Artículo

Research Overview on Urban Heat Islands Driven by Computational Intelligence

Resumen

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.
Autores
Ramirez, WG; Rio-Belver, RM; de Alegria, IM; Letzkus, CM
Título
Analysis of the Latin American scientific contribution to the electric vehicle issue
Afiliaciones
University of Basque Country; University of Basque Country; Universidad Catolica del Norte
Año
2021
DOI
10.37610/dyo.v0i75.610
Tipo de acceso abierto
hybrid
Referencia
WOS:000738340500005
Artículo obtenido de:
WOS
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