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基于多源数据的长沙市人居热环境效应及其影响因素分析 被引量:37

Thermal environment effects of urban human settlements and influencing factors based on multi-source data:A case study of Changsha city
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摘要 针对城市人居热环境效应研究缺乏从自然-人文多维因子组合综合评价分析的现状,本文基于多源空间数据(Landsat 5、Landsat 8卫星影像数据、POI空间大数据、数字高程模型等)反演长沙市2000年、2009年和2016年城市地表温度格局,并快速获取与城市热环境密切相关的自然和人文因素共12个影响因子。应用标准差椭圆、空间主成分分析(PCA)等方法多角度分析了城市人居热环境效应及影响因素的联动关系。结果表明:①2000-2016年共16年间热岛面积共增加547 km^2、地表最高温度差达到10.1℃。城市热岛区的空间分布主要集中在城市建成区,如工商业集中和人口密集的城市中心地区,并呈现出地表温度从城市中心向郊区逐渐降低的热岛的空间分布格局,出现多个高温中心点,如五一广场商圈、长沙县星沙经济技术开发区、望城工业区、岳麓工业集中区、天心工业区等;②2000-2016年热岛空间发展主轴保持在东北-西南方向,2000-2009年热岛重心向西南偏移了2.7 km,偏转角度为54.9°,2009-2016年热岛重心向东北偏移了4.8 km,偏转角度为60.9°。整体上,长沙市热环境空间格局的变化和城市的建设强度的变化存在一定的关联;③通过主成分分析得出影响长沙城市热环境格局的因子为景观格局、城市建设强度、地形地貌3个主因子;④人文因素对于当前加剧热岛效应形成产生的促进作用明显大于自然因素的抑制作用,综合作用下地区将升温0.293℃。影响城市人居热环境的因素众多,多源数据有助于揭示城市热环境空间格局及演变规律,深化对城市热岛效应成因分析认知,明确人文和自然影响因素间相关关系和相关程度,以此为改善城市人居环境质量提供科学依据。 In view of the lack of comprehensive evaluation and analysis from the combination of natural and human multi-dimensional factors, the urban surface temperature patterns of Changsha in 2000, 2009 and 2016 are retrieved based on multi-source spatial data(Landsat 5,Landsat 8 satellite image data, POI spatial big data, digital elevation model, etc.), and 12 natural and human factors closely related to urban thermal environment are quickly obtained.The standard deviation ellipse method and spatial principal component analysis(PCA) method are used to analyze the effect of urban human residential thermal environment and the linkage of its influencing factors. The results show that:(1) During the 16 years from 2000 to 2016, the heat island area increased by 547 km^2, and the maximum surface temperature difference reached 10.1 ℃. The spatial distribution of urban heat island was mainly concentrated in urban built-up areas, such as industrial and commercial areas and densely populated urban centers.The spatial distribution pattern of heat island is gradually decreasing from the urban center to the suburbs. There were many high-temperature centers, such as Wuyi square business circle,Xingsha economic and technological development zone in Changsha County, Wangcheng industrial zone, Yuelu industrial concentration zone, and Tianxin industrial zone.(2) From 2000 to 2016, the main axis of spatial development of heat island maintained in the northeastsouthwest direction. From 2000 to 2009, the center of gravity of heat island shifted 2.7 km to the southwest, and the deflection angle was 54.9°;the center of gravity of heat island shifted to the northeast by 4.8 km, and the deflection angle was 60.9°. On the whole, the change of spatial pattern of thermal environment in Changsha was related to the change of urban construction intensity.(3) Through the principal component analysis method, it was concluded that the factors affecting the urban thermal environment pattern of Changsha were landscape pattern,urban construction intensity and landform.(4) The promotion effect of human factors on the formation of heat island effect was obviously greater than that of natural factors. Under the comprehensive effect, the temperature would rise by 0.293 units. There are many factors influencing the urban human settlements thermal environment. Multi-source data could help to reveal the spatial pattern and evolution law of urban thermal environment, deepen the understanding of the causes of urban heat island effect, and clarify the correlation and degree between human and natural factors, so as to provide scientific supports for the improvement of the quality of urban human settlements.
作者 熊鹰 章芳 XIONG Ying;ZHANG Fang(College of Architecture,Changsha University of Science and Technology,Changsha 410076,China;Hunan Key Lab of Land&Resource Evaluation&Utilization,Changsha 410007,China;Research Center of Resource Environment and Urban Planning,Changsha 410114,China)
出处 《地理学报》 EI CSSCI CSCD 北大核心 2020年第11期2443-2458,共16页 Acta Geographica Sinica
基金 国家社会科学基金项目(15BJY051) 国土资源评价与利用湖南省重点实验室开放课题(SYS-ZX-202002) 湖南省社会科学成果评审委员会课题(XSP18ZDI031)。
关键词 热环境 自然—人文影响因素 多源数据 空间主成分分析(PCA) 长沙市 thermal environment natural-human factor multi-source data spatial principal component analysis Changsha city
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