Quantifying human impact on the environment is increasingly important and particularly so in complex mosaic landscapes. Such landscapes are prolific in the developing world, notably in West African, small holder cocoa farming communities. Human Appropriated Net Primary Productivity (HANPP) is a metric which has been developed to quantify the human impact on the environment and has been used in a number of studies globally. However, most operationalization's of HANPP have been done on a coarse global scale or a very local scale, and few studies exist of complex mosaic landscapes. This study utilizes Unmanned Autonomous Vehicles (UAV), or drones, to classify land use and HANPP for three cocoa farming regions in Ghana's Central Region. The results of the study indicate while all regions differ in land use composition, the primary crop for all is cocoa, followed by palm and then land that was previously cultivated which has been left fallow. The average HANPP was 44% for all measured regions, calculated using net primary productivity (NPP) values of an adjacent natural tropical forest. The HANPP for the three regions studied was found to be approximately 6.69, 8.00, and 9.85 Mg C ha−1 yr−1. These values are higher than those that have been reported in some widely accepted global studies, and highlight the need for more regional and landscape scale studies to supplement global assessments of HANPP.