Identifying Surface Urban Heat Island Drivers and Their Spatial Heterogeneity in China's 281 Cities: An Empirical Study Based on Multiscale Geographically Weighted Regression

文献类型： 外文期刊

第一作者： Niu, Lu

作者： Niu, Lu;Zhang, Zhengfeng;Peng, Zhong;Jiang, Yazhen;Tang, Ronglin;Peng, Zhong;Jiang, Yazhen;Tang, Ronglin;Liang, Yingzi;Liu, Meng;Wei, Jing

作者机构：

关键词： SUHI; MODIS; driven factor; spatial heterogeneity; spatial scale; land use

期刊名称：REMOTE SENSING （ 影响因子：4.848； 五年影响因子：5.353 ）

ISSN：

年卷期： 2021 年 13 卷 21 期

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收录情况： SCI

摘要： The spatially heterogeneous nature and geographical scale of surface urban heat island (SUHI) driving mechanisms remain largely unknown, as most previous studies have focused solely on their global performance and impact strength. This paper analyzes diurnal and nocturnal SUHIs in China based on the multiscale geographically weighted regression (MGWR) model for 2005, 2010, 2015, and 2018. Compared to results obtained using the ordinary least square (OLS) model, the MGWR model has a lower corrected Akaike information criterion value and significantly improves the model's coefficient of determination (OLS: 0.087-0.666, MGWR: 0.616-0.894). The normalized difference vegetation index (NDVI) and nighttime light (NTL) are the most critical drivers of daytime and nighttime SUHIs, respectively. In terms of model bandwidth, population and & UDelta;fine particulate matter are typically global variables, while & UDelta;NDVI, intercept (i.e., spatial context), and NTL are local variables. The nighttime coefficient of & UDelta;NDVI is significantly negative in the more economically developed southern coastal region, while it is significantly positive in northwestern China. Our study not only improves the understanding of the complex drivers of SUHIs from a multiscale perspective but also provides a basis for urban heat island mitigation by more precisely identifying the heterogeneity of drivers.

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