The aim of this study is to identify the main factors of anthropogenic impact and indicators of landscape transformation in the Fatala River Basin in the Republic of Guinea. Our fieldwork in the Boke and Kindia regions was the main source of materials and data. The landscape and ecological situation of nine key study plots were characterized. These key plots make up a representative series of transformed and natural landscapes. We complemented our fieldwork with Landsat satellite image analysis. We learned that the main factors of anthropogenic impact in the Fatala River Basin are the systematic burning of vegetation, mechanical disturbances of soil and vegetation cover, the depletion of fertile topsoil, grazing, and the littering of the landscape with household waste. The indicators of landscape transformation are deforestation, changes in the natural vegetation cover, and mechanically disturbed lands. We identified five main stages of agro-landscape development, starting from the clearing of a plot by burning vegetation (stage I) and ending with the completion of the agricultural activity in the plot and its abandonment to restore the topsoil (stage V). The limiting factors of nature management are elevation differences, the rapid restoration of vegetation cover, and rocky/gravelly substrate. It is possible to identify transformed landscapes in large or hard-to-reach regions using satellite images. Thus, natural or quasi-natural landscapes can be identified based on the lower surface temperature relative to the surrounding lands. The normalized difference vegetation index (NDVI) and normalized difference moisture index (NDMI) could be useful for identifying agricultural pasture plots within a tropical forest using long-term satellite data series. We revealed a tendency for landscape deterioration in the middle and upper parts of the Fatala River Basin, while vegetation cover is being restored in the lower part of the basin. Finally, we propose some measures to rehabilitate transformed landscapes and increase the efficiency of agricultural production in the study region.