Evaluating Differences between Ground-Based and Satellite-Derived Measurements of Urban Heat: The Role of Land Cover Classes in Portland, Oregon and Washington, D.C

Vivek Shandas (), Yasuyo Makido and Aakash Nath Upraity
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Vivek Shandas: School of Urban Studies and Planning, Portland State University, Portland, OR 97207, USA
Yasuyo Makido: School of Urban Studies and Planning, Portland State University, Portland, OR 97207, USA
Aakash Nath Upraity: Department of Fisheries, Wildlife and Conservation Sciences, Oregon State University, Corvallis, OR 97331, USA

Land, 2023, vol. 12, issue 3, 1-15

Abstract: The distinction between satellite-based land surface temperature (LST) and air temperature has become an increasingly important part of managing urban heat islands. While the preponderance of urban heat research relies on LST, the emergence of a growing infrastructure of publicly available consumer oriented, ground-based sensor networks has offered an alternative for characterizing microscale differences in temperatures. Recent evidence suggests large differences between LST and air temperatures, yet discerning the reason for these differences between satellite-derived measurements of urban heat islands (UHI) and ground-based measurements of air temperature remains largely unresolved. In this study, we draw on an unusually robust and spatially exhaustive dataset of air temperature in two distinct bioclimates—Portland, Oregon, USA and Washington, D.C., USA—to evaluate the role of land cover on temperature. Our findings suggest that LST in highly built environments is consistently higher than recorded air temperatures, at times varying upwards of 15-degree Celsius, while forested areas contain between 2.5 and 3.5-degree Celsius lower temperatures than LST would otherwise indicate. Furthermore, our analyses points to the effects of land use and land cover features and other geophysical processes may have in determining differences in heat measurements across the two locations. The strength of the present analyses also highlights the importance of hyperlocal scales of data used in conjunction with coarser grain satellite derived data to inform urban heat assessments. Our results suggest a consistent pattern in both study areas, which can further our capacity to develop predictive models of air temperature using freely available descriptions of LST.

Keywords: urban heat; land surface temperature (LST); near surface air temperature (NSAT); mobile monitoring; land cover (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jlands:v:12:y:2023:i:3:p:562-:d:1080594

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