Changes in cultivated land in China are related to food security for nearly 1.4 billion people. Administrative ruling has decomposed the goal of cultivated land protection in China and implemented it from top to bottom, so that cultivated land data have nested attributes. Although related research on cultivated land changes has achieved fruitful results, these studies have neglected the scale effect created by the nested structure of cultivated land data, and it is easy for the policy to lose its effect in scaling. A two-layer linear model of the hierarchical linear model is constructed in this paper based on spatial autocorrelation and scale variance analyses to analyse the different spatial scales for cultivated land changes and reveal the interaction mechanism of the driving factors at different spatial scales. The results show the following: (1) The smaller the spatial scale of the study area, the easier the spatial correlation of the cultivated land quantity distribution. (2) An analysis of the driving factors of cultivated land change in Chongqing finds that 33.80% of the differences are from the functional block scale and 66.20% are from the district or county scale. (3) We found that the spatial scale has a certain impact on the effectiveness of the driving factors of cultivated land changes. Large-scale driving factors will change the correlation between small-scale driving factors and cultivated land change. In the future, the problem of scale effects should be considered in the field of cultivated land management, the effects of different driving forces at various scales should be considered and the scientific decomposition of cultivated land protection tasks according to the spatial scale should be carried out to improve the efficiency of the protection of cultivated land.
Keywords: China; Cultivated land preservation; Cultivated land use change; Driving factors; Hierarchical linear models; Scale effect.