Uncertainty of city-based urban heat island intensity across 1112 global cities: Background reference and cloud coverage

Li, Kangning; Chen, Yunhao; Gao, Sijie

doi:10.1016/j.rse.2022.112898

Cited by 40 publications

(14 citation statements)

References 51 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…SUHII is defined as the average LST difference between the urban area and its surrounding rural area. Currently, various methods exist for estimating SUHII, with differences primarily arising from the definition of rural area (K. Li et al., 2022; Q. Yang et al., 2023b). The preferred rural area should be chosen to minimize the effects of natural factors like topographic relief and water bodies, while also eliminating the influence of human activities (K. Li et al., 2022).…”

Section: Methodsmentioning

confidence: 99%

“…The preferred rural area should be chosen to minimize the effects of natural factors like topographic relief and water bodies, while also eliminating the influence of human activities (K. Li et al, 2022). Hence, this study utilized the Modified Equal Area-Rural (MEA-R) method, as introduced by K. Li et al (2022), to extract the rural area. This method has been proved to be effective in removing the influence of confounding factors on the estimation of SUHII (K. Li et al, 2022).…”

Section: Estimation Of Suhiimentioning

confidence: 99%

“…Hence, this study utilized the Modified Equal Area-Rural (MEA-R) method, as introduced by K. Li et al (2022), to extract the rural area. This method has been proved to be effective in removing the influence of confounding factors on the estimation of SUHII (K. Li et al, 2022). Specific details of the MEA-R method are provided in Text S1 in Supporting Information S1.…”

Section: Estimation Of Suhiimentioning

confidence: 99%

Section: Estimation Of Suhiimentioning

confidence: 99%

“…However, it remains questionable whether such localized conclusions, drawn from a few cities, can be extrapolated to global cities distributed in different climate zones, given the large spatiotemporal heterogeneity of the SUHI effect. Although some studies have analyzed the effect of missing LST data on SUHII estimations at continental or global scales (K. Li et al., 2022; Q. Yang et al., 2023b), there is a lack of large‐scale quantitative assessments comparing SUHII derived from clear‐sky and all‐sky conditions.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Satellite Clear‐Sky Observations Overestimate Surface Urban Heat Islands in Humid Cities

Yang,

Xu,

Wen

et al. 2024

Geophysical Research Letters

View full text Add to dashboard Cite

Satellite‐based thermal infrared (TIR) land surface temperature (LST) is hindered by cloud cover and is applicable solely under clear‐sky conditions for estimating surface urban heat island intensity (SUHII). Clear‐sky SUHII may not accurately represent all‐sky conditions, potentially introducing quantitative biases in assessing urban heat islands. However, the differences between clear‐sky and all‐sky SUHIIs and their spatiotemporal variations are still poorly understood. Our analysis of over 600 global cities demonstrates that clear‐sky SUHII is mostly higher than all‐sky SUHII, particularly in summer, daytime, and precipitation‐rich regions. Besides, clear‐sky SUHII typically exhibits stronger seasonal and diurnal contrasts than all‐sky SUHII, especially for cities located in humid regions. These discrepancies can be attributed mainly to the increased missing LST data caused by cloud enhancement in urban areas. Our findings highlight the tendency for clear‐sky observations to overestimate SUHII, providing valuable insights for standardizing the quantification of surface urban heat islands.

show abstract

Section: Methodsmentioning

confidence: 99%