基于MODIS地表温度的气温估计方法及其在中国东部城市群热岛效应研究中的应用
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摘要
随着城市化的快速发展,研究城市化的热岛效应变得日益重要。本文利用MODIS地表温度、地表覆盖类型产品和台站气温观测资料,建立了中国东部城市群地区区域尺度的气温估计模型,得到了高分辨率的长江三角洲地区和京津唐地区的最高气温场,并分析了长江三角洲地区和京津唐地区近十年城市热岛变化及其与城市群发展的关系研究,主要工作如下：
1.利用MODIS地表覆盖类型资料和站点气温资料,建立了区域气温估计模型,并对模型做了独立样本检验,结果表明：不同地表覆盖类型下MODIS白天地表温度和站点最高气温间相关性较好,可以利用该关系来估计近地面气温,并得到了高分辨率(1km)的城市群最高气温场；最高气温估计值平均绝对误差在2℃-3℃之间,长江三角洲地区的气温估计模型精度略高于京津唐地区；对上述气温估计模型进行了误差分析,发现地表温度数据精度是气温估计误差的来源之一,经提高后,气温估计值精度有了一定程度的提高,提升幅度在0.5℃以内。
2.对2009年长江三角洲地区和2001年京津唐地区基于地表温度和最高气温估计值的热岛的季节变化的研究结果表明,无论是在城市热岛强度还是城市带对区域增温的贡献上看,城市热岛效应都以春夏两季最强,秋季次之,冬季最弱。
3.利用长江三角洲地区和京津唐地区2001-2010夏季平均的MODIS地表温度及最高气温估计值,对研究区近十年热状况的变化特征进行了研究,结果表明,自2001年以来,长江三角洲地区夏季白天热岛区的面积不断增长,导致该区域热状况过渡区面积大幅减小。其中强热岛区的范围呈现出快速增长的趋势,各城市群又以苏锡常城市群的增速为最大,该城市群热岛与上海热岛已连成一体成为了大城市群热岛区,并沿海岸线有向杭州湾发展连成更大城市群热岛区的趋势。同时,京津唐地区夏季热岛区的面积也在不断增长,使得城市群内部各城市间热岛连成了一体,并有向其他城市发展的趋势,其中以北京-廊坊-天津城市带最为明显。
4.对近十年城市、城郊和乡村地区温度的变化与城市群城市化进程之间的关系的研究表明,长江三角洲地区的温度变化与夜间灯光灰度值的变化的关系密切,城郊地区的温度增温幅度最大,夜间灯光灰度值的加强趋势也最高,乡村次之,城市地区则几乎没有增温,夜间灯光加强趋势也最小,表明温度的精细变化与城市化进程有着相当密切的联系。将近十年京津唐地区温度的变化分布图与夜间灯光灰度值变化的分布图结合起来看,发现城市化变化最大的城郊地区,温度处于明显的上升趋势；乡村和城市中心区城市化基本无变化,而温度也无变化或有微弱的降温趋势,表明了温度变化与城市化进程之间密切的联系。
With the rapid urbanization around the globe, the urban heat island (UHI) effects have received considerable attention by scientists. In this paper, high resolution MODIS daytime land surface temperature (LST), MODIS land cover types, DMSP/OLS nighttime light imagery and meteorological stations data were used to estimate the regional surface air temperature. Spatial patterns and variability of UHI over Yangtze River Delta area and Beijing-Tianjin-Tangshan metropolitan area were analized.
(1) Based on the remote sensing data from MODIS and ground stations data, a simple statistical model was developed. The accuracy of the model was analyzed. Results show that the linear relationships between MODIS land surface temperature and stations daily maximum air temperature are significant. The2008-2009data was used for the training, and2001-2003data was used for accuracy assessment of the model. It is found that the error (mean absolute error) of the estimated surface air temperature is2℃-3℃. The estimated value has slightly lower error over Yangtze River Delta area than that over Beijing-Tianjin-Tangshan Metropolitan Area. For error analysis, we improve the MODIS land surface temperature data accuracy by using best quality values only, results show that it is successeful to increase the accuracy of the model to about2℃. However, this study has used LST data at all quality levels in develping the statistical model as using best quality data will reduce dramatically the valid data points.
(2) By analyzing the seasonal variation of UHI in2009over Yangtze River Delta area and in2001over Beijing-Tianjin-Tangshan Metropolitan Area, results show that the UHI effect observed from the daytime Ts is most significant in the spring and summer; weaker in the autumn, and is not significant in the winter.
