Analysis of local-scale urban heat island characteristics using an integrated method of mobile measurement and GIS-based spatial interpolation
Analysis of local-scale urban heat island characteristics using an integrated method of mobile measurement and GIS-based spatial interpolation
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DOI：
10.1016/j.buildenv.2017.03.013
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发表时间：
2017-05-15
影响因子：
7.4
通讯作者：
Wu, Qing
中科院分区：
文献类型：
--
作者：
Liu, Lin;Lin, Yaoyu;Wu, Qing
在一个城市格局多样化的复杂城市区域，当地气候通常会随着时间和空间的变化而变化。利用高效的实地调查方法准确掌握当地气候特征，有助于为气候意识生态城市建设提供理论支持和技术参考。本研究以深圳华侨城(OCT)为研究区域，主要研究不同城市格局下的局部尺度城市热岛特征。提出并应用了一种将移动测量与基于地理信息系统的空间内插相结合的有效方法。通过对获得的移动数据进行时间校正，表达了沿移动路线的局部城市热岛强度(LUHII)。然后基于移动路径上的LUHII值，分别应用三种主要的空间内插方法(SIMS)得到整个OCT内的LUHII空间分布。空间分布结果表明，OCT内的LUHII具有明显的时空特征。用24个实测数据进一步验证了SIMS的结果，3个SIMS的总平均绝对误差(MAE)和均方根误差(RMSE)约为03℃。然后讨论了3个城市格局指标对LUHII的定量影响，两个表达LUHII的公式表明，降低建筑密度有助于缓解局地尺度的城市热岛效应。(C)2017爱思唯尔有限公司。保留所有权利。
Across a complex urban region with diversified urban patterns, the local climate usually varies with time and space. Achieving accurate local climatic characteristics by using efficient field survey method contributes to providing theoretical support and technical reference for climate-conscious eco-city construction. This study takes the Shenzhen Overseas Chinese Town (OCT) as research area, and mainly focuses on the local-scale urban heat island (UHI) characteristics under different urban patterns. An efficient method by integrating both the mobile measurement and GIS-based spatial interpolation is proposed and applied. By applying temporal corrections to the obtained mobile data, the local UHI intensities (LUHII) along the mobile route are expressed. Then based on the LUHII values along the mobile route, three main spatial interpolation methods (SIMs) are respectively applied to obtain the LUHII spatial distributions within the whole OCT. The spatial distribution results illustrate that the LUHII within the OCT express obvious spatial-temporal characteristics. Further verifying the results of SIMs with 24 field measurement data, the three SIMs present total average mean absolute error (MAE) and root mean square error (RMSE) values of about 03 degrees C. Then quantitative effects of three urban pattern indicators on LUHII are discussed and two equations for expressing the LUHII in two seasons demonstrate that decreasing the building density could help relieve local-scale UHI effects. (C) 2017 Elsevier Ltd. All rights reserved.