Temporal and Spatial Urban Heat Islands in a Coastal Brazilian Area of Tropical Climate

Abstract

This study explores the urban heat island (UHI) phenomenon in the Metropolitan Region of Vitória (MRV), Brazil. Two methods were employed: the traditional approach estimating the Atmospheric Urban Heat Island (UHI) using air temperature data, and the quantiles method assessing the Surface Urban Heat Island (SUHI) through medium spatial resolution images. The findings demonstrate the existence of an average heat island effect, as estimated by both UHI (+0.9 °C) and SUHI (+2.03 °C). The intensity of the atmospheric UHI is linked with higher air temperature values around midday. Additionally, the study reveals that UHI values in the MRV are more pronounced during spring and summer SUHI estimates peak during the summer months. The utilization of orbital remote sensing enables the identification of hotspots throughout the metropolitan area, with the highest temperatures observed in industrial areas, suburban neighborhoods, and densely populated regions. The advantage of the UHI method lies in its long time series, providing high temporal resolution and statistical significance over an extended period. Conversely, the SUHI method offers the advantage of considering data across the entire domain with high spatial resolution. Thus, these two methods complement each other in identifying the heat island phenomenon.

Keywords:

• UHI
• SUHI
• metropolitan region of Vitória
• land use and land cover
• air temperature
• thermal infrared sensor

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The authors acknowledge the support of Espírito Santo Research and Innovation Support Foundation (FAPES) by financing the project “Numerical and Observational Study of the Heat Island in the Metropolitan Region of Vitória” (PROCAP 2016). They also acknowledge the Bahia State Research and Support Foundation (FAPESB), and Espírito Santo Climate Study Institute (IEC). This work was also supported by the São Paulo Research Foundation (FAPESP - grants 2019/25701-8, and 2023/03206-0). We would like to thank the Coordination for the Improvement of Higher Education Personnel (CAPES).