TY - JOUR
T1 - A spatially explicit surface urban heat island database for the United States
T2 - Characterization, uncertainties, and possible applications
AU - Chakraborty, T.
AU - Hsu, A.
AU - Manya, D.
AU - Sheriff, G.
N1 - Funding Information:
This work was funded by the Samuel Center for Social Connectedness (grant number: AWDR14157 ) and the National University of Singapore Early Career Award (grant number: US_ECRA_FY18_P15 ). We thank Nicholas Chin of Yale-NUS College for assistance in extracting US census data, and Barkley Dai of Yale College for compiling an early version of the United States SUHI Explorer tool in Google Earth Engine.
Funding Information:
This work was funded by the Samuel Center for Social Connectedness (grant number: AWDR14157) and the National University of Singapore Early Career Award (grant number: US_ECRA_FY18_P15). We thank Nicholas Chin of Yale-NUS College for assistance in extracting US census data, and Barkley Dai of Yale College for compiling an early version of the United States SUHI Explorer tool in Google Earth Engine.
Publisher Copyright:
© 2020 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS)
PY - 2020/10
Y1 - 2020/10
N2 - The urban heat island (UHI) effect is strongly modulated by urban-scale changes to the aerodynamic, thermal, and radiative properties of the Earth's land surfaces. Interest in this phenomenon, both from the climatological and public health perspectives, has led to hundreds of UHI studies, mostly conducted on a city-by-city basis. These studies, however, do not provide a complete picture of the UHI for administrative units using a consistent methodology. To address this gap, we characterize clear-sky surface UHI (SUHI) intensities for all urbanized areas in the United States using a modified Simplified Urban-Extent (SUE) approach by combining a fusion of remotely-sensed data products with multiple US census-defined administrative urban delineations. We find the highest daytime SUHI intensities during summer (1.91 ± 0.97 °C) for 418 of the 497 urbanized areas, while the winter daytime SUHI intensity (0.87 ± 0.45 °C) is the lowest in 439 cases. Since urban vegetation has been frequently cited as an effective way to mitigate UHI, we use NDVI, a satellite-derived proxy for live green vegetation, and US census tract delineations to characterize how vegetation density modulates inter-urban, intra-urban, and inter-seasonal variability in SUHI intensity. In addition, we also explore how elevation and distance from the coast confound SUHI estimates. To further quantify the uncertainties in our estimates, we analyze and discuss some limitations of these satellite-derived products across climate zones, particularly issues with using remotely sensed radiometric temperature and vegetation indices as proxies for urban heat and vegetation cover. We demonstrate an application of this spatially explicit dataset, showing that for the majority of the urbanized areas, SUHI intensity is lower in census tracts with higher median income and higher proportion of white people. Our analysis also suggests that poor and non-white urban residents may suffer the possible adverse effects of summer SUHI without reaping the potential benefits (e.g., warmer temperatures) during winter, though establishing this result requires future research using more comprehensive heat stress metrics. This study develops new methodological advancements to characterize SUHI and its intra-urban variability at levels of aggregation consistent with sources of other socioeconomic information, which can be relevant in future inter-disciplinary research and as a possible screening tool for policy-making. The dataset developed in this study is visualized at: https://datadrivenlab.users.earthengine.app/view/usuhiapp.
AB - The urban heat island (UHI) effect is strongly modulated by urban-scale changes to the aerodynamic, thermal, and radiative properties of the Earth's land surfaces. Interest in this phenomenon, both from the climatological and public health perspectives, has led to hundreds of UHI studies, mostly conducted on a city-by-city basis. These studies, however, do not provide a complete picture of the UHI for administrative units using a consistent methodology. To address this gap, we characterize clear-sky surface UHI (SUHI) intensities for all urbanized areas in the United States using a modified Simplified Urban-Extent (SUE) approach by combining a fusion of remotely-sensed data products with multiple US census-defined administrative urban delineations. We find the highest daytime SUHI intensities during summer (1.91 ± 0.97 °C) for 418 of the 497 urbanized areas, while the winter daytime SUHI intensity (0.87 ± 0.45 °C) is the lowest in 439 cases. Since urban vegetation has been frequently cited as an effective way to mitigate UHI, we use NDVI, a satellite-derived proxy for live green vegetation, and US census tract delineations to characterize how vegetation density modulates inter-urban, intra-urban, and inter-seasonal variability in SUHI intensity. In addition, we also explore how elevation and distance from the coast confound SUHI estimates. To further quantify the uncertainties in our estimates, we analyze and discuss some limitations of these satellite-derived products across climate zones, particularly issues with using remotely sensed radiometric temperature and vegetation indices as proxies for urban heat and vegetation cover. We demonstrate an application of this spatially explicit dataset, showing that for the majority of the urbanized areas, SUHI intensity is lower in census tracts with higher median income and higher proportion of white people. Our analysis also suggests that poor and non-white urban residents may suffer the possible adverse effects of summer SUHI without reaping the potential benefits (e.g., warmer temperatures) during winter, though establishing this result requires future research using more comprehensive heat stress metrics. This study develops new methodological advancements to characterize SUHI and its intra-urban variability at levels of aggregation consistent with sources of other socioeconomic information, which can be relevant in future inter-disciplinary research and as a possible screening tool for policy-making. The dataset developed in this study is visualized at: https://datadrivenlab.users.earthengine.app/view/usuhiapp.
KW - Environmental disparities
KW - Google earth engine
KW - LST
KW - MODIS
KW - NDVI
KW - SUHI
KW - Surface Urban Heat Island Intensity
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U2 - 10.1016/j.isprsjprs.2020.07.021
DO - 10.1016/j.isprsjprs.2020.07.021
M3 - Article
AN - SCOPUS:85091779737
SN - 0924-2716
VL - 168
SP - 74
EP - 88
JO - ISPRS Journal of Photogrammetry and Remote Sensing
JF - ISPRS Journal of Photogrammetry and Remote Sensing
ER -