Land Use and Land Cover Changes

Abstract

In the Bandarban district of Bangladesh, optical satellite imagery has been analyzed for the purpose of determining the spatial distribution of land use and land cover (LULC) categories, as well as the temporal changes that have occurred, and making predictions about those categories. This is the primary study area work in which multi-temporal Landsat imagery has been utilized to generate LULC maps for the years 1992, 2002, 2012, and 2022. The first part of the process consisted of deriving a total of six LULC categories through the integration of NDVI and supervise classification techniques. These categories also were evaluated through the use of the error matrix table and kappa statistics. Overall accuracy and Kappa statistic for all four years were both above 90%, according to the results of the accuracy assessment process. An exhaustive change analysis was performed with the help of the Land Change Modeler (LCM), and the results showed that significant shifts had occurred in the hilly forest, shrub land, and crop land categories between the years 1992 and 2022. From 1992 to 2022, hill forest decreased 74.41% to 46.66%, or 121504 hectares, while shrub land and cropland increased 16.48% to 43.61% and 5.26% to 7.39%, respectively. During the second stage of the process, Markov chain-cellular automata was utilized to model and make predictions regarding LULC in the study area. The Markov chain was used first to generate transition probability matrices between LULC categories, and then cellular automata was used to predict the LULC map for 2022 to validation. Afterwards, following the successful validation of the observed and predicted LULC maps for 2022 (approximately similar), the combined procedure was used to simulate land use and land-cover for 2052. The results of the simulation for the years 2022-2052 showed a significant rise in the amount of shrub land, crop land, and settlement area while there was a dramatic decrease in the amount of hilly forest, which dropped from 46.66% to 32.59%. All of these findings from the research could offer the opportunity for more skilled management and policy making in the study region regarding biodiversity, forests, land, and other environmental resources.land-cover for 2052. The results of the simulation for the years 2022-2052 showed a significant rise in the amount of shrub land, crop land, and settlement area while there was a dramatic decrease in the amount of hilly forest, which dropped from 46.66% to 32.59%. All of these findings from the research could offer the opportunity for more skilled management and policy making in the study region regarding biodiversity, forests, land, and other environmental resources.