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. 2024 Nov 9;14(1):27375.
doi: 10.1038/s41598-024-78118-7.

Correlation analysis of landscape patterns and urban thermal environment in Kunming based on a panel data model

Ting Chen  1 , Zhibin Ren  2 , Yao Fu  3 , Chang Liu  4
Affiliations

Correlation analysis of landscape patterns and urban thermal environment in Kunming based on a panel data model

Ting Chen et al. Sci Rep. .

Abstract

With the development of urbanization, the spatial and temporal distribution characteristics of the urban landscape pattern play a decisive role in the intensity of the urban heat island (UHI) effect. A panel data model was constructed to study the relationship between the UHI effect and landscape pattern in Kunming from 1995 to 2020 at four different scales. The results indicate: (1) The landscape pattern of Kunming changed obviously with time, the artificial patch increased, the natural patch decreased, and the UHI effect became more and more obvious; (2) With an increase in scale, the number of influencing variables continues to grow, and the impact of artificial patches gradually intensifies; (3) The normalized difference water index (NDWI) has the greatest influence on the UHI, and the cooling effect is more obvious with the increase in scale. Unlike previous studies, the spatial configuration of the landscape in Kunming City had a stronger effect on the UHI effect than the landscape grouping and vegetation index; (4) This paper introduces the panel data model into the discussion of the UHI for the first time, providing a new method for better understanding the changing patterns of the urban thermal environment.

Keywords: Kunming; Landscape pattern; Panel data model; Urban heat island.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Location of the study area. The graph was created using ArcGIS10.7 (https://www.arcgis.com), The base map was from the standard map with review number GS (2022) 2764 downloaded from the website of Standard Map Service of the Ministry of Natural Resources, with no modification of the base map (http://bzdt.ch.mnr.gov.cn/).
Fig. 2
Fig. 2
Process of model selection.
Fig. 3
Fig. 3
Calculated changes in landscape index of each patch type in urban areas of Kunming at different scales (a: PD, b: PAFRAC, c: LPI, d: COHESION).
Fig. 4
Fig. 4
Landscape pattern index of landscape level at different spatial scales (1995–2020).
Fig. 5
Fig. 5
Instantaneous spatial pattern of thermal force field in Kunming (1995–2020).
Fig. 6
Fig. 6
Correlation coefficient graph.
Fig. 7
Fig. 7
Contribution rates of independent variables. ((a): 500 m × 500 m; (b): 1000 m × 1000 m; (c):1500 m × 1500 m; (d): 2000 m × 2000 m).
Fig. 8
Fig. 8
Predicted surface temperature map for the year 2020.
See this image and copyright information in PMC

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