A simplified urban-extent algorithm to characterize surface urban heat islands on a global scale and examine vegetation control on their spatiotemporal variability

Chakraborty, TC; Lee, Xuhui

doi:10.1016/j.jag.2018.09.015

Cited by 216 publications

(212 citation statements)

References 32 publications

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“…We examine the associations between neighborhood-scale daytime surface UHI and the Δα, ΔNDVI, and ΔNDBI for each city ( figure 4). In general, we see a negative correlation between UHI and ΔNDVI, since more vegetated neighborhoods have higher evaporative cooling, and thus, lower surface temperatures, as demonstrated at various scales (Rizwan et al 2008, Peng et al 2011, Chakraborty et al 2017, Chakraborty and Lee 2019. A few cities, like Buenos Aires, Copenhagen, Melbourne, and Tokyo do show slight positive relationships between UHI and ΔNDVI.…”

Section: Physical Characteristics Of Cities and Their Impact On Uhi Imentioning

confidence: 68%

Disproportionately higher exposure to urban heat in lower-income neighborhoods: a multi-city perspective

Chakraborty

Hsu

Manya

et al. 2019

Environ. Res. Lett.

158

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A growing literature documents the effects of heat stress on premature mortality and other adverse health outcomes. Urban heat islands (UHI) can exacerbate these adverse impacts in cities by amplifying heat exposure during the day and inhibiting the body's ability to recover at night. Since the UHI intensity varies not only across, but also within cities, intra-city variation may lead to differential impact of urban heat stress on different demographic groups. To examine these differential impacts, we combine satellite observations with census data to evaluate the relationship between distributions of both UHI and income at the neighborhood scale for 25 cities around the world. We find that in most (72%) cases, poorer neighborhoods experience elevated heat exposure, an incidental consequence of the intra-city distribution of income in cities. This finding suggests that policymakers should consider designing city-specific UHI reduction strategies to mitigate its impacts on the most socioeconomically vulnerable populations who may be less equipped to adapt to environmental stressors. Since the strongest contributor of intra-urban UHI variability among the physical characteristics considered in this study is a neighborhood's vegetation density, increasing green space in lower income neighborhoods is one strategy urban policymakers can adopt to ameliorate some of UHI's inequitable burden on economically disadvantaged residents.

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Section: Physical Characteristics Of Cities and Their Impact On Uhi Imentioning

confidence: 68%

Disproportionately higher exposure to urban heat in lower-income neighborhoods: a multi-city perspective

Chakraborty

Hsu

Manya

et al. 2019

Environ. Res. Lett.

158

View full text Add to dashboard Cite

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“…Land surface temperatures (LSTs) derived from satellite sensor can be used to estimate the surface UHI (SUHI) from the contrast between urban pixels and surrounding rural ones (Zhou et al, 2019). However, the long-term trends of SUHI at the global scale were only investigated by Chakraborty and Lee (2019), showing that the trends of annual daytime and nighttime SUHII during 2003-2017 were 0.03°C per decade and 0.00°C per decade, respectively. However, the long-term trends of SUHI at the global scale were only investigated by Chakraborty and Lee (2019), showing that the trends of annual daytime and nighttime SUHII during 2003-2017 were 0.03°C per decade and 0.00°C per decade, respectively.…”

Section: Introductionmentioning

confidence: 99%

“…However, Chakraborty and Lee (2019) only computed the trends of annual mean SUHII and did not provide any seasonal differences. In addition, the data and methods in Chakraborty and Lee (2019) may lead to some uncertainties (for further discussion, see section 3.1). A systematic evaluation of SUHII and related drivers at a global scale is still needed.…”

Section: Introductionmentioning

confidence: 99%

Greening in Rural Areas Increases the Surface Urban Heat Island Intensity

Yao

Wang

Huang

et al. 2019

Geophysical Research Letters

182

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In this study, Moderate Resolution Imaging Spectroradiometer land cover, land surface temperature (LST), and enhanced vegetation index (EVI) data were used to investigate the trends of surface urban heat island intensity (SUHII, urban LST minus rural LST) and their relations with vegetation in 397 global big cities during 2001–2017. Major findings include the following: (1) Annual daytime and nighttime SUHII increased significantly (p < 0.05, Mann‐Kendall trend test) in 42.1% and 30.5% cities, respectively. (2) The daytime SUHII in the growing season was significantly and positively correlated with rural EVI in 58.9% cities. This is because high rural EVI can increase the EVI difference between urban and rural areas. (3) Rural greening contributed 22.5% of the increased daytime SUHII in the growing season at the global scale. This study highlights that the effect of greening in rural areas was a significant and widespread driver for the increased daytime SUHII.

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“…Within the past decade several large-scale studies have documented a daytime 'urban cool island' effect for many dryland cities as surrounding landscapes with sparse xeric vegetation, grasses, and dry soils warm more rapidly than urban surfaces (Imhoff et al 2010, Peng et al 2014, Chakraborty and Lee 2019. Surrounding deserts then cool more rapidly at night than urban pavement and rooftops, leading to nighttime UHIs.…”

Section: Introductionmentioning

confidence: 99%

Urban heat island behaviors in dryland regions

Dialesandro

Wheeler

2019

Environ. Res. Commun.

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Urban heat island (UHI) characteristics and mitigation strategies for dryland cities differ from those for wetter urban regions. Whereas the latter typically see daytime surface UHIs, the rapid heating and cooling of deserts surrounding arid cities often produces daytime 'urban cool islands' and nighttime UHIs. Degrees of aridness, extent of vegetation, elevation, latitude, humidity, topography, and typical building types are likely to influence dryland UHI dynamics. This study analyzes variations in thermal effects at multiple scales for 10 dryland urban regions representing varied geographies worldwide with an aim to establish a broader understanding of the spectrum of UHI patterns in dryland cities. We used GIS to assemble daytime and nighttime satellite imagery, determined land surface temperature and vegetation at a 30-meter scale, and analyzed typical neighborhood-scale examples of six land cover types in each region. The 10 regions showed large variation in thermal effects. We found a strong daytime surface UHI in only one. Nighttime heat islands were more pronounced. However, all regions showed strong small-scale variation in temperature, averaging a 12.3°C difference between mean topquintile and bottom-quintile surface temperatures. Samples of urban forest landscapes cooled daytime temperatures an average of 5.6°C compared to metro averages. Irrigated lawn and multistory building land cover samples also had a substantial cooling effect. Xeriscaped landscapes amplified daytime heating. Our results indicate that UHIs for dryland cities are unlikely to be reduced by xeriscape strategies, but that shade-maximizing urban forestry and built form hold promise to reduce heat islands.

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A simplified urban-extent algorithm to characterize surface urban heat islands on a global scale and examine vegetation control on their spatiotemporal variability

Cited by 216 publications

References 32 publications

Disproportionately higher exposure to urban heat in lower-income neighborhoods: a multi-city perspective

Disproportionately higher exposure to urban heat in lower-income neighborhoods: a multi-city perspective

Greening in Rural Areas Increases the Surface Urban Heat Island Intensity

Urban heat island behaviors in dryland regions

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