Comparative Analysis of Spatial Autocorrelation Models of Land Use Based on Different Weights——A Case Study of Yuanmou County
[Objective]To study the impact of different spatial weight matrices on the spatial correlation model of land use. [Method]Based on the land-use variables of the administrative village of Yuanmou County, this paper first analyzed the spatial autocorrelation of land-use types and their driving factors under different weight matrices, and established an algorithm based on the queen weight matrix, rook weight matrix and distance threshold weight matrix. Spatial autoregressive model for the evolution of the spatio-temporal pattern of cultivated land. Parame-ters such as goodness of fit, maximum likelihood logarithm, Akaike information criterion, Schwartz information criterion, number of influence factors and spatial autocorrelation of model residuals were selected as model evaluation indicators.The differences between the classic linear re-gression model, the spatial lag model and the spatial error model were compared and analyzed. [Result]In 2018, land use types and land use drivers in Yuanmou County showed a strong positive spatial correlation under different spatial weight matrices. By comparing the classic linear regression model, spatial lag model and spatial error model of the three weight matrices, it was found that in the same spatial autocorrelation model, the fitting effect of the spatial autoregressive model based on the distance threshold weight matrix was better; based on the same space, the weight matrix and the spatial error model fit better. [Conclusion]The spatial correlation was related to the spatial weight matrix. The spa-tial error model based on the distance threshold matrix had the best fitting degree and the strongest interpretation ability, which could better re-present the spatial evolution of the land use pattern in the mountainous plateau of Yunnan.
Land useSpatial weight matrixSpatial autocorrelationSpatial autoregression modelYuanmou County
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