(3) Analyzing the2001-2010summer MODIS LST and estimaed surface air temperature over Yangtze River Delta area and Beijing-Tianjin-Tangshan Metropolitan Area, we found that during last decade, the heat island areas over the Yangtze River Delta region are increased rapidly, leading to significant decreases in the size of temperature transition region. The strong heat island areas increase fastest, especially in the Suzhou-Wuxi-Changzhou city cluster. The number and size of UHI over the Yangtze River Delta region are grown very fast, connecting each other gradually and forming a giant heat island. At the same time, the heat island areas over Beijing-Tianjin-Tangshan Metropolitan Area region are also increased rapidly, especially in the Beijing-Langfang-Tianjin city cluster.
(4) By analyzing the relationship between the change of temperature and the different urbanization area over the study areas, the change of mean temperature is highly correlated to the change of the nighttime lights, the spatial correlation coefficient between mean temperature and nightlight values was high, indicating that the human activity (urbanization) is highly responsible for the local temperature change.
1.利用MODIS地表覆盖类型资料和站点气温资料,建立了区域气温估计模型,并对模型做了独立样本检验,结果表明：不同地表覆盖类型下MODIS白天地表温度和站点最高气温间相关性较好,可以利用该关系来估计近地面气温,并得到了高分辨率(1km)的城市群最高气温场；最高气温估计值平均绝对误差在2℃-3℃之间,长江三角洲地区的气温估计模型精度略高于京津唐地区；对上述气温估计模型进行了误差分析,发现地表温度数据精度是气温估计误差的来源之一,经提高后,气温估计值精度有了一定程度的提高,提升幅度在0.5℃以内。
2.对2009年长江三角洲地区和2001年京津唐地区基于地表温度和最高气温估计值的热岛的季节变化的研究结果表明,无论是在城市热岛强度还是城市带对区域增温的贡献上看,城市热岛效应都以春夏两季最强,秋季次之,冬季最弱。
3.利用长江三角洲地区和京津唐地区2001-2010夏季平均的MODIS地表温度及最高气温估计值,对研究区近十年热状况的变化特征进行了研究,结果表明,自2001年以来,长江三角洲地区夏季白天热岛区的面积不断增长,导致该区域热状况过渡区面积大幅减小。其中强热岛区的范围呈现出快速增长的趋势,各城市群又以苏锡常城市群的增速为最大,该城市群热岛与上海热岛已连成一体成为了大城市群热岛区,并沿海岸线有向杭州湾发展连成更大城市群热岛区的趋势。同时,京津唐地区夏季热岛区的面积也在不断增长,使得城市群内部各城市间热岛连成了一体,并有向其他城市发展的趋势,其中以北京-廊坊-天津城市带最为明显。
4.对近十年城市、城郊和乡村地区温度的变化与城市群城市化进程之间的关系的研究表明,长江三角洲地区的温度变化与夜间灯光灰度值的变化的关系密切,城郊地区的温度增温幅度最大,夜间灯光灰度值的加强趋势也最高,乡村次之,城市地区则几乎没有增温,夜间灯光加强趋势也最小,表明温度的精细变化与城市化进程有着相当密切的联系。将近十年京津唐地区温度的变化分布图与夜间灯光灰度值变化的分布图结合起来看,发现城市化变化最大的城郊地区,温度处于明显的上升趋势；乡村和城市中心区城市化基本无变化,而温度也无变化或有微弱的降温趋势,表明了温度变化与城市化进程之间密切的联系。
With the rapid urbanization around the globe, the urban heat island (UHI) effects have received considerable attention by scientists. In this paper, high resolution MODIS daytime land surface temperature (LST), MODIS land cover types, DMSP/OLS nighttime light imagery and meteorological stations data were used to estimate the regional surface air temperature. Spatial patterns and variability of UHI over Yangtze River Delta area and Beijing-Tianjin-Tangshan metropolitan area were analized.
(1) Based on the remote sensing data from MODIS and ground stations data, a simple statistical model was developed. The accuracy of the model was analyzed. Results show that the linear relationships between MODIS land surface temperature and stations daily maximum air temperature are significant. The2008-2009data was used for the training, and2001-2003data was used for accuracy assessment of the model. It is found that the error (mean absolute error) of the estimated surface air temperature is2℃-3℃. The estimated value has slightly lower error over Yangtze River Delta area than that over Beijing-Tianjin-Tangshan Metropolitan Area. For error analysis, we improve the MODIS land surface temperature data accuracy by using best quality values only, results show that it is successeful to increase the accuracy of the model to about2℃. However, this study has used LST data at all quality levels in develping the statistical model as using best quality data will reduce dramatically the valid data points.
(2) By analyzing the seasonal variation of UHI in2009over Yangtze River Delta area and in2001over Beijing-Tianjin-Tangshan Metropolitan Area, results show that the UHI effect observed from the daytime Ts is most significant in the spring and summer; weaker in the autumn, and is not significant in the winter.
