Comprehensive degree of land use analysis based on BGWR model: A case study of Wuhan

This paper studied the spatial distribution of Wuhan land use degree in 2015. In addition, the spatial autocorrelation of land use degree and its impact factors were analyzed, including population density, primary industry, secondary industry, tertiary industry, road density and terrain relief degree. A spatial autoregressive model and Bayesian Geographically Weighted Regression (BGWR) was established from the perspective of global local. The results showed that there was a significant autocorrelation in land use degree and its impact factors. BGWR model could give the local parameter of various factors while spatial regression model could estimate the overall parameter of variables. There is clear difference of influencing factors to land use degree in sub-urban, and small difference in the central urban area. Then, it points out the land use comprehensive index could be controlled by the driving factors, especially for suburban region and provided a series of reference indicators for future land use planning and urban planning.