This chapter provides a comprehensive overview of the concept, classification, and development of the urban thermal environment (UTE) and urban heat island (UHI) phenomena. It introduces the key distinctions between UTE and UHI in terms of definitions, climatic variables involved, and spatial characteristics. This chapter describes the multi-layered structure and diurnal dynamics of surface and canopy UHIs. It reviews the historical progression of urban climate research, summarizing milestone studies and advancements in observation and modeling techniques. Various methods of data acquisition, including field monitoring, remote sensing, and numerical modeling, are presented alongside recent developments in gap-filling and resolution enhancement techniques. This chapter also outlines approaches for measuring and mapping UHI intensity and discusses traditional statistical and emerging machine learning methods used to investigate influencing factors. In addition, it reviews inter-city and intra-city variations in surface UHI and explores the multiple spatial scales at which thermal heterogeneity and its drivers operate. This chapter builds a technical foundation for understanding urban thermal patterns.

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Research Progress of Urban Thermal Environment Studies

  • Liang Zhou,
  • Bo Yuan,
  • David López-Carr,
  • Fengning Hu

摘要

This chapter provides a comprehensive overview of the concept, classification, and development of the urban thermal environment (UTE) and urban heat island (UHI) phenomena. It introduces the key distinctions between UTE and UHI in terms of definitions, climatic variables involved, and spatial characteristics. This chapter describes the multi-layered structure and diurnal dynamics of surface and canopy UHIs. It reviews the historical progression of urban climate research, summarizing milestone studies and advancements in observation and modeling techniques. Various methods of data acquisition, including field monitoring, remote sensing, and numerical modeling, are presented alongside recent developments in gap-filling and resolution enhancement techniques. This chapter also outlines approaches for measuring and mapping UHI intensity and discusses traditional statistical and emerging machine learning methods used to investigate influencing factors. In addition, it reviews inter-city and intra-city variations in surface UHI and explores the multiple spatial scales at which thermal heterogeneity and its drivers operate. This chapter builds a technical foundation for understanding urban thermal patterns.