城市地表热通量遥感反演及与下垫面关系分析

doi:10.11821/xb201201011

摘要/Abstract

摘要： 选择日本埼玉县熊谷市为研究区,应用ASTER热红外遥感图像,采用PCACA模型以及理论定位算法,对城市地表热通量的相关参数进行反演,进而分析城市下垫面不同土地覆盖类型对地表热通量以及能量平衡的影响。结果表明,PCACA模型应用于城市区域地表通量估算是可行的。这种算法可以大大减少在下垫面结构复杂的城市区域进行地表热通量估算时所需的参数,并有效降低研究结果的不确定性。研究发现,城乡不同下垫面地表覆盖类型对地表热通量的影响差异显著。不同地表下垫面类型的波文比由大到小顺序依次为:工业用地>住宅用地> 交通用地> 公共设施用地> 旱田> 公共绿地> 水域。在相同的外部气象条件下,与城市周边的植被覆盖区相比,城市人工建筑用地具有较高的显热通量,较低的潜热通量,以及较高的波文比。由于城市地表显热通量和波文比明显高于周边植被覆盖地表,导致城市地表向低层大气供热的增加,这是城市热岛效应形成的重要机制之一。

关键词: 地表通量, 显热, 潜热, 城市土地覆盖, 遥感, 日本熊谷市

Abstract: This study extracted urban surface heat flux parameters based on PCACA model using ASTER infrared remote sensing image, and then analyzed the impacts on urban surface heat flux and energy balance from different land cover types in the experimental area of Kumagaya City, Saitama Prefecture of Japan. The results indicate that this method on application PCACA model to estimate surface flux in urban areas is feasible. This algorithm can greatly reduce the complexity of the underlying surface structure of the urban areas of surface heat flux estimates, and decrease the uncertainty of the results. The study found that urban and rural areas of different land cover types on the surface heat flux were significantly different. According to urban land use and cover types, Bowen ratio is industrial, residential, traffic, establishment, dry field, public green and water body in a descending order. In the same weather conditions, surrounding vegetation and urban areas compared to urban land has a high sensible heat flux, the lower the latent heat flux, and the higher Bowen ratio. The urban surface sensible heat flux and Bowen ratio was significantly higher than that of the surrounding vegetation surface, leading to urban surface heating of the lower atmosphere. This is an important mechanism for the formation of urban heat island effect.

Key words: surface flux, sensible heat, latent heat, urban land cover, remote sensing, Kumagaya city of Japan

刘越, Shintaro Goto, 庄大方, 匡文慧. 城市地表热通量遥感反演及与下垫面关系分析[J]. 地理学报, 2012, 67(1): 101-112.

LIU Yue, Shintaro Goto, ZHUANG Dafang, KUANG Wenhui. Urban Surface Heat Flux Inversion Based on Infrared Remote Sensing and the Relationship with Land Cover[J]. Acta Geographica Sinica, 2012, 67(1): 101-112.

