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My dissertation examines the Land Use and Land Cover (LULC) change impacts of major employers locating in small towns and rural areas both spatially and temporally at a regional scale. Major employer location has for decades been considered a powerful tool for economic development in small towns and rural areas, however, the impacts of such employers in instigating development activities and LULC changes are rarely evaluated even though they are acknowledged in the literature. Using the case study of the Toyota plant location near Georgetown in rural Scott County, this research develops Cellular Automata and Markov Chain Analysis (CA_MCA) based LULC change models to assess the Toyota plant impacts within 9 counties adjoining Scott from the 1980s to 2000s. The influence of a set of local socio-economic, geographic, biophysical, and land use control factors that drive LULC changes are also incorporated in the models.Two LULC change scenarios – Scenario 1 and 2 – are developed to estimate the LULC changes as impacted by the plant and understand the process of development over time and space. Scenario 1 is developed with LULC and other datasets from the pre-Toyota phase to predict the LULC changes in the region in absence of the plant, and then the predicted images are compared with the actual ones to estimate the plant impacts. Scenario 2 is developed with datasets from the post-Toyota phase to understand the changing influence of the plant in the region over time. The significance of this research is that it applies advanced methodologies for assessment of LULC changes that often occur in small towns and rural areas following large-scale economic development projects, and can assist planners and policy makers with better understanding of locations and time-frames of LULC changes so that valuable land resources can be efficiently developed, managed or protected in sustainable ways.