(3) Analyzing the2001-2010summer MODIS LST and estimaed surface air temperature over Yangtze River Delta area and Beijing-Tianjin-Tangshan Metropolitan Area, we found that during last decade, the heat island areas over the Yangtze River Delta region are increased rapidly, leading to significant decreases in the size of temperature transition region. The strong heat island areas increase fastest, especially in the Suzhou-Wuxi-Changzhou city cluster. The number and size of UHI over the Yangtze River Delta region are grown very fast, connecting each other gradually and forming a giant heat island. At the same time, the heat island areas over Beijing-Tianjin-Tangshan Metropolitan Area region are also increased rapidly, especially in the Beijing-Langfang-Tianjin city cluster.
(4) By analyzing the relationship between the change of temperature and the different urbanization area over the study areas, the change of mean temperature is highly correlated to the change of the nighttime lights, the spatial correlation coefficient between mean temperature and nightlight values was high, indicating that the human activity (urbanization) is highly responsible for the local temperature change.
引文
[1]周淑贞,束炯城市气候学[M].北京：气象出版社,1994,1-9.
[2]Trenberth K E, Jones P D, Ambenje P, et al.. Observations:Surface and atmospheric climate change. Climate Change 2007:The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge, United Kingdom and New York, NY, USA:Cambridge University Press, 301-403
[3]Bornstein R D. Observations of the urban heat island effect in New York City.1968,7: 575-582.
[4]Oke T R. The energetic basis of the urban heat island[J]. Quarterly Journal of the Royal Meteorological Society,1982,108(455):1-24.
[5]Owen T W, T N Carlson, R R Gillies. An assessment of satellite remotely-sensed land cover parameters in quantitatively describing the climatic effect of urbanization[J]. International Journal of Remote Sensing,1998,19(9):1663-1681.
[6]Baker L A, A J Brazel, N Selover, et al. Urbanization and warming of phoenix(Arizona, USA):Impacts, feedbacks and mitigation[J]. Springer,2002,6:183-203.
[7]Chen X L, H M Zhao, P X Li, et al. Remote sensing image-based analysis of the relationship between urban heat island and land use/cover changes [J]. Remote Sensing of Environment, 2006,104(2):133-146.
[8]Zhang X, T Zhong, K Wang, et al. Scaling of impervious surface area and vegetation as indicators to urban land surface temperature using satellite data[J]. International Journal of Remote Sensing,2009,30(4):841-859.
[9]Song Y B. Influence of new town development on the urban heat island-The case of the Bundang area[J]. Journal of Environmental Sciences-China,2005,17(4):641-645.
[10]Santamouris M, N Papanikolaou, I Livada, et al. On the impact of urban climate on the energy consumption of buildings[J]. Solar Energy,2001,70(3):201-216.
[11]Santamouris M, K Paraponiaris, G Mihalakakou. Estimating the ecological footprint of the heat island effect over Athens, Greece[J]. Climatic Change,2007,80(3-4):265-276.
[12]Junk J, A Helbig, J Luers. Urban climate and air quality in Trier Germany [J]. International Journal of Biometeorology,2003,47(4):230-238.
[13]汝信,陆学艺,李培林.社会蓝皮书：2012年中国社会形势分析与预测[M].北京：社会科学文献出版社,2011：2-3.
[14]Oke T R. City size and the urban heat island [J]. Atmospheric Environment,1967,7(8): 769-779.
[15]Katsoulis B D, Theoharatos G A. Indications of the Urban Heat Island in Athens, Greece [J]. Journal of Climate and Applied Meteorology,1985,24.
[16]Landberg H E. The climate of towns Man's role in changing the face of the Earth [M]. University of Chicago Press,1956.
[17]Rudolf B, Marie B. An urban bias in air temperature fluctuations at the Klementinum, Prague, the Czech Republic [M]. Atmospheric Environment,1999,33:4211-4217.
[18]Giridharan B, Ganesan S, Lau S S Y. Daytime urban heat island effect in high-rise and high-density residential developments in Hong Kong [J]. Energy and Buildings,2004, 36(6):525-534.
[19]Goodridge J D. Urban bias influences on long-term California air temperature trends [J]. Atmosp Environ,1992,26B (1):1-7.
[20]Hughes W E, Balling R C. Urban influences on South African temperature trends [J]. Int J Climatol,1996,16:935-940.
[21]初子莹,任国玉.北京地区城市热岛强度变化对区域温度序列的影响[J].气象学报, 2005,63：534-540.
[22]刘学峰,于长文,任国玉.河北省城市热岛强度变化对区域地表平均气温序列的影响[J]气候与环境研究,2005,10(4)：763-770.
[23]陈正洪,王海军,任国玉.武汉市城市热岛强度非对称性变化[J].气候变化研究进展,2003,3(5)：282-286.
[24]张玲,徐宗学,阮本清.北京城市热岛效应对气温和降水量的影响[J].自然资源学报,2006,21(5)：746-755.
[25]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[J].地球物理学报,2006,49(1)：69-77.
[26]周淑贞,张超.上海城市热岛效应[J].地理学报,1982,37：372-381.
