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

机译:基于BGWR模型的土地利用综合分析-以武汉市为例

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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.
机译:本文研究了2015年武汉市土地利用程度的空间分布。此外,分析了土地利用程度的空间自相关及其影响因素,包括人口密度,第一产业,第二产业,第三产业,道路密度和地形缓解度。 。从全球局部性的角度建立了空间自回归模型和贝叶斯地理加权回归(BGWR)。结果表明,土地利用程度及其影响因素之间存在显着的自相关性。 BGWR模型可以给出各种因素的局部参数,而空间回归模型可以估计变量的整体参数。在郊区,影响土地使用程度的因素存在明显差异,而在中心城区则差异不大。然后指出,土地利用综合指数可以受驱动因素控制,尤其是郊区,并为未来土地利用规划和城市规划提供了一系列参考指标。

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