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Review

Urban Heat Island and Its Regional Impacts Using Remotely Sensed Thermal Data—A Review of Recent Developments and Methodology

1
ASRC Federal Data Solutions (AFDS), Contractor to the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center, Sioux Falls, SD 57198, USA
2
U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center, Sioux Falls, SD 57198, USA
3
Center for Satellite Applications and Research, National Oceanic and Atmospheric Administration (NOAA)/NESDIS, College Park, MD 20740, USA
*
Author to whom correspondence should be addressed.
Academic Editors: Sara Venafra, Carmine Serio and Guido Masiello
Land 2021, 10(8), 867; https://doi.org/10.3390/land10080867
Received: 17 July 2021 / Revised: 10 August 2021 / Accepted: 11 August 2021 / Published: 18 August 2021
(This article belongs to the Special Issue Land Surface Monitoring Based on Satellite Imagery)
Many novel research algorithms have been developed to analyze urban heat island (UHI) and UHI regional impacts (UHIRIP) with remotely sensed thermal data tables. We present a comprehensive review of some important aspects of UHI and UHIRIP studies that use remotely sensed thermal data, including concepts, datasets, methodologies, and applications. We focus on reviewing progress on multi-sensor image selection, preprocessing, computing, gap filling, image fusion, deep learning, and developing new metrics. This literature review shows that new satellite sensors and valuable methods have been developed for calculating land surface temperature (LST) and UHI intensity, and for assessing UHIRIP. Additionally, some of the limitations of using remotely sensed data to analyze the LST, UHI, and UHI intensity are discussed. Finally, we review a variety of applications in UHI and UHIRIP analyses. The assimilation of time-series remotely sensed data with the application of data fusion, gap filling models, and deep learning using the Google Cloud platform and Google Earth Engine platform also has the potential to improve the estimation accuracy of change patterns of UHI and UHIRIP over long time periods. View Full-Text
Keywords: urban heat island; UHI regional impacts; non-urban areas; remote sensing; thermal band; UHI intensity urban heat island; UHI regional impacts; non-urban areas; remote sensing; thermal band; UHI intensity
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MDPI and ACS Style

Shi, H.; Xian, G.; Auch, R.; Gallo, K.; Zhou, Q. Urban Heat Island and Its Regional Impacts Using Remotely Sensed Thermal Data—A Review of Recent Developments and Methodology. Land 2021, 10, 867. https://doi.org/10.3390/land10080867

AMA Style

Shi H, Xian G, Auch R, Gallo K, Zhou Q. Urban Heat Island and Its Regional Impacts Using Remotely Sensed Thermal Data—A Review of Recent Developments and Methodology. Land. 2021; 10(8):867. https://doi.org/10.3390/land10080867

Chicago/Turabian Style

Shi, Hua, George Xian, Roger Auch, Kevin Gallo, and Qiang Zhou. 2021. "Urban Heat Island and Its Regional Impacts Using Remotely Sensed Thermal Data—A Review of Recent Developments and Methodology" Land 10, no. 8: 867. https://doi.org/10.3390/land10080867

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