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Model simulation and scenario change analysis are the core contents of the future land-use change(LUC) study. In this paper, land use status data of the Three Gorges Reservoir Region(TGRR) in 1990 was used as base data. The relationship between driving factors and land-use change was analyzed by using binary logistic stepwise regression analysis, based on which land use in 2010 was simulated by CLUE-S model. After the inspection and determination of main parameters impacting on driving factors of land use in the TGRR, land use of this region in 2030 was simulated based on four scenarios, including natural growth, food security, migration-related construction and ecological conservation. The results were shown as follows:(1) The areas under ROC curves of land-use types(LUTs) were both greater than 0.8 under the analysis and inspection of binary logistic model. These LUTs include paddy field, dryland, woodland, grassland, construction land and water area. Therefore, it has a strong interpretation ability of driving factors on land use, which can be used in the estimation of land use probability distribution.(2) The Kappa coefficients, verified from the result of land-use simulation in 2010, were shown of paddy field 0.9, dryland 0.95, woodland 0.97, grassland 0.84, construction land 0.85 and water area 0.77. So the results of simulation could meet the needs of future simulation and prediction.(3) The results of multi-scenario simulation showed a spatial competitive relationship between different LUTs, and an influence on food security, migration-related construction and ecological conservation in the TGRR, including some land use actions such as the large-scale conversion from paddy field to dryland, the occupation on cultivated land, woodland and grassland for rapid expansion of construction land, the reclamation of woodland and grassland into cultivated land, returning steep sloping farmland back into woodland and grassland. Therefore, it is necessary to balance the needs of various aspects in land use optimization, to achieve the coordination between socio-economy and ecological environment.