Using “Local Climate Zones” to Detect Urban Heat Island on Two Small Cities in Alabama

Abstract

Classifying “urban” and “rural” environments is a challenge in understanding urban climate, specifically urban heat islands (UHIs). Stewart and Oke developed the “local climate zone” (LCZ) classification system to clarify these distinctions using 17 unique groups. This system has been applied to many areas around the world, but few studies have attempted to utilize them to detect UHI effects in smaller cities. Our aim was to use the LCZ classification system 1) to detect UHI in two small cities in Alabama and 2) to determine whether similar zones experienced similar intensity or magnitude of UHIs. For 1 week, we monitored hourly temperature in two cities, in four zones: compact low-rise, open low-rise, dense forests, and water. We found that urban zones were often warmer for overall, daytime, and nighttime temperatures relative to rural zones (from −0.1° to 2.8°C). In addition, we found that temperatures between cities in similar zones were not very similar, indicating that the LCZ system does not predict UHI intensity equally in places with similar background climates. We found that the LCZ classification system was easy to use, and we recognize its potential as a tool for urban ecologists and urban planners.

The spatiotemporal dynamics of urbanisation and local climate: A case study of Islamabad, Pakistan

“…The WUDAPT procedure has emerged as a widely used methodology in several studies for mapping LCZs. A study conducted in Alabama, USA, followed the WUDAPT procedure by using the Landsat images from United States Geological Survey (USGS) and training areas from Google Earth (Chieppa et al, 2018). The same methodology was used for Harare, Zimbabwe (Mushore, 2019), and Yogyakarta, Indonesia (Pradhesta et al, 2019).…”

A global map of local climate zones to support earth system modelling and urban-scale environmental science

“…Since the LCZ typology was initially designed for urban temperature studies (Stewart and Oke, 2012), typical applications focus on the UHI, usually providing the context for designing and analysing observations from urban meteorological networks (Skarbit et al, 2017;Beck et al, 2018;Chieppa et al, 2018;Verdonck et al, 2018;Yang et al, 2018;Leconte et al, 2020;Milošević et al, 2021;Zong et al, 2021), from crowd-sourced data (Fenner et al, 2017;Varentsov et al, 2021;Fenner et al, 2021;Potgieter et al, 2021;Brousse et al, 2022), or from remote sensing (Wang and Ouyang, 2017;Bechtel et al, 2019b;Eldesoky et al, 2021;Stewart et al, 2021). However, the typology has been used for other purposes (see also Lehnert et al, 2021, for European applications), such as urban heat (risk) assessment studies (Verdonck et al, 2019b;Van de Walle et al, 2022), climate-sensitive design, land use/land cover change, urban planning (policies) (Perera and Emmanuel, 2018;Aminipouri et al, 2019;Vandamme et al, 2019;Maharoof et al, 2020;Chen et al, 2021b;Zhi et al, 2021), anthropogenic heat, building energy demand and consump-tion, carbon emissions (Wu et al, 2018;Santos et al, 2020;Yang et al, 2020;Benjamin et al, 2021;Kotharkar et al, 2022), quality of life (Sapena et al, 2021), urban ventilation (Z.…”

The Spatial and Temporal Characteristics of Urban Heat Island Intensity: Implications for East Africa’s Urban Development

“…This suggests that these already intensified SUHIs will become more complicated. The important role of climate conditions and their diurnal variations in SUHI intensity should not be ignored [6,61] but the changes are also inadequately explained by a focus on climate zones alone.…”