参考文献

[1] IGBP Secretariat. GLP science plan and implementation strategy. Stockholm, IGBP Report No.53/IHDP ReportNo.2005, 2005.
[2] McMahon G, Benjamin S P, Clarke K et al. Geography for a changing world: A science strategy for the geographicresearch of the U.S. Geological Survey, 2005-2015, Sioux Falls, SD: U.S. Geological Survey Circular, 2005, 1281: 1-76.
[3] Rindfuss R, Walsh S, Turner B L et al. Developing a science of land change: Challenges and methodological issues.PNAS, 2004, 101: 13976-13981.
[4] Foley A. Global consequences of land-use. Science, 2005, 309: 570-574.
[5] Grimm N B, Faeth S H, Golubiewski N E et al. Global change and the ecology of cities. Science, 2008, 319: 756-760.
[6] Alberti M. Advances in urban ecology integrating humans and ecological processes in urban ecosystems. New York:Springer science + business media, 2009.
[7] Pickett S A, Cadenasso M L, Grove J M et al. Urban ecological systems: Scientific foundations and a decade ofprogress. Journal of Environment Management, 2011, 92: 331-362.
[8] IHDP. Urbanize and global environment change. Germany: International Human Dimensions Programme on GlobalEnvironmental Change, 2005.
[9] Bierwagen B G, heobald D T, Pyke C R et al. National housing and impervious surface scenarios for integrated climateimpact assessments. PNAS, 2010, 10: 1073-1078.
[10] Parrish D, Zhu Tong. Clean air for megacities. Science, 2009, 326(30): 674-675.
[11] Batty. The size, scale, and shape of cities. Science, 2008, 319: 769-771.
[12] Agardy T, Alder J, Dayton P. Ecosystems and human well-being: Coastal systems. MA, 2003: 513-549.
[13] Kalnay E, Cai M. Impact of urbanization and land-use change on climate. Nature, 2003, 423: 528-531.
[14] Russell S V, Thomas R K, David R E et al. Impact of land-use change on climate. Nature, 2004, 427: 213-214.
[15] Hansen J E. A closer look at United States and global surface temperature change. Journal of Geophysical Research,2001, 106: 23947-23963.
[16] Gallo K P, Owen T W, Easterling D R et al. Temperature trends of the US historical climatology network based onsatellite-designated land use/land cover. Journal of Climate, 1999, 12(5): 1344-1348.
[17] David E P. Large-scale warming is not urban. Nature, 2004, 432: 290-290.
[18] Thomas C P. Assessment of urban versus rural in situ surface temperatures in the contiguous United States: Nodifference found. Journal of Climate, 2004, 16(18): 2941-2959.
[19] He J F, Liu J Y, Zhang D F et al. Assessing the effect of land use/land cover change on the change of urban heatisland intensity. Theoretical and Applied Climatology, 2007, 90: 217-226.
[20] Oke T. The surface energy budgets of urban areas//Hosker P R. Modeling the Urban Boundary Layer. Boston: AMS,1987.
[21] Lu D S, Weng Q. Spectral mixture analysis of ASTER images for examining the relationship between urban thermalfeatures and biophysical descriptors in Indianapolis. Remote Sensing of Environment, 2006, 104(2): 157-167.
[22] Shao Quanqin, Sun Chaoyang, Liu Jiyuan et al. Impact of urban expansion on meteorological observation data andoverestimation to regional air temperature in China. Acta Geographica Sinica, 2009, 64(11): 1292-1302. [邵全琴, 孙朝阳, 刘纪远等. 中国城市扩展对气温观测的影响及其高估程度. 地理学报, 2009, 64(11): 1292-1302.]
[23] Watarai Y, Nakagawa K, Fukuoka Y. Numerical simulation of the intense heat over the central Kanto plain in 15-16August 2007, using the regional meteorological model. Japanese Journal of Biometeorology, 2009, 46(1): 35-41.
[24] Gillespie A R, Rokugawa S. Temperature/eEmissivity separation algorithm theoretical basis document, version 2.4 [M/OL]. Prepared under NASA Contract NAS5~31372, 1999. http://eospso.gsfc.nasa.gov/eos-homepage/for-scientists /atbd/docs/ASTER.
[25] Li Haitao, Tian Qingjiu. An introduction to ASTER data and ASTER mission. Remote Sensing Information, 2004, (3):53-56. [李海涛, 田庆久. ASTER 数据产品的特性及其计划介绍. 遥感信息, 2004, (3): 53-56.]
[26] Bastiaanssen W G M. Regionalization of surface flux densities and moisture indicators in composite terrain. TheNetherlands, Wageningen: Agr Res Dept, 1995, Report 109.
[27] Su Z. The surface energy system (SEBS) for estimation of turbulent heat fluxes. Hydrology and Earth SystemSciences, 2002, 6(1): 85-99.
[28] Norman J M, Kustas W P, Humes K S. Source approach for estimating soil and vegetation energy fluxes inobservations of directional radiometric surface temperature. Agricultural and Forest Meteorology, 1995, 77: 263- 293.
[29] Zhang Renhua. Quantity Infrared Remote Sensing Model and the Ground Experiment Base. Beijing: Science Press,2009. [张仁华. 定量热红外遥感模型及地面实验基础. 北京: 科学出版社, 2009.]
[30] Zhang R H. An operational two-layer remote sensing model to estimate surface flux in regional scale: Physicalbackground. Science in China: Series D, 2005, 48(Suppl.1): 225-244.
[31] Zhang Renhua. Thermal inertia of soil moisture model and its application. Chinese Science Bulletin, 1991, (12):924-927. [张仁华. 土壤含水量的热惯量模型及其应用. 科学通报, 1991, (12): 924-927.]
[32] Zhang Renhua, Li Zhaoliang, Sun Xiaomin et al. On the applicability of Kirchoff's law and the principle of heatbalance in thermal infrared remote sensing: A non-isothermal system. Science in China: Series D, 2004, 34(4):350-358. [张仁华, 李召良, 孙晓敏等. 非同温系统中基尔霍夫定律的适用性和热量平衡原理. 中国科学: D 辑,2004, 34(4): 350-358.]
[33] Zhang R H, Sun X M, Zhu Z L et al. A remote sensing model for monitoring soil evaporation based on differentialthermal inertia and its validation. Science in China: Series D, 2003, 46(4): 342-355.
[34] Zhu Zhilin, Sun Xiaomin, Yuan Guofu et al. Calibration method of eddy covariance flux in heterogeneous surfaceconditions and their application in ChinaFLUX. Science in China: Series D, 2004, 34 (Suppl. II): 37-45. [朱志林, 孙晓敏, 袁国富等. 非平坦下垫面涡度相关通量的校正方法及其在ChinaFLUX 中的应用. 中国科学: D辑, 2004, 34(增刊II): 37-45.]
[35] Anderson M C, Norman J M, Diak G R et al. A two-source time-integrated model for estimating surface fluxes usingthermal infrared remote sensing. Remote Sensing of Environment, 1997, 60: 195-216.
[36] Niemela S. Comparison of surface radiative flux parameterizations (Part I): Longwave radiation. AtmosphericEnvironment, 2001, 58: 1-8.
[37] Liang S L. Narrowband to broadband conversions of land surface albedo algorithms. Remote Sensing of Environment,2000, 76: 213-238.
[38] Kotoda K. Estimation of river basin évapotranspiration. Univ. Tsukuba, Environ Res (Center Papers), 1986.
[39] Kotoda K, Sakura Y, Hayashi Y et al. On the observation and data acquisition system for the heat and water balancestudies of ERC experimental field. Bull. Environ. Res. Cent. Univ. Tsukuba, 1978, 2: 65-89.
[40] Kotoda K. A simple method to estimate total solar radiation on a slope surface considering direct and diffuse components. Journal of Agricultural Meteorology, 1986, 42: 249-259.
[41] Oke T R, Fuggle R F. Comparison of urban/rural counter and net radiation at night. Boundary-Layer Meteorology,1972, 2: 290-308.
[42] Kondo J. Atmospheric Science near the Ground Surface. Tokyo: University of Tokyo Press, 2000.
[43] Wang Xiuxin, Zhu Qijiang, Chen Shenghai et al. Analysis of water, heat and CO2 fluxes on urban green space. ActaEcologica Sinica, 2007, 27(8): 3232-3239. [王修信, 朱启疆, 陈声海等. 城市公园绿地水、热与CO2通量观测与分析. 生态学报, 2007, 27(8): 3232-3239.]