Poyang Lake Basin is the biggest freshwater lake in China and a significant wetland of the world. The study of the land use changes on there is a great significance for regional sustainable development. In this paper, using the RS image as the main data source, the study area was divided into six land use types. With the acquired land use data of three periods, the spatio-temporal dynamic variation characteristics were analyzed with the area changes and land use dynamic index (LUDI). The analysis shows that the largest land use type is woodland, followed by cultivated land and grassland, and area of the rest types all account for less than 10%. Through the analysis of the area transfer matrix of LUCC, it shows that woodland and construction land increased in each period while cultivated land reduced. Unused land increased a lot during 1990 to 2000 before decreased dramatically during 2000 to 2008, grassland and water experienced a significant increase after an obvious decline and came out to increase finally. The analysis of LUDI indicates that construction land changed the most quickly, followed by unused land and cultivated land, yet the other land use types changed slowly.
Markov model is found to be beneficial in describing and analyzing land cover change process. The probability of transition between each pair of states is recorded as an element of a transition probability matrix, which is the key factor to obtain a higher precision of prediction in Markov model. In this study, a combined use of RS, GIS, Markov stochastic modeling and Monte Carlo simulating techniques are employed in analyzing and prediction land use/cover changes in Wuhan city. The results indicate that the transition probability matrix derived from Monte Carlo experiment is more accurate for land use prediction, and the prediction results of land use change show that there urban growth is has notable, area of forest land continued decreasing, and that the land use/cover change process would be stable in the future. The study demonstrates remote sensing image is an effective data source and statistical information of land use is a valid supplement for land use/land cover research. Integration of these two kinds of data in Markov - Monte Carlo method can adjust the basis of the same observation time when images are not available every year or at a constant time interval in LUCC modeling. Land use/land cover change information from the prediction results will be beneficial in describing, analyzing the change process of land structure in Wuhan city in next 20 years.