Copyright : © the author(s), publisher and licensee Technoscience Academy. This is an open-access article distributed under the terms of the Creative Commons Attribution Non-Commercial License, which permits unrestricted non- commercial use, distribution, and reproduction in any medium, provided the original work is properly cited International Journal of Scientific Research in Science, Engineering and Technology Print ISSN: 2395-1990 | Online ISSN : 2394-4099 (www.ijsrset.com) doi : https://doi.org/10.32628/IJSRSET21817 26 Land Use/Land Cover Change Detection Study Using Remote Sensing and GIS Technique in Puthimari River Basin - A Transboundary Basin Between Bhutan and India Swapnali Barman* 1 , Jaivir Tyagi 2 , Waikhom Rahul Singh 1 *1 Centre for Flood Management Studies, Guwahati, National Institute of Hydrology, India 2 National Institute of Hydrology, Roorkee, India 1 Centre for Flood Management Studies, Guwahati, National Institute of Hydrology, India Article Info Volume 8 Issue 1 Page Number: 26-34 Publication Issue : January-February-2021 Article History Accepted : 08 Jan 2021 Published : 15 Jan 2021 ABSTRACT Using remote sensing and GIS technique, we analyse the change detection of different land use/land cover (LULC) types that has taken place in Puthimari river basin during a two-decade period from 1999 to 2019. Supervised classification method with maximum likelihood algorithm have been applied to prepare the LULC maps. The LULC change detection has been performed employing a post-classification detection method. Puthimari is a north bank sub-catchment of River Brahmaputra, the northern part of which falls in Bhutan and the rest falls in the Assam state of India. The primary LULC types of the basin are, dense vegetation which is predominant in the upper catchment, crop land and rural settlement. Thus, five different classes have been considered for the analysis, viz., dense vegetation, water bodies, silted water, cropland and rural settlement. The results showed that the rural settlement and water bodies in the basin increased by 42.70% and 30.31% from 1999 to 2019. However, dense vegetation, silted water and cropland decreased by 9.24%, 27.47% and 28.10% during these two decades. Keywords : Supervised classification, LULC, Maximum likelihood, Landsat, Puthimari, Change detection I. INTRODUCTION “Land use” and “land cover” are commonly termed as LULC that provide useful topographical information about the surface of the earth and the associated anthropogenic activities [1]. Assessment of LULC has become one of the most important parameters for proper and meaningful management of land resources. LULC changes are primarily driven by both natural phenomena and human activities, and are widespread and accelerating processes with obvious impact on the environment [2, 3]. LULC change detection is important as it is an indicator of climate change. Also, over a particular time period, the landscape dynamic of any area can be better understood with the help of such study.