Research on the Spatio-Temporal Differentiation of Environmental Heat Exposure in the Main Urban Area of Zhengzhou Based on LCZ and the Cooling Potential of Green Infrastructure

Xu Huang, Lizhe Hou, Shixin Guan, Hongpan Li, Jombach Sándor, Fekete Albert, Filepné Kovács Krisztina and Huawei Li ()
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Xu Huang: College of Landscape Architecture and Art, Henan Agricultural University, Zhengzhou 450002, China
Lizhe Hou: College of Landscape Architecture and Art, Henan Agricultural University, Zhengzhou 450002, China
Shixin Guan: College of Landscape Architecture and Art, Henan Agricultural University, Zhengzhou 450002, China
Hongpan Li: College of Landscape Architecture and Art, Henan Agricultural University, Zhengzhou 450002, China
Jombach Sándor: Institute of Landscape Architecture, Urban Planning and Garden Art, Hungarian University of Agriculture and Life Sciences (MATE), 1118 Budapest, Hungary
Fekete Albert: Institute of Landscape Architecture, Urban Planning and Garden Art, Hungarian University of Agriculture and Life Sciences (MATE), 1118 Budapest, Hungary
Filepné Kovács Krisztina: Institute of Landscape Architecture, Urban Planning and Garden Art, Hungarian University of Agriculture and Life Sciences (MATE), 1118 Budapest, Hungary
Huawei Li: College of Landscape Architecture and Art, Henan Agricultural University, Zhengzhou 450002, China

Land, 2025, vol. 14, issue 9, 1-25

Abstract: Urban heat exposure has become an increasingly critical environmental issue under the dual pressures of global climate warming and rapid urbanization, posing significant threats to public health and urban sustainability. However, conventional linear regression models often fail to capture the complex, nonlinear interactions among multiple environmental factors, and studies confined to single LCZ types lack a comprehensive understanding of urban thermal mechanisms. This study takes the central urban area of Zhengzhou as a case and proposes an integrated “Local Climate Zone (LCZ) framework + random forest-based multi-factor contribution analysis” approach. By incorporating multi-temporal Landsat imagery, this method effectively identifies nonlinear drivers of heat exposure across different urban morphological units. Compared to traditional approaches, the proposed model retains spatial heterogeneity while uncovering intricate regulatory pathways among contributing factors, demonstrating superior adaptability and explanatory power. Results indicate that (1) high-density built-up zones (LCZ1 and E) constitute the core of heat exposure, with land surface temperatures (LSTs) 6–12 °C higher than those of natural surfaces and LCZ3 reaching a peak LST of 49.15 °C during extreme heat events; (2) NDVI plays a dominant cooling role, contributing 50.5% to LST mitigation in LCZ3, with the expansion of low-NDVI areas significantly enhancing cooling potential (up to 185.39 °C·km 2 ); (3) LCZ5 exhibits an anomalous spatial pattern with low-temperature patches embedded within high-temperature surroundings, reflecting the nonlinear impacts of urban form and anthropogenic heat sources. The findings demonstrate that the LCZ framework, combined with random forest modeling, effectively overcomes the limitations of traditional linear models, offering a robust analytical tool for decoding urban heat exposure mechanisms and informing targeted climate adaptation strategies.

Keywords: Local Climate Zone (LCZ); environmental heat exposure; Land Surface Temperature (LST); Normalized Difference Vegetation Index (NDVI); greening cooling potential (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2025
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