Sustainable Land Use Prediction in Light of Agroforestry Systems in Response to the Changing Scenario of Land Cover

Abstract

Change detection of land-cover to recommend the future directions of land-use is indispensable for sustainable development and the proper utilization of land resources. In this research, unsupervised classification maps produced using images of Landsat 8 OLI from 2013 until 2021 (with a 4-year interval) reveal important land-cover changes, along with their drivers, in Kapa-sia, Bangladesh. Overall, a substantial increase in paddy (24.7% to 27.2%) and urban (3.5% to 10.1%) and a decrease in homestead (67.5% to 59.3%) and forest (4.2% to 3.4%) were observed within the time interval. To direct the land-use towards long-term biodiversity and sustainability of the region, it is important to implement types of agroforestry systems as the observed decrease in homestead and forest areas are alarming. Agroforestry practices will not only have a positive environmental impact but can help diversify food systems, increase economic return and optimize natural resource use.