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生态学杂志 ›› 2020, Vol. 39 ›› Issue (8): 2671-2677.

• 研究报告 • 上一篇    下一篇

粤港澳大湾区城市热岛时空特征及驱动因素

邓玉娇1,杜尧东2,王捷纯1*,徐杰1,谢维斯3   

  1. 1广东省生态气象中心, 广州 510640; 2广东省气候中心, 广州 510640; 3广东省气象公共服务中心, 广州 510640)
  • 出版日期:2020-08-10 发布日期:2021-02-10

Spatiotemporal characteristics and driving factors of urban heat islands in Guangdong-Hong Kong-Marco Greater Bay Area.

DENG Yu-jiao1, DU Yao-dong2, WANG Jie-chun1*, XU Jie1, XIE Wei-si3#br#   

  1. (1Guangdong Ecological Meteorology Center, Guangzhou 510640, China; 2Guangdong Climate Center, Guangzhou 510640, China; 3Guangdong Meteorological Public Service Center, Guangzhou 510640, China).
  • Online:2020-08-10 Published:2021-02-10

摘要: 城市热岛是粤港澳大湾区建设过程中的热点社会问题,其驱动因素研究更是学者们关注的重要科学问题。本文基于多种卫星遥感资料,定量分析粤港澳大湾区城市热岛的时空分布特征,利用多元回归方法,综合探讨城市热岛的驱动因素。结果表明:2003—2018年粤港澳大湾区城市热岛效应显著增强,热岛强度年增长0.05 ℃,热岛区面积年增长0.18%;城市热岛具有明显的季节变化规律,夏季热岛强度最强且热岛区面积最大,冬季热岛强度最弱但热岛区面积仅次于夏季;热岛区主要分布在东莞大部、深圳大部、广州与佛山交界处、中山北部及惠州中部。多元回归分析表明,海拔对城市热岛影响最为显著,其次是灯光指数、归一化植被指数,再次是气溶胶光学厚度,其中灯光指数为正向驱动因素,其余均为负向驱动因素。

关键词: 热岛强度, 热岛区面积, 时空分布, 驱动因素

Abstract: The urban heat island is a hot social issue during the construction of Guangdong-Hong Kong-Macao Greater Bay Area. The study of the driving factors for the heat island is an important scientific issue. Based on satellite remote sensing data, we quantitatively analyzed the spatiotemporal distribution of urban heat islands in GuangdongHong KongMarco Greater Bay Area. The driving factors of urban heat islands were analyzed by the multiple regression. The results showed that the urban heat island effect in Greater Bay Area increased significantly from 2003 to 2018, with an annual increase of the heat island intensity of 0.05 ℃ and an annual increase of the heat island area of 0.18%. For seasonal variation of urban heat islands, the intensity was the strongest in summer and the weakest in winter. The heat island area was the largest in summer, and second largest in winter. The heat island area was mainly distributed in Dongguan, Shenzhen, the junction of Guangzhou and Foshan, the north of Zhongshan, and the central part of Huizhou. Theresults of multiple regression analysis showed that the altitude had the most significant impact on urban heat islands, followed by the light index, normalized vegetation index, and aerosol optical thickness in a descending order. The light index was a positive driving factor, whereas the rest were negative driving factors.

Key words: heat island intensity, heat island area, spatiotemporal distribution, driving factor.