Effects of green space spatial pattern on land surface temperature: Implications for sustainable urban planning and climate change adaptation
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Effects of green space spatial pattern on land surface temperature: Implications for sustainable urban planning and climate change adaptationAutoria
Data de publicació
2014-03xmlui.dri2xhtml.METS-1.0.item-edition
PostprintEditor
ElsevierCita bibliogràfica
MAIMAITIYIMING, Matthew, et al. Effects of green space spatial pattern on land surface temperature: Implications for sustainable urban planning and climate change adaptation. ISPRS Journal of Photogrammetry and Remote Sensing, 2014, vol. 89, p. 59-66.Tipus de document
info:eu-repo/semantics/articleVersió de l'editorial
http://www.sciencedirect.com/science/article/pii/S0924271614000021Versió
info:eu-repo/semantics/acceptedVersionParaules clau / Matèries
Resum
The urban heat island (UHI) refers to the phenomenon of higher atmospheric and surface temperatures
occurring in urban areas than in the surrounding rural areas. Mitigation of the UHI effects via the configuration
of ... [+]
The urban heat island (UHI) refers to the phenomenon of higher atmospheric and surface temperatures
occurring in urban areas than in the surrounding rural areas. Mitigation of the UHI effects via the configuration
of green spaces and sustainable design of urban environments has become an issue of increasing
concern under changing climate. In this paper, the effects of the composition and configuration of green
space on land surface temperatures (LST) were explored using landscape metrics including percentage of
landscape (PLAND), edge density (ED) and patch density (PD). An oasis city of Aksu in Northwestern
China was used as a case study. The metrics were calculated by moving window method based on a green
space map derived from Landsat Thematic Mapper (TM) imagery, and LST data were retrieved from Landsat
TM thermal band. A normalized mutual information measure was employed to investigate the relationship
between LST and the spatial pattern of green space. The results showed that while the PLAND is
the most important variable that elicits LST dynamics, spatial configuration of green space also has significant
effect on LST. Though, the highest normalized mutual information measure was with the PLAND
(0.71), it was found that the ED and PD combination is the most deterministic factors of LST than the
unique effects of a single variable or the joint effects of PLAND and PD or PLAND and ED. Normalized
mutual information measure estimations between LST and PLAND and ED, PLAND and PD and ED and
PD were 0.7679, 0.7650 and 0.7832, respectively. A combination of the three factors PLAND, PD and
ED explained much of the variance of LST with a normalized mutual information measure of 0.8694.
Results from this study can expand our understanding of the relationship between LST and street trees
and vegetation, and provide insights for sustainable urban planning and management under changing
climate [-]
Publicat a
ISPRS Journal of Photogrammetry and Remote Sensing, 2014, vol. 89Drets d'accés
2014 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS) Published by Elsevier
B.V. All rights reserved.
http://rightsstatements.org/vocab/InC/1.0/
info:eu-repo/semantics/openAccess
http://rightsstatements.org/vocab/InC/1.0/
info:eu-repo/semantics/openAccess
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