Analysing patterns of forest cover change and related land uses in the Tano-Offin forest reserve in Ghana: Implications for forest policy and land management

• Forest cover change processes were analysed in a protected landscape. Machine learning image classification was implemented. Agricultural land increased more than the forest and developed land. targeted to greater extent. policy should incorporate monitoring of multiple factors. is major contributing factor global environmental change. Whereas several studies have focused on general use dynamics, we focus analysing patterns landscape taking into consideration how other categories are increasing at expense forest. In this study, analyse associated proximate factors between 1987 2017 using Landsat images from Tano-Offin Reserve (TOFR) Ghana. Using Random machine algorithm, classified forest, land, agricultural The study finds that losses 1.9 1.4 times amount gains 1987–2002 2002–2017, respectively. We find even though likely recover developers mostly Ghana's Wildlife Policy underlying process TOFR suggest country's combination diverse spatially explicit threaten integrity forests.