Effects of green space spatial pattern on land surface temperature: Implications for sustainable urban planning and climate change adaptation

被引:327
|
作者
Maimaitiyiming, Matthew [1 ]
Ghulam, Abduwasit [1 ]
Tiyip, Tashpolat [2 ,3 ]
Pla, Filiberto [4 ]
Latorre-Carmona, Pedro [4 ]
Halik, Uemuet [2 ,3 ]
Sawut, Mamat [1 ,2 ,3 ]
Caetano, Mario [5 ]
机构
[1] St Louis Univ, Ctr Sustainabil, St Louis, MO 63103 USA
[2] Xinjiang Univ, Coll Resources & Environm Sci, Urumqi 830046, Xinjiang, Peoples R China
[3] Xinjiang Univ, Minist Educ, Key Lab Oasis Ecol, Urumqi 830046, Xinjiang, Peoples R China
[4] Univ Jaume 1, Inst New Imaging Technol, Castellon de La Plana 12071, Spain
[5] Univ Nova Lisboa ISEGI NOVA, Inst Super Estat & Gestao Informacao, P-1070312 Lisbon, Portugal
基金
中国国家自然科学基金;
关键词
Land surface temperature; Landscape metrics; Normalized mutual information measure; Remote sensing; Sustainable urban planning; Urban heat island; Urban green space; HEAT-ISLAND; SEASONAL-VARIATIONS; LANDSCAPE PATTERN; MULTISENSOR DATA; VEGETATION; COVER; AIR; IMPACT; WATER; CONFIGURATION;
D O I
10.1016/j.isprsjprs.2013.12.010
中图分类号
P9 [自然地理学];
学科分类号
0705 ; 070501 ;
摘要
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. (C) 2014 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS) Published by Elsevier B.V. All rights reserved.
引用
收藏
页码:59 / 66
页数:8
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