Abstract:[Objective] Land use change and its influence factor analysis of river urban-Dexing City of Jiangxi Province in the process of rapid urbanization were explored, in order to provide scientific basis for the land use structure adjustment of river city and the development of similar river city experiencing rapid urbanization in China. [Methods] Based on the land use change data of remote sensing image of Dexing City from 2000 to 2014, the association degree between information entropy change of land use structure and related factors in Dexing City were analyzed using entropy model and grey correlation analysis. And on this basis, the dynamic correlations between information entropy change of land use structure and the main factors in Dexing City were further explained using impulse response function and variance decomposition of vector autoregressive model. [Results] (1) The areas of construction land, forest land, grassland, water, and other land-use types was decreasing, on the contrary, construction land area was rising. Moreover, the land use structure was in a disorderly development state, and the equilibrium of land use type was enhanced but the dominance of a single type was reduced. (2) According to the results of the impulse response function and variance decomposition analysis of VAR model, long-term total population, gross output of grain and urbanization level had positive effects on information entropy change of land use structure in Dexing City, and the impact effects gradually diminished and finally tended to be stable with time lag increased. Thereinto, total population and urbanization level had promoting effects on the information entropy change of land use structure in Dexing City, but the role of gross output of grain contributing to the degree of variance was declined with time going by. [Conclusoin] The degree of land use in Dexing City was not high. The land use structure was in a disorderly development state from 2000 to 2014. Total population, gross output of grain and urbanization level were the main factors influencing information entropy of land use structure.