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DOI	10.1016/j.buildenv.2022.109910
	Measuring the relationship between morphological spatial pattern of green space and urban heat island using machine learning methods
	Lin, Jinyao; Qiu, Suixuan; Tan, Xiujuan; Zhuang, Yaye
发表日期	2023
ISSN	0360-1323
EISSN	1873-684X
卷号	228
英文摘要	Land use pattern can substantially shape urban thermal environment. Although previous studies have shown that urban heat island (UHI) intensity will be easily affected by the landscape pattern of green space, the relationship between the morphological spatial pattern of green space and UHI intensity remains to be discovered. Compared with landscape pattern, morphological spatial pattern analysis (MSPA) can reveal more specific details on the configuration and composition of land use. Therefore, this study aims to explore whether the morphological spatial pattern of land use matters to UHI using machine learning methods. Firstly, the morphological characteristics of green space were analyzed based on MSPA. Secondly, the linear associations between UHI intensity and a set of potential influencing factors (including morphological characteristics) were measured according to correlation coefficient. Lastly, the non-linear contribution of the morphological factors to UHI intensity was quantified based on random forest. An empirical case study in a rapidly-urbanized city has revealed the huge influence of morphological characteristics on UHI intensity with benchmark factors considered. The UHI intensity was negatively correlated with the cores, perforations, and loops of green space, but positively correlated with islets. Therefore, a few large core areas would be better than a large number of small islets when the total amount of green space is fixed. In addition, the fragmented patches of green space should be integrated or connected to enhance the cooling capacity. Our findings could offer some insights for UHI mitigation and land use planning, especially when the size of green space cannot be unlimitedly increased.
英文关键词	Urban heat island; Morphological spatial pattern analysis; Green space; Environmental planning; Machine learning
语种	英语
WOS研究方向	Construction & Building Technology ; Engineering, Environmental ; Engineering, Civil
WOS类目	Science Citation Index Expanded (SCI-EXPANDED)
WOS记录号	WOS:000906312200001
来源期刊	BUILDING AND ENVIRONMENT
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/281043
作者单位	Guangzhou University; Guangzhou University
推荐引用方式 GB/T 7714	Lin, Jinyao,Qiu, Suixuan,Tan, Xiujuan,et al. Measuring the relationship between morphological spatial pattern of green space and urban heat island using machine learning methods[J],2023,228.
APA	Lin, Jinyao,Qiu, Suixuan,Tan, Xiujuan,&Zhuang, Yaye.(2023).Measuring the relationship between morphological spatial pattern of green space and urban heat island using machine learning methods.BUILDING AND ENVIRONMENT,228.
MLA	Lin, Jinyao,et al."Measuring the relationship between morphological spatial pattern of green space and urban heat island using machine learning methods".BUILDING AND ENVIRONMENT 228(2023).