[27]Kenneth M, Hinkel, Frederick E, et al. The urban heat island in winer at Barrow, Alaska [J]. Int J Climatol,2003,23:1889-1905.
[28]Gedzelman S, Austin R, Cermak, et al. Mesoscale aspects of the Urban Heat Island around New York City [J]. Theor. Appl. Climatol,2003,75:29-42.
[29]郑敬刚,张景光,李有.郑州市热岛效应研究与人体舒适度评价[J].应用生态学报,2005,16(10)：1838-1842.
[30]张一平,何云玲,马友鑫等.昆明城市热岛效应立体分布特征[J].高原气象,2002,21(6)：604-609.
[31]Czajkowski K P, Goward S N, Stadler S, et al. Thermal Remote Sensing of Near Surface Environmental Variables:Application over the Oklahoma Mesonet [J]. The Professional Geographer,2000,52(2):345-357.
[32]侯英雨,张佳华,延昊等.利用卫星遥感资料估算区域尺度空气温度[J].气象,2010,36(4)：75-79.
[33]Christelle V, Pietro C, Tufa D, et al. Evalution of MODIS land surface temperature data to estimate air temperature in different ecosystems over Africa [J]. Remote Sensing of Environment,2010,114:449-465.
[34]Cresswell M P, Morse A P, Thomson M C, et al. Estimating surface air temperatures, from Meteosat land surface temperatures, using an empirical solar zenith angle model [J]. International Journal of Remote Sensing,1999,20(6):1125-1132.
[35]Mostovoy G V, King R L, Reddy K R, Kakani V G, et al. Statistical estimation of daily maximum and minimum air temperatures from MODIS LST data over the state of Mississippi[J]. GIScience and Remote Sensing,2006,43(1):78-110.
[36]Prince S D, Goetz S J, Dubayah R O, et al. Inference of surface and air temperature, atmospheric precipitable water and vapor pressure deficit using advanced very high-resolution radiometer satellite observations:Comparison with field observations [J]. Journal of Hydrology,1998,213(1-4):230-249.
[37]Stisen S, Sandholt I, Norgaard A, Fensholt R, et al. Estimation of diurnal air temperature using MSG SEVIRI data in West Africa [J]. Remote Sensing of Environment,2007,110(2): 262-274.
[38]Nemani R R, Running S W. Estimation of regional surface-resistance to evapotranspiration from NDVI and thermal-IR AVHRR data [J]. Journal of Applied Meteorology,1989,28(4): 276-284.
[39]Goward S N, Waring R H, Dye D G, et al. Ecological remote-sensing at OTTER-Satellite macroscale observations[J]. Ecological Applications,1994,4:322-343.
[40]Prince S D, Goward S N. Global primary production:A remote sensing approach [J]. Journal of Biogeography,1995,22(4-5):815-835.
[41]Prihodko L, Goward S N. Estimation of air temperature from remotely sensed surface observations [J]. Remote Sensing of Environment,1997,60(3):335-346.
[42]Goetz S J, Prince S D, Small J. Advances in satellite remote sensing of environmental variables for epidemiological applications. Advances in Parasitology[J],2000,47:289-307.
[43]Stisen S, Sandholt I, Norgaard A, et al. Estimation of diurnal air temperature using MSG SEVIRI data in West Africa [J]. Remote Sensing of Environment,2007,110(2):262-274.
[44]Saravanapavan T, Dye D G. Satellite estimation of environmental variables by the contextual analysis method:validation in seasonal tropical environment [G]. Global Engineering Laboratory Institute of Industrial Science University of Tukyo, Janpan,1995.
[45]Czajkowski K P, Mulhern T, Goward S N, et al. Biospheric environmental monitoring at BOREAS with AVHRR observations [J]. Journal of Geophysical Research,1997,102: 29651-29662.
[46]Rao P K. Remote sensing of urban "hear islands" from an environmental satellite [J]. Bullutin American Metenmi Soc.,1972,53:647-648.
[47]Carlson T N, Augusfin J A, Boland F E. Potential application of satellite temperatures measurements in the analysis of land use over urban areas [J]. Bull. Amer. Meteor. Soc., 1977,58:1301-1303.
[48]Bailing R C, Brazel S W. High-resolution surface-temperature patterns in a complex urban terrain [J]. Photographic Engineering Remote Sensing Review,1988,54:1289-1293.
[49]Roth M, Oke T R, Emery W J. Satellite-derived urban heat island from three coastal cities and the utilization of such data in urban climatology [J]. International Journal of Remote Sensing,1989,10(11):1699-1720.
[50]延昊,邓莲堂.利用遥感地表参数分析上海市的热岛效应及治理对策[J].热带海洋学报,2004(20)：579-585.
[51]苏万楷,张文,刘波等.成都市城市热岛分析[J].四川林业科技,2006,27(3)：57-66.
