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. |
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| 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] |
| Copyright of Remote Sensing is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
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| Header | DbId: egs DbLabel: Engineering Source An: 194915122 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Identifying Spatial Heterogeneity in LCZ Impacts on SUHII and Corresponding Planning Strategies Using Coupled Spatial Autocorrelation and GWR Models: A Case Study of Berlin. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Xie%2C+Changkun%22">Xie, Changkun</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> xiechangkun@sjtu.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Yan%2C+Mengling%22">Yan, Mengling</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Afshari%2C+Afshin%22">Afshari, Afshin</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Cao%2C+Yuheng%22">Cao, Yuheng</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Qin%2C+Yifeng%22">Qin, Yifeng</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Che%2C+Shengquan%22">Che, Shengquan</searchLink><relatesTo>1</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Remote+Sensing%22">Remote Sensing</searchLink>. Jun2026, Vol. 18 Issue 12, p1989. 22p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Urban+heat+islands%22">Urban heat islands</searchLink><br /><searchLink fieldCode="DE" term="%22Spatial+analysis+%28Statistics%29%22">Spatial analysis (Statistics)</searchLink><br /><searchLink fieldCode="DE" term="%22Zoning%22">Zoning</searchLink><br /><searchLink fieldCode="DE" term="%22Regression+analysis%22">Regression analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Cities+%26+towns%22">Cities & towns</searchLink><br /><searchLink fieldCode="DE" term="%22Climatic+zones%22">Climatic zones</searchLink> – Name: SubjectGeographic Label: Geographic Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Berlin+%28Germany%29%22">Berlin (Germany)</searchLink><br /><searchLink fieldCode="DE" term="%22Germany%22">Germany</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: 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] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Remote Sensing is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.3390/rs18121989 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 22 StartPage: 1989 Subjects: – SubjectFull: Urban heat islands Type: general – SubjectFull: Spatial analysis (Statistics) Type: general – SubjectFull: Zoning Type: general – SubjectFull: Regression analysis Type: general – SubjectFull: Cities & towns Type: general – SubjectFull: Climatic zones Type: general – SubjectFull: Berlin (Germany) Type: general – SubjectFull: Germany Type: general Titles: – TitleFull: Identifying Spatial Heterogeneity in LCZ Impacts on SUHII and Corresponding Planning Strategies Using Coupled Spatial Autocorrelation and GWR Models: A Case Study of Berlin. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Xie, Changkun – PersonEntity: Name: NameFull: Yan, Mengling – PersonEntity: Name: NameFull: Afshari, Afshin – PersonEntity: Name: NameFull: Cao, Yuheng – PersonEntity: Name: NameFull: Qin, Yifeng – PersonEntity: Name: NameFull: Che, Shengquan IsPartOfRelationships: – BibEntity: Dates: – D: 15 M: 06 Text: Jun2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 20724292 Numbering: – Type: volume Value: 18 – Type: issue Value: 12 Titles: – TitleFull: Remote Sensing Type: main |
| ResultId | 1 |
