上海市人类活动对热环境的影响
收稿日期: 2007-07-11
修回日期: 2007-11-02
网络出版日期: 2008-03-25
基金资助
国家自然科学基金项目(40701177)
Impact of Human Activities on Urban Thermal Environment in Shanghai
Received date: 2007-07-11
Revised date: 2007-11-02
Online published: 2008-03-25
Supported by
National Natural Science Foundation of China, No.40701177
随着城市规模不断扩张, 由城市热岛现象而导致的热环境问题不断凸现。城市热环境 的时空变化, 是下垫面改变、人为热释放和环境污染等人类活动因素相互交织作用的结果。 由于城市热环境影响因子的复杂性, 传统观测手段和统计方法在获取数据和分析人类活动对 热环境响应机制方面存在着局限性。而卫星遥感和GIS 技术为人类活动对城市热环境的影响 分析提供了技术支撑。选用Landsat ETM+ 影像, 以上海市外环内区域为研究靶区, 在探讨热 环境的空间格局基础上, 运用空间主成分分析方法替代传统的多准则判断(MCE) 方法, 分析 了人类活动对城市热环境的影响特征。结果发现, 对于上海主城区而言, 城市建筑与人口密 度、工业区布局、下垫面类型以及城市景观多样性四个因子是影响城市热环境空间格局的主 导因子; 四个因子的线性模型, 较好地模拟了热环境的空间变化, 定量揭示了上海城市人类活动对热环境的影响机制。
岳文泽, 徐建华 . 上海市人类活动对热环境的影响[J]. 地理学报, 2008 , 63(3) : 247 -256 . DOI: 10.11821/xb200803003
The urban thermal environment effect resulted from urban heat island phenomena becomes prominent with the rapid urban expansion, which had adverse effect on the urban environment and the urban sustainable development. Spatial-temporal change of urban thermal environment is relevant to interactions of human activities such as the change of underlying surface, anthropogenic heat emission and environmental pollution. Due to the complexity of factors contributing to urban thermal environment, the routine observing methods and statistical methods are insufficient in acquiring data and analyzing the responses of human activities to thermal environment, especially discerning the major attributors from the others. Fortunately, the remote sensing and GIS can resolve the technical problem effectively, which can quantitatively explore the relationship of spatial-temporal change of thermal environment with human activities. Based on Landsat ETM+ images and taking the urban area inside the ring road of Shanghai as a case study, this paper employed Spatial Principal Component Analysis (PCA) method to analyze the spatial pattern and the influencing factors of urban thermal environment as a substitute of Multi-Criterion Evaluation (MCE) method. The results showed that urban construction density and population density, allocation of industries, types of underlying surface and diversity of urban landscape were the leading factors contributing to the urban thermal environment in the metropolitan area of Shanghai. The linear model including the four independent variables could reveal the response mechanism of human activities on thermal environment in Shanghai. From the model, urban building density and population aggregation were regarded as the most sensitive factors to thermal environment among these factors. Furthermore, the difference in spatial distributions of the main factors formation of the diverse urban thermal environment in different areas. The results would be of value to simulate spatial change of urban thermal environment and even put forward countermeasures to lessen the urban thermal environment intensity for policy makers.
Key words： urban thermal environment; factors; Principal Component Analysis; Shanghai
[1] Owen T W, Carlson T N, Gillies R R. An assessment of satellite remotely-sensed land cover parameters in quantitatively describing the climatic effect of urbanization. International Journal of Remote Sensing, 1998, 19: 1663-1681.
[2] Carlson T N, Arthur S T. The impact of land use-land cover changes due to urbanization on surface microclimate and hydrology: As satellite perspective. Global and Planetary Change, 2000, 25: 49-65.
[3] Zhou Shuzhen, Zhang Chao. On the Shanghai urban heat island effect. Acta Geographica Sinica, 1982, 37(4): 372-381.
[周淑贞, 张超. 上海城市热岛效应. 地理学报, 1982, 37(4): 372-381.]
[4] Chen Yunhao, Shi Peijun, Li Xiaobing. Research on spatial thermal environment in Shanghai City based on remote sensing and GIS. Acta Geodaetica et Cartographica Sinic, 2002, 31(2): 139-144.
[陈云浩, 史培军, 李晓兵. 基于遥感和 GIS 的上海城市空间热环境研究. 测绘学报, 2002, 31(2): 139-144.]
[5] Kim H H. Urban heat island. International Journal of Remote Sensing, 1992, 13(12): 2319-2336.
[6] Chrysoulaks N, Cartalis C. Thermal detection of plumes produced by industrial accidents in urban areas based on the presence of the heat island. International Journal of Remote Sensing, 2002, 23(14): 2909-2916.
[7] Lo C P, Quattrochi D A, Luvall J C. Application of high resolution thermal infrared remote sensing and GIS to assess the urban heat island effect. International Journal of Remote Sensing, 1997, 18(17): 287-304.
[8] Weng Q H. A remote sensing-GIS evaluation of urban expansion and its impact on surface temperature in the Zhujiang Delta, China. International Journal of Remote Sensing, 2001, 22(10): 1999-2014.
[9] Wilson J S, Clay M, Martin E. Evaluating environmental influence of zoning in urban ecosystems with remote sensing. Remote Sensing of Environment, 2003, 86: 303-321.
[10] Kato S, Yamaguchi Y. Analysis of urban heat-island effect using ASTER and ETM+ Data: Separation of anthropogenic heat discharge and nature heat radiation from sensible heat flux. Remote Sensing of Environment, 2005, 99: 44-54.
