Forest Cover Change Assessment in the Sangu River Basin Using Sentinel-2 Satellite Data

Abstract

Abstract Forest covers are changing at an alarming rate, in particular to the tropics, emphasizing the need for continuous forest monitoring using satellite technology. Forest cover change in the Sangu River Basin in the Chittagong Hill Tracts (CHT), Bangladesh is typically missing and this study aims to fill the gap by applying a suitable methodology for mapping forest cover change in the area using Sentinel-2 satellite images. Maximum Likelihood, Minimum Distance, Support Vector Machine, and Random Forest classification methods were examined and Minimum Distance Classification Algorithm was chosen for mapping forest cover. Forest cover maps of 2016 and 2020 and forest cover change map of 2016–2020 were prepared. The accuracy of image classification was assessed with 300 random points; overall accuracy of classification was 91.7% and 94.7% for 2016 and 2020 satellite images, respectively. The study revealed that the major Land Use and Land Cover (LULC) classes remained stable over the study period (2016–2020) with a total area of 98.2 thousand ha. Among these classes, forest area is extended over 46.4 thousand ha (37.5%) and shrub classes cover around 45.7 thousand ha (37.0%). The change classes comprise 23.2 thousand ha (20.6%), with the largest conversion class being forest to shrubs or forest to bare land representing deforestation, which is around 17.7 thousand ha (around 14.3%). Shifting cultivation is identified as the major driver of forest cover change in the region. This process has converted many areas of CHT into shrub-dominated areas. The result of the study can assist local forest managers in combating deforestation and conserving the remaining forest in the region.