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Multi-buffer zones reveal the relationship between spatial pattern of land surface temperature and land use indices in Guangzhou, China
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  • Published: 19 March 2026

Multi-buffer zones reveal the relationship between spatial pattern of land surface temperature and land use indices in Guangzhou, China

  • Zhoujiang Liu1,2,
  • Kai He2,
  • Zehua Ke2,4,
  • Litao Yuan2,
  • Yanqin Mao2 &
  • …
  • Yuning Zhang3 

Scientific Reports , Article number:  (2026) Cite this article

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We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content, and all legal disclaimers apply.

Subjects

  • Climate sciences
  • Ecology
  • Environmental sciences

Abstract

Land surface temperature is a crucial physical parameter in the examination of the natural ecological environment. The study utilized Landsat data to investigate land use indices and thermal environment change in Guangzhou, employing the radiative transfer equation, concentric circles, Pearson correlation coefficient, and other geospatial methods. Overall, as the distance from the city center increased, NDVI values tended to rise, while land surface temperature showed a gradual decreasing trend. Additionally, land surface temperature exhibited a negative correlation with NDVI and a positive correlation with NDBI. Barren had the highest LST, followed by impervious, while the water and the forest were cooler. The high-temperature area took on a V-shape, primarily situated in the west and southern areas, whereas the cooler temperature zone was mainly found in the northeast. The results can offer a scientific foundation for further exploration of the urban heat island formation mechanism, development of rational planning policies, and assessment of urbanization’s impact on local climate.

Data availability

The data that support the findings of this study are available from the corresponding author, upon reasonable request.

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Acknowledgements

We express our gratitude to anonymous reviewers and editors for their professional comments and suggestions.

Funding

This research was jointly supported by the Yunnan Provincial Basic Research (202301AT070084 and 202301AT070085), Western Yunnan University of Applied Sciences Talent Introduction Research Initiation Project (2023RCKY0001 and 2022RCKY0003), Breaking the Bottleneck of Teaching Resources: Infinite Simulation Scenario Generation and Practice for Autonomous Driving Based on AIGC and GIS (2026J1229), The Special Basic Cooperative Research Programs of Yunnan Provincial Undergraduate Universities’ Association: Research on the evaluation method of land ecosystem vulnerability in central Yunnan (202401BA070001-016).

Author information

Authors and Affiliations

  1. Institute of International Rivers and Eco-Security, Yunnan University, Kunming, China

    Zhoujiang Liu

  2. College of Surveying and Information Engineering, West Yunnan University of Applied Sciences, Dali, China

    Zhoujiang Liu, Kai He, Zehua Ke, Litao Yuan & Yanqin Mao

  3. Faculty of land and Resources Engineering, Kunming University of Science and Technology, Kunming, China

    Yuning Zhang

  4. College of Geography and Remote Sensing, HoHai university, Nanjing, China

    Zehua Ke

Authors
  1. Zhoujiang Liu
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  2. Kai He
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  3. Zehua Ke
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  4. Litao Yuan
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Contributions

Conceptualization and supervision, Z.L. and K.H.; methodology, Z.L. and K.H.; writing—original draft preparation, Z.L. and Z.K.; writing—review and editing, Z.L., K.H., Z.K., L.Y., Y.M., Y.Z.; validation, Z.L., Z.K. and K.H. All authors have read and agreed to the published version of the manuscript.

Corresponding author

Correspondence to Kai He.

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The authors declare no competing interests.

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Cite this article

Liu, Z., He, K., Ke, Z. et al. Multi-buffer zones reveal the relationship between spatial pattern of land surface temperature and land use indices in Guangzhou, China. Sci Rep (2026). https://doi.org/10.1038/s41598-026-44159-3

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  • Received: 08 January 2026

  • Accepted: 10 March 2026

  • Published: 19 March 2026

  • DOI: https://doi.org/10.1038/s41598-026-44159-3

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Keywords

  • Land surface temperature
  • Land use indices
  • Land use
  • Pearson correlation coefficient
  • Concentric circles
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