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Identification of Thermal Environment Networks in the Wanjiang Urban Agglomeration Based on MSPA and Circuit Theory

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  • Yuexia Han

    (School of Resources and Environmental Management, Anhui Agricultural University, Hefei 230036, China
    School of Economics and Management, Anhui Agricultural University, Hefei 230036, China)

  • Bin Dong

    (School of Resources and Environmental Management, Anhui Agricultural University, Hefei 230036, China)

  • Zhili Xu

    (School of Resources and Environmental Management, Anhui Agricultural University, Hefei 230036, China)

  • Jianshen Qu

    (School of Resources and Environmental Management, Anhui Agricultural University, Hefei 230036, China)

  • Hao Wang

    (School of Resources and Environmental Management, Anhui Agricultural University, Hefei 230036, China)

  • Liwen Xu

    (School of Resources and Environmental Management, Anhui Agricultural University, Hefei 230036, China)

Abstract

With the acceleration of urbanization, the high density and intensity of urban construction and expansion have led to an exacerbation of the urban heat island (UHI) effect, which, in turn, contributes to global climate warming and severely impacts urban ecological environments and human health. This study takes the Wanjiang urban agglomeration as a case study. Using land surface temperature data from 2010, 2016, and 2022, the study employs the Morphological Spatial Pattern Analysis (MSPA) model to quantitatively identify the types and spatiotemporal distribution characteristics of heat island patches in the Wanjiang urban agglomeration. Based on this analysis, this study constructed thermal environment sources and heat island corridors, and applied circuit theory (CIRCUIT) to identify the spatial network of the thermal environment in the urban agglomeration. The results show that (1) from 2010 to 2022, seven types of heat island patches in the Wanjiang urban belt were identified by consensus, mainly distributed in the northwest and southeast, and their areas increased significantly. The dominant type of heat island patches changed from island type in 2010 to core type in 2022. (2) From 2010 to 2022, the number and area of urban thermal environment sources in Wanjiang increased. According to the thermal environment source distribution and circuit theory, the number of heat island corridors increased from 2010 to 2022. The pinch points of the heat island network in the Wanjiang urban agglomeration increased from 2010 to 2022, indicating that the ecosystem connectivity of the urban agglomeration had improved during the study period. Based on the circuit theory, the heat island network barrier points of the urban agglomeration from 2010 to 2022 are identified. (3) During 2010–2022, α, β, and γ increased with time, the overall connectivity of the thermal environment network in the Wanjiang urban agglomeration was enhanced, the heat transmission efficiency between source areas was gradually improved, and the high temperature threat degree to urban and rural residents was on the rise. This study provides an identification and assessment of the spatial network of the thermal environment in the Wanjiang urban agglomeration, offering valuable insights for understanding the thermal environment network pattern and mitigating the urban heat island effect in the region.

Suggested Citation

  • Yuexia Han & Bin Dong & Zhili Xu & Jianshen Qu & Hao Wang & Liwen Xu, 2024. "Identification of Thermal Environment Networks in the Wanjiang Urban Agglomeration Based on MSPA and Circuit Theory," Land, MDPI, vol. 13(10), pages 1-21, October.
  • Handle: RePEc:gam:jlands:v:13:y:2024:i:10:p:1695-:d:1500395
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    References listed on IDEAS

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    1. Shreevastava, Anamika & Rao, P. Suresh C. & McGrath, Gavan, 2019. "Emergent self-similarity and scaling properties of fractal intra-Urban Heat Islets for diverse global cities," Earth Arxiv t9s3g, Center for Open Science.
    2. Huaiyin Jiang & Gang He, 2023. "Analysis of Spatial and Temporal Evolution of Regional Water Resources Carrying Capacity and Influencing Factors—Anhui Province as an Example," Sustainability, MDPI, vol. 15(14), pages 1-19, July.
    3. Chao Wang & Zhijun Li & Haifeng Chen & Meibo Wang, 2023. "Comprehensive Evaluation of Agricultural Water Resources’ Carrying Capacity in Anhui Province Based on an Improved TOPSIS Model," Sustainability, MDPI, vol. 15(18), pages 1-16, September.
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