[52]周红妹,周成虎,葛伟强等.基于遥感和GIS的城市热场分布规律研究[J].地理学报,2001,56(2)：189-197.
[53]Camahan W H, Larson R C. An analysis of an urban heat sink [J]. Remote sensing of Environment,1990,33:65-71.
[54]Nichol J E. A GIS-based approach to microclimate monitoring in Singapore's high-rise housing estates [J]. Photogrammetric Engineering and Remote Sensing,1994,60(10): 1225-1232.
[55]Bekele G. Assessing Urban Heat Island in Morgantown, WV Using Landsat Thermal Infrared Imagery.2002, http//:geo.wvu/geog655/spring2002/01/project.htm.
[56]Baumann P R. An Urban Heat Island Washington, D. C.2002:http//: www.onenota.edu/faculty/baumann/goosat2/urban_heat_island/urban_heat_island.htm.
[57]覃志豪,Zhang Minghua, Arnon Kanieli等.用陆地卫星TM6数据演算地表温度的单窗算法[J].地理学报,2001,56(4)：456-466.
[58]陈云浩,李京,李晓兵.城市空间热环境[M].北京：科学出版社,2003.
[59]张穗,何报寅,杜耘.武汉市城区热岛效应的遥感研究[J].长江流域资源与环境,2003,12(5)：445-449.
[60]宫阿都,江樟焰,李京等.基于Landset TM图像的北京城市地表温度遥感反演研究[J].遥感信息,2005(3)：18-22.
[61]何全军,吴志军,张月维.利用MODIS热红外数据进行广州市夏季热场分析[J].遥感技术与应用,2005,20(5)：501-505.
[62]黄荣峰,徐涵秋.利用Landsat ETM+影像研究土地利用/覆盖与城市热环境的关系[J].遥感信息,2005,5：36-39.
[63]田振坤,黄妙芬,刘良云等.使用单窗算法研究北京城区热岛效应[J].遥感信息,2006,1：21-24.
[64]江志红,叶丽梅.近十年南京城市热岛演变的遥感研究[J].南京信息工程大学学报(自然科学版),2010,2(2)：148-154.
[65]Streutker D R. Satellite-measured growth of the urban heat island of Houston, Texas [J]. Remote sensing of Environment,2003,85:282-289.
[66]Streutker D R. A remote sensing study of the urban heat island of Houston, Texas [J]. International Journal of Remote Sensing,2002,23(13):2595-2608.
[67]范天锡,潘钟跃.北京地区城市热岛特性的卫星遥感[J].气象,1987,13(10)：29-32.
[68]张佳华,侯英雨,李贵才等.北京城市及周边热岛日变化及季节特征的卫星遥感研究与影响因子分析[J].中国科学D辑,2005,35(增刊)：187-194.
[69]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[J].测绘学报,2002,31(2)：139-144.
[70]徐涵秋.利用改进的归一化差异水体指数(MNDWI)提取水体信息的研究[J].遥感学报,2005,5：589-595.
[71]谢志清,杜银,曾燕等.长江三角洲城市带扩展对区域温度变化的影响[J].地理学报,2007,62(7)：717-727.
[72]倪敏莉,申双和,张佳华.长江三角洲城市群热环境研究[J].大气科学学报,2009,32(5)：711-715.
[73]葛伟强,周红妹,杨何群.基于MODIS数据的近8年长三角城市群热岛特征及演变分析[J].气象,2010,36(11)：77-81.
[74]饶胜,张惠远,金陶陶等.基于MODIS的珠江三角洲地区区域热岛的分布特征[J].地理研究,2010,29(1)：127-136.
[75]Zeng Yongnian, Huang Wei, Zhan F. Benjamin, et al. Study on the urban heat island effects and its relationship with surface biophysical characteristics using MODIS imageries[J]. Geo-spatial Information Science,2010,13(1):1-7.
[76]Wan Z. MODIS Land Surface Temperature Products Users'Guide[EB/OL].2007, available online:http://www.icess.ucsb.edu/modis/LstUsrGuide/MODIS_LST_products_Users_guide_C5.pdf.
[77]Strahler A. MODIS land cover product algorithm theoretical basis document[EB/OL]. 1999, available online:http://modis.gsfc.nasa.gov/data/atbd/atbd_mod12.pdf.
[78]Wan Z. MODIS land-surface temperature algorithm theoretical basis document[EB/OL]. 1999, available online:http://modis.gsfc.nasa.gov/data/atbd/atbd mod11.pdf.
[79]Wan Z, Li Z L. Radiance-based validation of the V5 MODIS land-surface temperature product[J]. International Journal of Remote Sensing,2008,29:5373-5395.
[80]Coll C, Wan Z, Galve J M. Temperature-based and radiance-based validations of the V5 MODIS land surface temperature product[J]. Journal of Geophysical Research,2009, doi: 10.1029/2009 JD012038.
