<b>Assessing the spatiotemporal patterns of Robusta coffee (</b><b><i>Coffea canephora</i></b><b>) cropland expansion, associated land cover transformation, and driving forces in Uganda</b>

Land use and land cover (LULC) change is a key driver of global environmental transformation, influencing ecosystem integrity, agricultural productivity, and rural livelihoods. Understanding these dynamics is particularly critical for perennial cash crops such as coffee, which are sensitive to environmental and socioeconomic pressures. Robusta coffee (Coffea canephora), the dominant coffee species in Uganda, supports millions of smallholder farmers and contributes substantially to national export earnings. However, the rapid expansion of Robusta coffee cropland has led to significant land cover transformations, whose spatiotemporal patterns and driving forces remain inadequately understood. This study assessed Robusta coffee cropland expansion, associated LULC transformations, and their driving forces across Uganda’s main Robusta-growing regions from 1992 to 2022. LULC maps were produced for 1992, 2007, and 2022 using Sentinel-based remote sensing data and a pixel-based random forest (RF) classification, validated with ground truth data, achieving overall accuracies between 93.5 and 98.2%. Five vegetation indices (VIs), including the chlorophyll vegetation index, modified simple ratio, normalized difference vegetation index (NDVI), combination of chlorophyll absorption reflectance index (MCARI) and optimized soil-adjusted vegetation index (OSAVI), and Beison Datt vegetation index were also derived and used in the classification experiment. Results revealed a substantial expansion of Robusta coffee cropland, mixed agriculture and grasslands, and built-up areas, alongside a marked decline in natural forests and water bodies. Using the optimal parameter-based geodetector model, the human impact index and population density were identified as the dominant driving forces of land use intensity variations. These findings elucidate the spatiotemporal dynamics and underlying drivers of Robusta coffee landscape transformation, providing a robust scientific basis for sustainable land-use planning, ecological conservation, and climate-resilient coffee production strategies in Uganda.