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| DOI: | 10.1016/j.ufug.2017.06.008 |
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| Web URL(s): | https://www.sciencedirect.com/science/article/pii/S1618866717300687#!
Last checked: 01/17/2018
Access conditions: Item is within a limited-access website |
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| Publication Type:
| Refereed |
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| Author(s): | Du, Hongyu;
Cai, Wenbo;
Xu, Yanqing;
Wang, Zhibao;
Wang, Yuanyuan;
Cai, Yongli |
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| Author Affiliation: | Du, Zhibao Wang, Yuanyuan Wang, and Yongli Cai: Shanghai Key Laboratory for Urban Ecological Processes and Eco-Restoration, East China Normal University, Shanghai, China and Department of Environmental Science, East China Normal University, Shanghai, China; Wenbo Cai: Department of Geography, School of Environmental Sciences, University of Hull, Hull, UK; Xu: Department of Geography & Planning, The University of Toledo, OH |
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| Title: | Quantifying the cool island effects of urban green spaces using remote sensing data |
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| Source: | Urban Forestry & Urban Greening. Vol. 27, October 2017, p. 24-31. |
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| Publishing Information: | Jena, Germany: Urban & Fischer |
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| # of Pages: | 8 |
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| Keywords: | TIC Keywords: Greenspace; Remote sensing; Temperatures; Thermal conductivity; Urban habitat; Urban heat island; Urbanization
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| Geographic Terms: | Shanghai, China |
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| Abstract/Contents: | "Urban Heat Island (UHI) leads to increased energy consumption, aggravated pollution and threatened health of citizens. Urban green spaces mitigate UHI effects, however, it is still unclear how the green space characteristics and its surrounding environment affects the green space cool island (GCI). In this study, land surface temperature (LST) and land cover types within the outmost ring road of Shanghai, China were obtained from Landsat 8 data and high-resolution Google Earth data. The GCI effects were defined in three aspects: GCI range (GR), amplitude of temperature drop (TA) and temperature gradient (TG). Pearson correlation analysis was processed to get the relationship between the aspects and impact factors. The results indicated that the GCI principle could be explained by the thermal conduct theory. The efficient methods to decrease LST of green spaces include increasing green space area while staying below the threshold, adding complexity of green space shape, decreasing impervious surfaces and enlarging the area of water bodies. For the surrounding environment of the green spaces, increasing vegetation and water body fractions or decreasing impervious surfaces will help to strengthen GCI effects. The findings can help urban planners to understand GCI formation and design cool green spaces to mitigate UHI effects." |
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| Language: | English |
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| References: | 36 |
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| Note: | Maps
Pictures, color
Tables
Graphs |
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| ASA/CSSA/SSSA Citation (Crop Science-Like - may be incomplete):
Du, H., W. Cai, Y. Xu, Z. Wang, Y. Wang, and Y. Cai. 2017. Quantifying the cool island effects of urban green spaces using remote sensing data. Urban Forestry & Urban Greening. 27:p. 24-31. |
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| DOI: 10.1016/j.ufug.2017.06.008 |
| Web URL(s):
https://www.sciencedirect.com/science/article/pii/S1618866717300687#!
Last checked: 01/17/2018
Access conditions: Item is within a limited-access website |
| 
MSU catalog number: b5268048 |
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