Abstract:[Objective] We aimed to reveal the regularity of spatial distribution of cultivated land by spatial autocorrelation analysis and multivariable regression, in order to provide a rapid evaluation method for land development, reclamation, and consolidation. [Methods] Coverage ratio by cultivated land was as response variable, and methods of spatial autocorrelation and mosaic plot were utilized to demonstrate its spatial pattern. Nine factors such as Euclidean distances, terrain, NDWI, population density, simulated cultivated land distribution suitability, etc. were used as independent variables, and multivariate regression of them with the response variable was conducted to test the distributional suitability of cultivated land. [Results] The Euclidean distances and terrain have significant impacts on the spatial distribution of cultivated land, and the Moran's I index is 0.701 5. In addition, the main types of local indicators of spatial association(LISA) distribution are not significant. L-L(low spatial autocorrelations) and H-H(high spatial autocorrelations) and insignificant types are three of the main types, especially the third type covered over 65% of study area. Multivariate regression behaved well in the distribution suitability simulation of cultivated land, it was remarkably coincided with the present distribution of cultivated land. The regression model was testified reliable and had goodness of fit (R2=0.846). [Conclusion] (1) The spatial distribution of cultivated land in the study area generally exhibits a strong positive correlation. And the distribution of cultivated land is affected by distance and terrain significantly. (2) The regression model can well reveal the spatial distribution of cultivated land in the study area, showing that the study area has a potential for cultivated land supplement. (3) We can improve the quality of additional cultivated land, reduce soil erosion, and optimize the land utilization structure if under the guidance of the regression model for land development, reclamation and consolidation.