[11] Yuan F, Bauer M E. Comparison of impervious surface area and normalized difference vegetation index as indicators of surface urban heat island effects in Landsat imagery. Remote Sensing of Environment, 2007, 106: 375-386.
[12] Zhang Hsiaofei, Wang Yanglin, Wu Jiansheng et al. Study on land surface temperature vegetation cover relationship in urban region: A case in Shenzhen City. Geographical Research, 2006, 25(3): 369-379.
[ 张小飞, 王仰麟, 吴健生等. 城市地域地表温度—植被覆盖定量关系分析: 以深圳为例. 地理研究, 2006, 25(3): 369-379.]
[13] Wu Jiawei, Xu Jianhua, Tan Wenqi. Study on the relationship of urban heat island and vegetation abundance in Shanghai City. Remote Sensing Technology and Application, 2007, 22(1): 26-30.
[武佳卫, 徐建华, 谈文琦. 上海城市 热场与植被覆盖的关系研究. 遥感技术与应用, 2007, 22(1): 26-30.]
[14] Ji Chongping, Liu Weidong, Xuan Chunyi. Impact of urban growth on the heat island in Beijing. Chinese Journal of Geophysics, 2006, 49(1): 69-77.
[季崇萍, 刘伟东, 轩春怡. 北京城市化进程对城市热岛的影响研究. 地球物理学报, 2006, 49(1): 69-77.]
[15] Zhou Shuzhen, Su Jiong. Urban Climatology. Beijing: China Meteorological Press, 1994. 244-345.
[周淑贞, 束炯. 城 市气候学. 北京: 气象出版社, 1994. 244-345.]
[16] Sang Jianguo, Zhang Zhiyi, Zhang Boyin. Dynamical analyses on heat island circulation. Acta Meteorologica Sinica, 2000, 58(3): 321-327.
[桑建国, 张治坤, 张伯寅. 热岛环流的动力学分析. 气象学报, 2000, 58(3): 321-327.]
[17] Chen Shenbin, Pan Liqing. Effects of urbanization on the annual mean temperature of Beijing. Acta Geographica Sinica, 1997, 52(1): 27-36.
[陈沈斌, 潘莉卿. 城市化对北京平均气温的影响. 地理学报, 1997, 52(1): 27-36.]
[18] Zhou Jianhua, Sun Tianzong. Urban Remote Sensing. Shanghai: Shanghai Scientific and Technological Literature Press, 1995. 31-55.
[周坚华, 孙天纵. 城市遥感. 上海: 上海科学技术文献出版社, 1995. 31-55.]
[19] Markham B L, Barker J K. Spectral characterization of the LANDSAT Thematic Mapper sensors. International Journal of Remote Sensing, 1985, 6(5): 697-716.
[20] Weng Q H. A remote sensing-GIS evaluation of urban expansion and its impact on surface temperature in the Zhujiang Delta, China. International Journal of Remote Sensing, 2001, 22(10): 1999-2014.
[21] Song Yongchang, You Wenhui, Wang Xiangrong. Urban Ecology. Shanghai: East China Normal University Press, 2000. 317-320.
[宋永昌, 由文辉, 王祥荣. 城市生态学. 上海: 华东师范大学出版社, 2000. 317-320.]
[22] Weng Q H, Lu D S, Schubring J. Estimation of land surface temperature-vegetation abundance relationship for urban heat island studies. Remote Sensing of Environment, 2004, 89: 467-483.
[23] Wu C. Estimating impervious surface distribution by spectral mixture analysis. Remote Sensing of Environment, 2003, 84: 493-505.
[24] Li Xia, Yeh A G O. Application for spatial decision and urban simulation of principal component analysis and Cellular Automata. Science in China (Series D), 2001, 31(8): 683-690.
[ 黎夏, 叶嘉安. 主成分分析与Cellular Automata 在空 间决策与城市模拟中的应用. 中国科学(D 辑), 2001, 31(8): 683-690.]
[25] Xu Jianhua. Mathematical Methods in Contemporary Geography (2nd edn.). Beijing: Higher Education Press, 2002. 84-93.
[徐建华. 现代地理学中的数学方法. 北京: 高等教育出版社, 2002. 84-93.]
[26] Gao Zhiqiang, Liu Jiyuan, Zhuang Dafang. The relations analysis between ecological environmental quality of Chinese land resources and population. Journal of Remote Sensing, 1999, 3(1): 66-70.
[高志强, 刘纪远, 庄大方. 基于遥感和 GIS 的中国土地资源生态环境质量同人口分布的关系研究. 遥感学报, 1999, 3(1): 66-70.]
[27] Zhang Xiuying, Zhao Chuanyan. Study on a potential eco-environment evaluation based on GIS in Longzhong Loess Plateau. Journal of Lanzhou University (Natural Sciences), 2003, 39(3): 73-76.
[张秀英, 赵传燕. 基于GIS 的陇中黄 土高原潜在生态环境评价研究. 兰州大学学报(自然科学版), 2003, 39(3): 73-76.]
[28] Xu Jianhua, Yue Wenze, Tan Wenqi. A statistical study on spatial scaling effects of urban landscape pattern: A case study of the central area of the external circle highway in Shanghai. Acta Geographica Sinica, 2004, 59(6): 1058-1067.
[徐建华, 岳文泽, 谈文琦. 城市景观格局尺度效应的空间统计规律: 以上海中心城区为例. 地理学报, 2004, 59(6): 1058-1067.]
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