[81]杨眉,王世新,周艺等DMSP/OLS夜间灯光数据应用研究综述[J].遥感技术与研究,2011,26(1)：45-51.
[82]Croft T A. Nighttime images of the earth from space[J]. Scientific American,1978,239: 86-89.
[83]He Chunyang, Shi Peijun, Li Jinggang, et al. Restoring urbanization process in China in the 1990s by using non-radiance-calibrated DMSP/OLS nighttime light imagery and statistical data[J]. Chinese Science Bulletin,2006,51(13):1614-1620.
[84]Elvidge C D, Baugh K E, Kihn E A, et al. Mapping of city lights using DMSP Operational Linescan System data[J]. Photogrammetric Engineering and Remote Sensing,1997,63: 727-734
[2]Trenberth K E, Jones P D, Ambenje P, et al.. Observations:Surface and atmospheric climate change. Climate Change 2007:The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge, United Kingdom and New York, NY, USA:Cambridge University Press, 301-403
[3]Bornstein R D. Observations of the urban heat island effect in New York City.1968,7: 575-582.
[4]Oke T R. The energetic basis of the urban heat island[J]. Quarterly Journal of the Royal Meteorological Society,1982,108(455):1-24.
[5]Owen T W, T N Carlson, R R Gillies. An assessment of satellite remotely-sensed land cover parameters in quantitatively describing the climatic effect of urbanization[J]. International Journal of Remote Sensing,1998,19(9):1663-1681.
[6]Baker L A, A J Brazel, N Selover, et al. Urbanization and warming of phoenix(Arizona, USA):Impacts, feedbacks and mitigation[J]. Springer,2002,6:183-203.
[7]Chen X L, H M Zhao, P X Li, et al. Remote sensing image-based analysis of the relationship between urban heat island and land use/cover changes [J]. Remote Sensing of Environment, 2006,104(2):133-146.
[8]Zhang X, T Zhong, K Wang, et al. Scaling of impervious surface area and vegetation as indicators to urban land surface temperature using satellite data[J]. International Journal of Remote Sensing,2009,30(4):841-859.
[9]Song Y B. Influence of new town development on the urban heat island-The case of the Bundang area[J]. Journal of Environmental Sciences-China,2005,17(4):641-645.
[10]Santamouris M, N Papanikolaou, I Livada, et al. On the impact of urban climate on the energy consumption of buildings[J]. Solar Energy,2001,70(3):201-216.
[11]Santamouris M, K Paraponiaris, G Mihalakakou. Estimating the ecological footprint of the heat island effect over Athens, Greece[J]. Climatic Change,2007,80(3-4):265-276.
[12]Junk J, A Helbig, J Luers. Urban climate and air quality in Trier Germany [J]. International Journal of Biometeorology,2003,47(4):230-238.
[13]汝信,陆学艺,李培林.社会蓝皮书：2012年中国社会形势分析与预测[M].北京：社会科学文献出版社,2011：2-3.
[14]Oke T R. City size and the urban heat island [J]. Atmospheric Environment,1967,7(8): 769-779.
[15]Katsoulis B D, Theoharatos G A. Indications of the Urban Heat Island in Athens, Greece [J]. Journal of Climate and Applied Meteorology,1985,24.
[16]Landberg H E. The climate of towns Man's role in changing the face of the Earth [M]. University of Chicago Press,1956.
[17]Rudolf B, Marie B. An urban bias in air temperature fluctuations at the Klementinum, Prague, the Czech Republic [M]. Atmospheric Environment,1999,33:4211-4217.
[18]Giridharan B, Ganesan S, Lau S S Y. Daytime urban heat island effect in high-rise and high-density residential developments in Hong Kong [J]. Energy and Buildings,2004, 36(6):525-534.
[19]Goodridge J D. Urban bias influences on long-term California air temperature trends [J]. Atmosp Environ,1992,26B (1):1-7.
[20]Hughes W E, Balling R C. Urban influences on South African temperature trends [J]. Int J Climatol,1996,16:935-940.
[21]初子莹,任国玉.北京地区城市热岛强度变化对区域温度序列的影响[J].气象学报, 2005,63：534-540.
[22]刘学峰,于长文,任国玉.河北省城市热岛强度变化对区域地表平均气温序列的影响[J]气候与环境研究,2005,10(4)：763-770.
[23]陈正洪,王海军,任国玉.武汉市城市热岛强度非对称性变化[J].气候变化研究进展,2003,3(5)：282-286.
[24]张玲,徐宗学,阮本清.北京城市热岛效应对气温和降水量的影响[J].自然资源学报,2006,21(5)：746-755.
[25]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[J].地球物理学报,2006,49(1)：69-77.
[26]周淑贞,张超.上海城市热岛效应[J].地理学报,1982,37：372-381.
