article: Clustering