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Journal of Engineering and Applied Sciences

ISSN: Online 1818-7803
ISSN: Print 1816-949x
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Water Feature Extraction, Enhancement and Change Detection Using Landsat-5 TM Multi Temporal Images by Image Fusion

M. Hemalatha and S. Varadarajan
Page: 5868-5872 | Received 21 Sep 2022, Published online: 21 Sep 2022

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Abstract

In this research letter, Urima lake satellite portrait is extracted and enhanced. Urima is 20th second largest lake and second largest saline lake in the world. There are several reasons that lead to shrinkage of this lake. The main cause is increasing salinity and decreasing surface water of the lake. Remote sensing derived indices such as Normalized Difference Water Index (NDWI)-method 1, Normalized Difference Vegetation Index (NDVI)-method 2, Normalized Difference Moisture Index (NDMI)-method 3, Modified Normalized Difference Water Index (MNDWI)-method 4, Water Ratio Index (WRI)-method 5 and Automated Water Extraction Index (AWEI )-method 6 were tested on surface water of Landsat-5 TM data. Out of all these remote sensing Indices, NDWI was found superior to model the spatiotemporal changes of Urima lake. Normalized Difference Water Index-Principle Component (NDWI-PC) and Modified Normalized Difference Water Index-Principle Component (MNDWI-PC) fusion is proposed for multi temporal surface water change detection. The surface water area of Urima lake is reduced from 2000-2010. The temporal changes of Lake Urima are implemented in this study. Accuracy assessment analysis is performed to show that proposed method is better than existing methods.


How to cite this article:

M. Hemalatha and S. Varadarajan. Water Feature Extraction, Enhancement and Change Detection Using Landsat-5 TM Multi Temporal Images by Image Fusion.
DOI: https://doi.org/10.36478/jeasci.2018.5868.5872
URL: https://www.makhillpublications.co/view-article/1816-949x/jeasci.2018.5868.5872