摘要
城市形态能够显著影响城市的热岛强度成为学界的共识,新兴的多尺度地理加权回归弥补了传统的地理加权回归模型中所有变量带宽一致的局限,可在分析各形态指标与热岛强度相关性的基础上分析其影响的尺度差异。文章利用多源数据,以街区为基本单元,基于MGWR分析广州主城区街区形态指标与热岛强度之间的关系,结果表明:①广州主城区的日间热岛状况以夏秋季尤为严重,超过95%的街区出现不同程度的热岛效应;②在四季UHII相关性分析中,MGWR的模型性能均优于GWR,表明各形态指标与UHII关系具有空间非平稳性特征,且不同形态指标的影响具有尺度差异;③各形态指标与UHII相关性具有季节差异、空间差异特征,不同季节、不同区位均会影响指标与UHII的相关方向、相关程度。基于以上结果,文章建议在开展以缓解热岛效应为导向的城市设计及空间规划时,对街区的形态优化应注重季节针对性、空间针对性和指标针对性。
Urban morphology can significantly affect the urban heat island intensity,which has become a consensus in the academic world.The emerging multi-scale geographic weighted regression makes up for the limitation of the same bandwidth of all variables in the traditional geographic weighted regression model.It can analyze the scale difference of the impact of various morphological indicators on the basis of analyzing the correlation between the heat island intensity.Based on MGWR,this paper analyzes the relationship between block morphology index and heat island intensity in Guangzhou urban area by using multi-source data and block as the basic unit.The results show that:①The daytime UHI in the main urban area of Guangzhou is particularly serious in summer and autumn,exceeding 95%of the blocks have different degrees of heat island effect;②In the correlation analysis of UHII in four seasons,the model performance of MGWR is better than GWR,indicating that the relationship between various morphological indexes and UHII has the characteristics of spatial nonstationarity,and the effects of different morphological indexes had scale difference;③The correlation between each morphological index and UHII has seasonal and spatial differences.Different seasons and different locations will affect the direction and degree of correlation between the indexes and UHII.Based on the above results,this article suggests that when carrying out urban design and spatial planning oriented to alleviate the heat island effect,the shape optimization of the block should pay attention to seasonal pertinence,spatial pertinence and indexes pertinence.
作者
陈卓伟
邓昭华
CHEN Zhuo-wei;DENG Zhao-hua(School of Architecture,South China University of Technology)
出处
《智能建筑与智慧城市》
2021年第10期13-17,共5页
Intelligent Building & Smart City
关键词
多尺度地理加权回归
街区形态
热岛强度
广州
multi-scale geographic weighted regression
block morphology
urban heat island intensity
Guangzhou