Identifying Spatial Heterogeneity in LCZ Impacts on SUHII and Corresponding Planning Strategies Using Coupled Spatial Autocorrelation and GWR Models: A Case Study of Berlin.

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Title: Identifying Spatial Heterogeneity in LCZ Impacts on SUHII and Corresponding Planning Strategies Using Coupled Spatial Autocorrelation and GWR Models: A Case Study of Berlin.
Authors: Xie, Changkun1 (AUTHOR) xiechangkun@sjtu.edu.cn, Yan, Mengling1,2 (AUTHOR), Afshari, Afshin1,2 (AUTHOR), Cao, Yuheng1,2 (AUTHOR), Qin, Yifeng1 (AUTHOR), Che, Shengquan1 (AUTHOR)
Source: Remote Sensing. Jun2026, Vol. 18 Issue 12, p1989. 22p.
Subjects: Urban heat islands, Spatial analysis (Statistics), Zoning, Regression analysis, Cities & towns, Climatic zones
Geographic Terms: Berlin (Germany), Germany
Abstract: Highlights: A coupled framework of spatial autocorrelation and GWR is proposed for SUHII analysis. An inverse urban–suburban gradient of LCZ thermal effects is newly identified. Three thermal zones of Berlin are quantitatively divided with distinct thermal gradients. A zoning-based regulation system is established for urban thermal governance. The urban heat island (UHI) effect has become a global environmental challenge, and quantifying the spatial heterogeneity of its driving mechanisms while developing differentiated regulation strategies remains a critical research gap. This study takes Berlin, Germany as a case study, integrating spatial autocorrelation analysis with a coupled geographically weighted regression (GWR) model to systematically investigate the spatial heterogeneity of the driving mechanisms of Local Climate Zones (LCZs) on surface urban heat island intensity (SUHII), and proposes refined regulation strategies. First, the WUDAPT method was employed to generate a LCZ map, and global and local Moran's I were used to identify SUHII spatial clustering characteristics, dividing the study area into High–High (HH), Low–Low (LL), and Not Significant (NS) clustering zones. Second, Ordinary Least Squares (OLS) and GWR coupled models were constructed to analyze the global and local relationships between LCZ composition and SUHII. The results indicate: (1) Berlin's SUHII exhibits significant spatial clustering characteristics (Moran's I = 0.984), with clear differentiation between the HH zone (25.8%, mean 2.67 °C) and the LL zone (26.4%, mean −0.16 °C); (2) the GWR model (R2 = 0.921, AICc = 1279.538) significantly outperforms the OLS model (R2 = 0.822, AICc = 2871.608), confirming strong spatial heterogeneity in the LCZ-SUHII relationship, with more pronounced advantages of GWR in urban–rural fringe areas; (3) LCZ 5 (low-density mid-rise buildings) and LCZ 2 (high-density mid-rise buildings) are key warming factors across the entire study area, but their warming effects are stronger in suburban areas than in central urban areas; LCZ A (dense trees) and LCZ G (water bodies) are key cooling factors across the entire area, but their cooling effects are stronger in central urban areas than in the suburbs. Based on these findings, this study establishes a differentiated strategy framework of "Zoning—Identifying Heterogeneity—Regulating", proposing that HH zones should implement "carbon sink enhancement and source reduction", NS zones should balance "ecological expansion with growth management", and LL zones should adopt "strict protection and development restriction". This framework provides a quantifiable scientific basis and practical guidance for refined urban thermal environment management. [ABSTRACT FROM AUTHOR]
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Abstract:Highlights: A coupled framework of spatial autocorrelation and GWR is proposed for SUHII analysis. An inverse urban–suburban gradient of LCZ thermal effects is newly identified. Three thermal zones of Berlin are quantitatively divided with distinct thermal gradients. A zoning-based regulation system is established for urban thermal governance. The urban heat island (UHI) effect has become a global environmental challenge, and quantifying the spatial heterogeneity of its driving mechanisms while developing differentiated regulation strategies remains a critical research gap. This study takes Berlin, Germany as a case study, integrating spatial autocorrelation analysis with a coupled geographically weighted regression (GWR) model to systematically investigate the spatial heterogeneity of the driving mechanisms of Local Climate Zones (LCZs) on surface urban heat island intensity (SUHII), and proposes refined regulation strategies. First, the WUDAPT method was employed to generate a LCZ map, and global and local Moran's I were used to identify SUHII spatial clustering characteristics, dividing the study area into High–High (HH), Low–Low (LL), and Not Significant (NS) clustering zones. Second, Ordinary Least Squares (OLS) and GWR coupled models were constructed to analyze the global and local relationships between LCZ composition and SUHII. The results indicate: (1) Berlin's SUHII exhibits significant spatial clustering characteristics (Moran's I = 0.984), with clear differentiation between the HH zone (25.8%, mean 2.67 °C) and the LL zone (26.4%, mean −0.16 °C); (2) the GWR model (R2 = 0.921, AICc = 1279.538) significantly outperforms the OLS model (R2 = 0.822, AICc = 2871.608), confirming strong spatial heterogeneity in the LCZ-SUHII relationship, with more pronounced advantages of GWR in urban–rural fringe areas; (3) LCZ 5 (low-density mid-rise buildings) and LCZ 2 (high-density mid-rise buildings) are key warming factors across the entire study area, but their warming effects are stronger in suburban areas than in central urban areas; LCZ A (dense trees) and LCZ G (water bodies) are key cooling factors across the entire area, but their cooling effects are stronger in central urban areas than in the suburbs. Based on these findings, this study establishes a differentiated strategy framework of "Zoning—Identifying Heterogeneity—Regulating", proposing that HH zones should implement "carbon sink enhancement and source reduction", NS zones should balance "ecological expansion with growth management", and LL zones should adopt "strict protection and development restriction". This framework provides a quantifiable scientific basis and practical guidance for refined urban thermal environment management. [ABSTRACT FROM AUTHOR]
ISSN:20724292
DOI:10.3390/rs18121989