Assessment of the Degradation of Teknaf Wildlife Sanctuary, Bangladesh: Use of Remote Sensing and Geographic Information System Techniques

The Teknaf Wildlife Sanctuary (TWS), situated in the southeastern part of Bangladesh, is a crucial forest biodiversity hotspot in Bangladesh currently having tremendous pressure due to various socioeconomic factors. The key objective of the study is to find out the degradation of the forest cover by land use and land cover (LULC) classification of TWS from 1991 to 2021 using Google Earth Engine (GEE) application programming interface (API)-based supervised classification approaches. The study used satellite and key informant interviews (KIIs) data to detect the forest landscape’s degradation and find the potential solution to combat the degradation. It also used ArcGIS spatial analysis tools for LULC change detection and mapping. The investigation found that the dense forest vegetation in the TWS decreased by 1389 ha from 1991 (4665 ha) to 2021 (3277 ha), which is 12% of the study area. Similarly, the agricultural land, covering 3.34% of TWS, decreased by 388 ha from 1991 to 2021. The human settlement, light forests, and built-up areas showed an increase of 8% (930 ha), 6% (694 ha), and 1.3% (148 ha), respectively, in the last three decades. Although the increment of the built-up area is small, it poses severe threats to the biodiversity and flow of ecosystem services from TWS. The KIIs indicated that the Rohingya influx, overexploitation by high population density, lack of mass awareness, illegal felling, expansion of human settlements, and fuelwood supply to the brick fields, factories, government and non-government organization’s offices and warehouses are abiotic drivers of forest degradation. At the same time, cyclones, reduced rainfall, and increased temperature were the natural causes. The study suggested measures to combat the degradation of the forest landscape, enabling policymakers to plan measures to retard further degradation of the TWS and conserve the threatened and rare species for reinstalling the ecosystem services.