[27]Kenneth M, Hinkel, Frederick E, et al. The urban heat island in winer at Barrow, Alaska [J]. Int J Climatol,2003,23:1889-1905.
[28]Gedzelman S, Austin R, Cermak, et al. Mesoscale aspects of the Urban Heat Island around New York City [J]. Theor. Appl. Climatol,2003,75:29-42.
[29]郑敬刚,张景光,李有.郑州市热岛效应研究与人体舒适度评价[J].应用生态学报,2005,16(10)：1838-1842.
[30]张一平,何云玲,马友鑫等.昆明城市热岛效应立体分布特征[J].高原气象,2002,21(6)：604-609.
[31]Czajkowski K P, Goward S N, Stadler S, et al. Thermal Remote Sensing of Near Surface Environmental Variables:Application over the Oklahoma Mesonet [J]. The Professional Geographer,2000,52(2):345-357.
[32]侯英雨,张佳华,延昊等.利用卫星遥感资料估算区域尺度空气温度[J].气象,2010,36(4)：75-79.
[33]Christelle V, Pietro C, Tufa D, et al. Evalution of MODIS land surface temperature data to estimate air temperature in different ecosystems over Africa [J]. Remote Sensing of Environment,2010,114:449-465.
[34]Cresswell M P, Morse A P, Thomson M C, et al. Estimating surface air temperatures, from Meteosat land surface temperatures, using an empirical solar zenith angle model [J]. International Journal of Remote Sensing,1999,20(6):1125-1132.
[35]Mostovoy G V, King R L, Reddy K R, Kakani V G, et al. Statistical estimation of daily maximum and minimum air temperatures from MODIS LST data over the state of Mississippi[J]. GIScience and Remote Sensing,2006,43(1):78-110.
[36]Prince S D, Goetz S J, Dubayah R O, et al. Inference of surface and air temperature, atmospheric precipitable water and vapor pressure deficit using advanced very high-resolution radiometer satellite observations:Comparison with field observations [J]. Journal of Hydrology,1998,213(1-4):230-249.
[37]Stisen S, Sandholt I, Norgaard A, Fensholt R, et al. Estimation of diurnal air temperature using MSG SEVIRI data in West Africa [J]. Remote Sensing of Environment,2007,110(2): 262-274.
[38]Nemani R R, Running S W. Estimation of regional surface-resistance to evapotranspiration from NDVI and thermal-IR AVHRR data [J]. Journal of Applied Meteorology,1989,28(4): 276-284.
[39]Goward S N, Waring R H, Dye D G, et al. Ecological remote-sensing at OTTER-Satellite macroscale observations[J]. Ecological Applications,1994,4:322-343.
[40]Prince S D, Goward S N. Global primary production:A remote sensing approach [J]. Journal of Biogeography,1995,22(4-5):815-835.
[41]Prihodko L, Goward S N. Estimation of air temperature from remotely sensed surface observations [J]. Remote Sensing of Environment,1997,60(3):335-346.
[42]Goetz S J, Prince S D, Small J. Advances in satellite remote sensing of environmental variables for epidemiological applications. Advances in Parasitology[J],2000,47:289-307.
[43]Stisen S, Sandholt I, Norgaard A, et al. Estimation of diurnal air temperature using MSG SEVIRI data in West Africa [J]. Remote Sensing of Environment,2007,110(2):262-274.
[44]Saravanapavan T, Dye D G. Satellite estimation of environmental variables by the contextual analysis method:validation in seasonal tropical environment [G]. Global Engineering Laboratory Institute of Industrial Science University of Tukyo, Janpan,1995.
[45]Czajkowski K P, Mulhern T, Goward S N, et al. Biospheric environmental monitoring at BOREAS with AVHRR observations [J]. Journal of Geophysical Research,1997,102: 29651-29662.
[46]Rao P K. Remote sensing of urban "hear islands" from an environmental satellite [J]. Bullutin American Metenmi Soc.,1972,53:647-648.
[47]Carlson T N, Augusfin J A, Boland F E. Potential application of satellite temperatures measurements in the analysis of land use over urban areas [J]. Bull. Amer. Meteor. Soc., 1977,58:1301-1303.
[48]Bailing R C, Brazel S W. High-resolution surface-temperature patterns in a complex urban terrain [J]. Photographic Engineering Remote Sensing Review,1988,54:1289-1293.
[49]Roth M, Oke T R, Emery W J. Satellite-derived urban heat island from three coastal cities and the utilization of such data in urban climatology [J]. International Journal of Remote Sensing,1989,10(11):1699-1720.
[50]延昊,邓莲堂.利用遥感地表参数分析上海市的热岛效应及治理对策[J].热带海洋学报,2004(20)：579-585.
[51]苏万楷,张文,刘波等.成都市城市热岛分析[J].四川林业科技,2006,27(3)：57-66.
