The rate at which forest ecosystems are lost and modified across tropical landscapes are alarming, yet proper documentation and proactive measures to curtail this still remains a huge challenge in most areas. This research focused on elucidating the ongoing land use change patterns of a riparian forest landscape, its current impacts on the ecosystem and land surface temperature, as well as its likely future scenarios for the zone. LANDSAT images were downloaded for 1988, 2003 and 2018 and used to show the dynamics for the zone, its drivers and their varying temperatures. Maximum Likelihood Classification algorithm was used for the classification and the land-use classes were categorized as: Water body, Farms and Sparse Vegetation, Built-up Areas, Bare Surface, and Thick Vegetation. Furthermore, Markov Chain Analysis was employed for understanding the future patterns of land use change in the zone. Land use categories experienced changes over the three epochs, but among all, farmlands/ sparse vegetation and thick vegetation had the most significant changes from 7.70 to 58.67 percent and 73.56 to 20.58 percent, respectively; implying that much of the forestland use/cover (which constituted the bulk of the land initially; 73.56 percent) were converted to agricultural land use. This same trend at which agriculture grew in the zone was seen to affect the land surface temperature for zone (Pearson correlation coefficient of 0.99 with p = 0.0058 at 0.05 level of significance). Future projection for the zone equally showed that agricultural land use will likely dominate the entire landscape in the coming years and a consequent impact on the climate and ecosystem expected as well. On that note, intensive agricultural practices that seek to maximize allocated farm units were advocated. Such initiatives will help to ensure that agricultural growth is contained within delimited zones so that haphazard cultivations, reductions in ecological value of the forest landscape and consequent climatic impacts could be managed across the region.