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北京市热环境时空分异与区划
引用本文:乔治,田光进.北京市热环境时空分异与区划[J].遥感学报,2014,18(3):715-734.
作者姓名:乔治  田光进
作者单位:水环境模拟国家重点实验室, 北京师范大学环境学院, 北京 100875;水环境模拟国家重点实验室, 北京师范大学环境学院, 北京 100875
基金项目:国家自然科学基金(编号:41071357);国家“十二五”科技支撑计划项目(编号:2012BAC13B01)
摘    要:城市热环境空间区划是采用分区管理的思路来缓解城市社会经济发展与热环境之间矛盾的技术基础。本文构建城市热环境区划模型的思路为:(1)将不同时相的MODIS地表温度数据产品进行正规化、分级,分析2008年北京城市热环境时空分布特征。(2)构建城市热环境影响因素评价体系,并通过空间主成分分析计算得到热环境影响主成分因子。(3)通过自组织映射神经网络,利用热环境影响主因子,进一步对热环境进行空间区划。结果表明,北京夜间较白天城市热岛分布层次感明显,夏季白天较其他季节高温区聚合程度高。区域下垫面组成要素直接影响热环境,北京城市热环境的主成分因子依次为植被覆盖、地形地貌、城市下垫面建设规模和人为热排放,并依此将北京划为7个热环境区域,根据各个分区热环境成因机制差异分别提出热环境改善和调控措施。

关 键 词:热环境  区划  空间主成分分析  人工神经网络  北京
收稿时间:2/5/2013 12:00:00 AM
修稿时间:2013/11/5 0:00:00

Spatiotemporal diversity and regionalization of the urban thermal environment in Beijing
QIAO Zhi and TIAN Guangjin.Spatiotemporal diversity and regionalization of the urban thermal environment in Beijing[J].Journal of Remote Sensing,2014,18(3):715-734.
Authors:QIAO Zhi and TIAN Guangjin
Institution:State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China;State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China
Abstract:Regionalization of the urban thermal environment is the technical basis for alleviating the conflict between urban socioeconomic development and the thermal environment based on partition management. In this paper, we constructed a regionalization model for the urban thermal environment. (1) Moderate Resolution Imaging Spectroradiometer land surface temperature products from four seasons were standardized and classified for characterizing the spatiotemporal pattern of the urban thermal environment in 2008. (2) A comprehensive evaluation system of the urban thermal environment was constructed and the principal components were identified by using the spatial principal component analysis method. (3) A self-organizing mapping neural network was used for spatial regionalization of the urban thermal environment. The results show that the distribution levels of the urban heat island are clearer during the nighttime than during the daytime and the high-temperature zone has the higher aggregation degree in summer than in the other seasons. The composition of the underlying surface directly affects the urban thermal environment. The principal components affecting the urban thermal environment include vegetation coverage, geomorphology, urban construction scale, and anthropogenic heat emission. The Beijing metropolitan area was divided into seven urban thermal environment zones, and specific measures and suggestions were proposed for improving the urban thermal environment based on the multiple formation mechanisms of the urban thermal environment in each zone.
Keywords:thermal environment  regionalization  spatial principal component analysis  artificial neural network  Beijing
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