Remote sensing is an important tool and technique for the best assessment of LULC map preparation and satellite image classification. This study emphasizes the classification of LULC of the adjacent lower zone area of the Subarnarekha River. To complete this study, ten such parameters have been considered, like Water-Body, Vegetation, Settlement, agricultural land area, Point Bar, Sand Bar, Sand Bank, Sand Dunes, Fishery Zone, and Mud-Bank Area at estuarine part of this river. Availability of Landsat images six specific years are sampled like 1998, 2004,2009,2014,2018 and 2022 respectively. The several factors have been consider including availability of quality Landsat imagery data through precise classification steps and users experience and expertise of the procedures. The objective of this study has been completed using the geospatial techniques like RS and GIS applications, which have compiled distinct two sections. First phase is containing Land-use and Land-cover (LULC) classification and, second phase is containing accuracy assessment of considered parameters. The Non-parametric Kappa coefficient Khat Statistic rule has applied for esteemed supervised classification with Kappa coefficient scale. The study had an overall classification accuracy of 86.75% and Kappa coefficient (K) of 0.911, 0.908, 0.719, 0.803, 0.858, and 0.886 following the considered study year. Overall accuracy through Khat Statistic reveals that vegetation, settlement, agricultural land, fishery and mud-bank are dominant parameters for the considered random samples. The revealed results are considerable and helpful for sustainable plan in future for this area.
International Journal of Geography, Geology and Environment
