International Journal of Electrical and Computer Engineering (IJECE) Vol. 8, No. 6, December 2018, pp. 4111~4119 ISSN: 2088-8708, DOI: 10.11591/ijece.v8i6.pp4111-4119  4111 Journal homepage: http://iaescore.com/journals/index.php/IJECE Extraction of Water-body Area from High-resolution Landsat Imagery B. Chandrababu Naik, B. Anuradha Department of Electronics and Communication, SVU College of Engineering, SV University, India Article Info ABSTRACT Article history: Received Apr 16, 2018 Revised Jul 10, 2018 Accepted Aug 2, 2018 Extraction of water bodies from satellite imagery has been broadly explored in the current decade. So many techniques were involved in detecting of the surface water bodies from satellite data. To detect and extracting of surface water body changes in Nagarjuna Sagar Reservoir, Andhra Pradesh from the period 1989 to 2017, were calculated using Landsat-5 TM, and Landsat-8 OLI data. Unsupervised classification and spectral water indexing methods, including the Normalized Difference Vegetation Index (NDVI), Normalized Difference Moisture Index (NDMI), Normalized Difference Water Index (NDWI), and Modified Normalized Difference Water Index (MNDWI), were used to detect and extraction of the surface water body from satellite data. Instead of all index methods, the MNDWI was performed better results. The Reservoir water area was extracted using spectral water indexing methods (NDVI, NDWI, MNDWI, and NDMI) in 1989, 1997, 2007, and 2017. The shoreline shrunk in the twenty-eight-year duration of images. The Reservoir Nagarjuna Sagar lost nearly around one-fourth of its surface water area compared to 1989. However, the Reservoir has a critical position in recent years due to changes in surface water and getting higher mud and sand. Maximum water surface area of the Reservoir will lose if such decreasing tendency follows continuously. Keyword: Index method Landsat MNDWI NDMI NDVI NDWI Surface water Copyright © 2018 Institute of Advanced Engineering and Science. All rights reserved. Corresponding Author: B. Chandrababu Naik, Department of Electronics and Communication, SVU College of Engineering, SV University, India. Email: babunaikb@gmail.com 1. INTRODUCTION The remote sensing knowledge is mainly used in different areas, such as the lake, coastal zone management, shoreline change and erosion monitoring, forest for monitoring of changes, forest and vegetation changes [1], [2], disaster monitoring [3], [4], flood prediction and evaluation of water resources [5]. It is essential for agriculture (food crops), day to day life of humans, and ecosystems [6]. To accomplish the information about open surface water is most important in different scientific areas, those are surface water analysis, watershed analysis, dynamic changes of rivers, environment monitoring, present and future estimations of water resources, and flood mapping [7]-[10]. Remote sensing satellites are having 30m resolutions and they offer a huge amount of data, which is widely used for detecting and extraction of surface water areas and its dynamic changes in recent decades [11]-[17]. Identification of water is very significant for various precise estimations and human life. To detecting and extraction of surface water area from satellite data has been introduced at many more image processing techniques in the current decades. A single-band and multi-band methods were widely used in Landsat imagery for detecting and extraction of surface water area along with selected threshold value, either positive or negative value [9]. Compared with a single-band method, multi-band method was extensively used for enhancing the surface water bodies [9]. Four different satellite multi-band methods were used for extraction of surface water bodies, those are water indexing methods, including the NDVI, NDMI, NDWI,