Research Overview on Urban Heat Islands Driven by Computational Intelligence

Chao Liu, Siyu Lu, Jiawei Tian, Lirong Yin (), Lei Wang and Wenfeng Zheng ()
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Chao Liu: School of Automation, University of Electronic Science and Technology of China, Chengdu 610054, China
Siyu Lu: School of Automation, University of Electronic Science and Technology of China, Chengdu 610054, China
Jiawei Tian: Department of Computer Science and Engineering, Hanyang University, Ansan 15577, Republic of Korea
Lirong Yin: Department of Geography & Anthropology, Louisiana State University, Baton Rouge, LA 70803, USA
Lei Wang: Department of Geography & Anthropology, Louisiana State University, Baton Rouge, LA 70803, USA
Wenfeng Zheng: School of Automation, University of Electronic Science and Technology of China, Chengdu 610054, China

Land, 2024, vol. 13, issue 12, 1-26

Abstract: In recent years, the intensification of the urban heat island (UHI) effect has become a significant concern as urbanization accelerates. This survey comprehensively explores the current status of surface UHI research, emphasizing the role of land use and land cover changes (LULC) in urban environments. We conducted a systematic review of 8260 journal articles from the Web of Science database, employing bibliometric analysis and keyword co-occurrence analysis using CiteSpace to identify research hotspots and trends. Our investigation reveals that vegetation cover and land use types are the two most critical factors influencing UHI intensity. We analyze various computational intelligence techniques, including machine learning algorithms, cellular automata, and artificial neural networks, used for simulating urban expansion and predicting UHI effects. The study also examines numerical modeling methods, including the Weather Research and Forecasting (WRF) model, while examining the application of Computational Fluid Dynamics (CFD) in urban microclimate research. Furthermore, we evaluate potential mitigation strategies, considering urban planning approaches, green infrastructure solutions, and the use of high-albedo materials. This comprehensive survey not only highlights the critical relationship between land use dynamics and UHIs but also provides a direction for future research in computational intelligence-driven urban climate studies.

Keywords: urban heat island effect; land use; vegetation index; computational intelligence; urban expansion simulation; heat island effect prediction (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:gam:jlands:v:13:y:2024:i:12:p:2176-:d:1543244

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