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Quantitative Analysis of a Spatial Distribution and Driving Factors of the Urban Heat Island Effect: A Case Study of Fuzhou Central Area, China

Author

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  • Meizi You

    (College of Forestry, Fujian Agriculture and Forestry University, Fuzhou 350002, China)

  • Riwen Lai

    (College of Forestry, Fujian Agriculture and Forestry University, Fuzhou 350002, China)

  • Jiayuan Lin

    (College of Forestry, Fujian Agriculture and Forestry University, Fuzhou 350002, China)

  • Zhesheng Zhu

    (School of Forestry, Northeast Forestry University, Harbin 150000, China)

Abstract

Land surface temperature (LST) is a joint product of physical geography and socio-economics. It is important to clarify the spatial heterogeneity and binding factors of the LST for mitigating the surface heat island effect (SUHI). In this study, the spatial pattern of UHI in Fuzhou central area, China, was elucidated by Moran’s I and hot-spot analysis. In addition, the study divided the drivers into two categories, including physical geographic factors (soil wetness, soil brightness, normalized difference vegetation index (NDVI) and modified normalized difference water index (MNDWI), water density, and vegetation density) and socio-economic factors (normalized difference built-up index (NDBI), population density, road density, nighttime light, park density). The influence analysis of single factor on LST and the factor interaction analysis were conducted via Geodetector software. The results indicated that the LST presented a gradient layer structure with high temperature in the southeast and low temperature in the northwest, which had a significant spatial association with industry zones. Especially, LST was spatially repulsive to urban green space and water body. Furthermore, the four factors with the greatest influence ( q -Value) on LST were soil moisture (influence = 0.792) > NDBI (influence = 0.732) > MNDWI (influence = 0.618) > NDVI (influence = 0.604). The superposition explanation degree (influence (Xi ∩ Xj)) is stronger than the independent explanation degree (influence (Xi)). The highest and the lowest interaction existed in ”soil wetness ∩ MNDWI” (influence = 0.864) and “nighttime light ∩ population density” (influence = 0.273), respectively. The spatial distribution of SUHI and its driving mechanism were also demonstrated, providing theoretical guidance for urban planners to build thermal environment friendly cities.

Suggested Citation

  • Meizi You & Riwen Lai & Jiayuan Lin & Zhesheng Zhu, 2021. "Quantitative Analysis of a Spatial Distribution and Driving Factors of the Urban Heat Island Effect: A Case Study of Fuzhou Central Area, China," IJERPH, MDPI, vol. 18(24), pages 1-19, December.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:24:p:13088-:d:700286
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    References listed on IDEAS

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    2. Taher Safarrad & Mostafa Ghadami & Andreas Dittmann, 2022. "Effects of COVID-19 Restriction Policies on Urban Heat Islands in Some European Cities: Berlin, London, Paris, Madrid, and Frankfurt," IJERPH, MDPI, vol. 19(11), pages 1-25, May.

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