Search for a command to run...
Bangladesh’s forests are vital for maintaining biodiversity, supporting rural livelihoods, and contributing to climate resilience. However, they face growing challenges from agricultural expansion, population pressure, infrastructure development, and climate-induced hazards. While several reforestation and community afforestation programs have been initiated, the overall trend, spatial variability, and underlying drivers of forest cover change remain insufficiently understood. This study integrates remote sensing, machine learning, and socioeconomic analysis to examine the dynamics and determinants of forest land change across Bangladesh over a 19-year period (2000–2018).The study employs Landsat time-series imagery processed in Google Earth Engine. Random Forest classification generates annual land cover maps, followed by least-square trend modeling to detect forest growth rates. Hotspot and zonal statistical analyses will identify regions of significant change. Expert interviews, literature review, and secondary datasets will be used to examine drivers such as population pressure, shifting cultivation, community forestry programs, governance challenges, and climatic influences.Preliminary results show that the total forest area in Bangladesh increased at an average annual rate of 0.78% (approximately 25,932 hectares per year) between 2000 and 2018. However, this growth is spatially uneven. The study will provide a comprehensive understanding of how forests in Bangladesh are changing across different forest types and vital project areas for forest development, such as community afforestation and coastal greenbelt projects, several reserved forests, including the Chittagong Hill Tracts and parts of the Sundarbans; and what factors are driving these dynamics. Findings will inform national forest management, policy development, and sustainable land-use planning.