地理学报 ›› 2019, Vol. 74 ›› Issue (3): 475-489.doi: 10.11821/dlxb201903006

所属专题: 气候变化与地表过程

• 土地利用与生态系统服务 • 上一篇    下一篇

2003-2017年北京市地表热力景观时空分异特征及演变规律

乔治1(), 黄宁钰1, 徐新良2, 孙宗耀3, 吴晨1, 杨俊4()   

  1. 1. 天津大学环境科学与工程学院,天津 300072
    2. 中国科学院地理科学与资源研究所 资源与环境信息系统国家重点实验室,北京 100101
    3. 山东师范大学地理与环境学院,济南 250014
    4. 辽宁师范大学人居环境研究中心,大连 116029
  • 收稿日期:2017-11-20 修回日期:2018-12-26 出版日期:2019-03-25 发布日期:2019-03-19
  • 作者简介:

    乔治(1986-), 男, 山东滕州人, 博士, 讲师, 研究方向为GIS和遥感应用、土地利用变化、城市热环境。E-mail: qiaozhi@tju.edu.cn

  • 基金资助:
    国家自然科学基金项目(41501472, 41771178)

Spatio-temporal pattern and evolution of the urban thermal landscape in metropolitan Beijing between 2003 and 2017

Zhi QIAO1(), Ningyu HUANG1, Xinliang XU2, Zongyao SUN3, Chen WU1, Jun YANG4()   

  1. 1. School of Environmental Science and Engineering, Tianjin University, Tianjin 300072, China
    2. Institute of Geographic Sciences and Natural Resources Research, CAS, State Key Laboratory of Resources and Environmental Information Systems, Beijing 100101, China
    3. College of Geography and Environment, Shandong Normal University, Jinan 250014, China
    4. Human Settlements Research Center, Liaoning Normal University, Dalian 116029, Liaoning, China
  • Received:2017-11-20 Revised:2018-12-26 Online:2019-03-25 Published:2019-03-19
  • Supported by:
    National Natural Science Foundation of China, No.41501472, No.41771178

摘要:

利用2003-2017年MODIS地表温度数据,分别从数量、形状和结构角度揭示北京市不同季相和昼夜间地表热力景观时空分异特征,并进一步通过热力等级变化图谱及质心迁移轨迹揭示城市热力景观空间演变规律,探究热力景观等级转换生态过程。结论如下:① 城市地表热力景观季节和昼夜空间特征差异显著;② 中温区在城市热环境中占主导地位。白天中温区是最不稳定的热力景观等级;夜间次低温区和次高温区不稳定性增加;③ 地表热力景观等级变化以稳定型占主,反复变化型和前期变化型次之。地表热力景观等级通常呈现逐级递增或递减规律,山区呈现逐级降温趋势,北部城郊—山地交错地带表现出次低温和中温的反复转向,南部地区有一定的升温趋势;④ 2003-2017年高温区面积增大且质心向城市中心集中,低温区质心向城市外围扩散。生态涵养发展区对北京市地表热力景观质心迁移贡献率最高。热力景观时空分异特征及演变规律可为有效缓解城市热岛效应提供管理决策支持。

关键词: 热力景观, 时空格局, 景观指数, 质心轨迹, MODIS, 北京市

Abstract:

Urban heat islands resulting from land use and land cover change have become a major barrier to urbanization and sustainable development of ecological urban environments. Although many studies have focused on the interannual and seasonal characteristics of urban heat islands, there has been no comparative analysis of the urban surface thermal landscape at multiple spatio-temporal scales. This study described the spatio-temporal patterns of the urban surface thermal landscape in different seasons and by time of day (daytime/nighttime) in terms of quantity, shape, and structure using MODIS LST products, and revealed the evolution of the urban surface thermal landscape using mapping techniques and analysis of barycenter trajectories in metropolitan Beijing between 2003 and 2017. The conclusions were as follows: (1) The characteristics of the urban surface thermal landscape vary significantly in different seasons and by time of day. (2) The medium-temperature zone constitutes the largest proportion of the area of metropolitan Beijing, which is the most unstable area during the daytime and the instability of the sub-high-temperature and sub-low-temperature zones increased at night. (3) The stable zone is most important in terms of the change in the land surface thermal landscape, followed by the repeated-changes zone and the zone where the change occurred in the first 5 years. The changes of different temperature zones usually increased or decreased progressively. There was a cooling trend in the mountains. In the north mountain-transition zone, the process of transferring between sub-low temperature and medium temperature was repeated. There was a warming trend in the south. (4) The area of the high-temperature zone increased from 2003 to 2017 and its barycenter was concentrated in the city center; the barycenter of the low-temperature zone moved to the urban fringe. The ecological conservation development zone made the greatest contribution to the surface thermal landscape in metropolitan Beijing. The spatio-temporal distribution and evolution of the urban surface thermal landscape support management decisions aimed at alleviating the effect of the urban heat island.

Key words: urban thermal landscape, spatiotemporal pattern, transition probability matrix, barycenter trajectory, MODIS, Beijing