TY - JOUR
T1 - Urban heat islands and landscape heterogeneity
T2 - Linking spatiotemporal variations in surface temperatures to land-cover and socioeconomic patterns
AU - Buyantuyev, Alexander
AU - Wu, Jianguo
N1 - Funding Information:
Acknowledgments We appreciate the extensive help provided by Anthony Brazel and Susanne Grossman-Clarke. Chris Eisinger helped with ASTER data processing, and Chris M. Clark advised on data analyses. We thank David Iwaniec, Darrel Jenerette, and two anonymous reviewers for their helpful comments on an earlier version of the manuscript. This research was supported by the National Science Foundation under Grant No. DEB-0423704, Central Arizona-Phoenix Long-Term Ecological Research (CAP LTER) and under Grant No. BCS-0508002 (Biocomplexity/CNH). Any opinions, findings and conclusions or recommendation expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation (NSF).
Copyright:
Copyright 2010 Elsevier B.V., All rights reserved.
PY - 2010/1
Y1 - 2010/1
N2 - The urban heat island (UHI) phenomenon is a common environmental problem in urban landscapes which affects both climatic and ecological processes. Here we examined the diurnal and seasonal characteristics of the Surface UHI in relation to land-cover properties in the Phoenix metropolitan region, located in the northern Sonoran desert, Arizona, USA. Surface temperature patterns derived from the Advanced Spaceborne Thermal Emission and Reflection Radiometer for two day-night pairs of imagery from the summer (June) and the autumn (October) seasons were analyzed. Although the urban core was generally warmer than the rest of the area (especially at night), no consistent trends were found along the urbanization gradient. October daytime data showed that most of the urbanized area acted as a heat sink. Temperature patterns also revealed intra-urban temperature differences that were as large as, or even larger than, urban-rural differences. Regression analyses confirmed the important role of vegetation (daytime) and pavements (nighttime) in explaining spatio-temporal variation of surface temperatures. While these variables appear to be the main drivers of surface temperatures, their effects on surface temperatures are mediated considerably by humans as suggested by the high correlation between daytime temperatures and median family income. At night, however, the neighborhood socio-economic status was a much less controlling factor of surface temperatures. Finally, this study utilized geographically weighted regression which accounts for spatially varying relationships, and as such it is a more appropriate analytical framework for conducting research involving multiple spatial data layers with autocorrelated structures.
AB - The urban heat island (UHI) phenomenon is a common environmental problem in urban landscapes which affects both climatic and ecological processes. Here we examined the diurnal and seasonal characteristics of the Surface UHI in relation to land-cover properties in the Phoenix metropolitan region, located in the northern Sonoran desert, Arizona, USA. Surface temperature patterns derived from the Advanced Spaceborne Thermal Emission and Reflection Radiometer for two day-night pairs of imagery from the summer (June) and the autumn (October) seasons were analyzed. Although the urban core was generally warmer than the rest of the area (especially at night), no consistent trends were found along the urbanization gradient. October daytime data showed that most of the urbanized area acted as a heat sink. Temperature patterns also revealed intra-urban temperature differences that were as large as, or even larger than, urban-rural differences. Regression analyses confirmed the important role of vegetation (daytime) and pavements (nighttime) in explaining spatio-temporal variation of surface temperatures. While these variables appear to be the main drivers of surface temperatures, their effects on surface temperatures are mediated considerably by humans as suggested by the high correlation between daytime temperatures and median family income. At night, however, the neighborhood socio-economic status was a much less controlling factor of surface temperatures. Finally, this study utilized geographically weighted regression which accounts for spatially varying relationships, and as such it is a more appropriate analytical framework for conducting research involving multiple spatial data layers with autocorrelated structures.
KW - Geographically weighted regression
KW - Land cover
KW - Surface temperature
KW - Surface urban heat island
KW - Urbanization
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U2 - 10.1007/s10980-009-9402-4
DO - 10.1007/s10980-009-9402-4
M3 - Article
AN - SCOPUS:73649086213
SN - 0921-2973
VL - 25
SP - 17
EP - 33
JO - Landscape Ecology
JF - Landscape Ecology
IS - 1
ER -