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Spatial pattern of greenspace affects land surface temperature: evidence from the heavily urbanized Beijing metropolitan area, China

Li, Xiaoma ; Zhou, Weiqi ; Ouyang, Zhiyun ; Xu, Weihua ; Zheng, Hua

Landscape ecology, 2012-07, Vol.27 (6), p.887-898 [Periódico revisado por pares]

Dordrecht: Springer Netherlands

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Título:
Spatial pattern of greenspace affects land surface temperature: evidence from the heavily urbanized Beijing metropolitan area, China
Autor: Li, Xiaoma ; Zhou, Weiqi ; Ouyang, Zhiyun ; Xu, Weihua ; Zheng, Hua
Assuntos: Animal, plant and microbial ecology ; Applied ecology ; Biological and medical sciences ; Biomedical and Life Sciences ; Ecology ; Environmental Management ; Fundamental and applied biological sciences. Psychology ; General aspects ; General aspects. Techniques ; Land use ; Landscape Ecology ; Landscape/Regional and Urban Planning ; Life Sciences ; Nature Conservation ; Research Article ; Sustainable Development ; Teledetection and vegetation maps ; Temperature ; Urban areas ; Urban planning
É parte de: Landscape ecology, 2012-07, Vol.27 (6), p.887-898
Notas: ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
Descrição: The urban heat island describes the phenomenon that air/surface temperatures are higher in urban areas compared to their surrounding rural areas. Numerous studies have shown that increased percent cover of greenspace (PLAND) can significantly decrease land surface temperatures (LST). Fewer studies, however, have investigated the effects of configuration of greenspace on LST. This paper aims to fill this gap using Beijing, China as a case study. PLAND along with six configuration metrics were used to measure the composition and configuration of greenspace. The metrics were calculated based on a greenspace map derived from SPOT imagery, and LST data were retrieved from Landsat TM thermal band. Ordinary least squares regression and spatial autoregression were employed to investigate the relationship between LST and spatial pattern of greenspace using the census tract as the analytical unit. The results showed that PLAND was the most important predictor of LST. A 10 % increase in PLAND resulted in approximately a 0.86 °C decrease in LST. Configuration of greenspace also significantly affected LST. Given a fixed amount of greenspace, LST increased significantly with increased patch density. In addition, the variance of LST was largely explained by both composition and configuration of greenspace. The unique variation explained by the composition was relatively small, and was close to that of the configuration. Results from this study can expand our understanding of the relationship between LST and vegetation, and provide insights for improving urban greenspace planning and management.
Editor: Dordrecht: Springer Netherlands
Idioma: Inglês

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Spatial pattern of greenspace affects land surface temperature: evidence from the heavily urbanized Beijing metropolitan area, China

Li, Xiaoma ; Zhou, Weiqi ; Ouyang, Zhiyun ; Xu, Weihua ; Zheng, Hua

Dordrecht: Springer Netherlands

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