[52]周红妹,周成虎,葛伟强等.基于遥感和GIS的城市热场分布规律研究[J].地理学报,2001,56(2)：189-197.
[53]Camahan W H, Larson R C. An analysis of an urban heat sink [J]. Remote sensing of Environment,1990,33:65-71.
[54]Nichol J E. A GIS-based approach to microclimate monitoring in Singapore's high-rise housing estates [J]. Photogrammetric Engineering and Remote Sensing,1994,60(10): 1225-1232.
[55]Bekele G. Assessing Urban Heat Island in Morgantown, WV Using Landsat Thermal Infrared Imagery.2002, http//:geo.wvu/geog655/spring2002/01/project.htm.
[56]Baumann P R. An Urban Heat Island Washington, D. C.2002:http//: www.onenota.edu/faculty/baumann/goosat2/urban_heat_island/urban_heat_island.htm.
[57]覃志豪,Zhang Minghua, Arnon Kanieli等.用陆地卫星TM6数据演算地表温度的单窗算法[J].地理学报,2001,56(4)：456-466.
[58]陈云浩,李京,李晓兵.城市空间热环境[M].北京：科学出版社,2003.
[59]张穗,何报寅,杜耘.武汉市城区热岛效应的遥感研究[J].长江流域资源与环境,2003,12(5)：445-449.
[60]宫阿都,江樟焰,李京等.基于Landset TM图像的北京城市地表温度遥感反演研究[J].遥感信息,2005(3)：18-22.
[61]何全军,吴志军,张月维.利用MODIS热红外数据进行广州市夏季热场分析[J].遥感技术与应用,2005,20(5)：501-505.
[62]黄荣峰,徐涵秋.利用Landsat ETM+影像研究土地利用/覆盖与城市热环境的关系[J].遥感信息,2005,5：36-39.
[63]田振坤,黄妙芬,刘良云等.使用单窗算法研究北京城区热岛效应[J].遥感信息,2006,1：21-24.
[64]江志红,叶丽梅.近十年南京城市热岛演变的遥感研究[J].南京信息工程大学学报(自然科学版),2010,2(2)：148-154.
[65]Streutker D R. Satellite-measured growth of the urban heat island of Houston, Texas [J]. Remote sensing of Environment,2003,85:282-289.
[66]Streutker D R. A remote sensing study of the urban heat island of Houston, Texas [J]. International Journal of Remote Sensing,2002,23(13):2595-2608.
[67]范天锡,潘钟跃.北京地区城市热岛特性的卫星遥感[J].气象,1987,13(10)：29-32.
[68]张佳华,侯英雨,李贵才等.北京城市及周边热岛日变化及季节特征的卫星遥感研究与影响因子分析[J].中国科学D辑,2005,35(增刊)：187-194.
[69]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[J].测绘学报,2002,31(2)：139-144.
[70]徐涵秋.利用改进的归一化差异水体指数(MNDWI)提取水体信息的研究[J].遥感学报,2005,5：589-595.
[71]谢志清,杜银,曾燕等.长江三角洲城市带扩展对区域温度变化的影响[J].地理学报,2007,62(7)：717-727.
[72]倪敏莉,申双和,张佳华.长江三角洲城市群热环境研究[J].大气科学学报,2009,32(5)：711-715.
[73]葛伟强,周红妹,杨何群.基于MODIS数据的近8年长三角城市群热岛特征及演变分析[J].气象,2010,36(11)：77-81.
[74]饶胜,张惠远,金陶陶等.基于MODIS的珠江三角洲地区区域热岛的分布特征[J].地理研究,2010,29(1)：127-136.
[75]Zeng Yongnian, Huang Wei, Zhan F. Benjamin, et al. Study on the urban heat island effects and its relationship with surface biophysical characteristics using MODIS imageries[J]. Geo-spatial Information Science,2010,13(1):1-7.
[76]Wan Z. MODIS Land Surface Temperature Products Users'Guide[EB/OL].2007, available online:http://www.icess.ucsb.edu/modis/LstUsrGuide/MODIS_LST_products_Users_guide_C5.pdf.
[77]Strahler A. MODIS land cover product algorithm theoretical basis document[EB/OL]. 1999, available online:http://modis.gsfc.nasa.gov/data/atbd/atbd_mod12.pdf.
[78]Wan Z. MODIS land-surface temperature algorithm theoretical basis document[EB/OL]. 1999, available online:http://modis.gsfc.nasa.gov/data/atbd/atbd mod11.pdf.
[79]Wan Z, Li Z L. Radiance-based validation of the V5 MODIS land-surface temperature product[J]. International Journal of Remote Sensing,2008,29:5373-5395.
[80]Coll C, Wan Z, Galve J M. Temperature-based and radiance-based validations of the V5 MODIS land surface temperature product[J]. Journal of Geophysical Research,2009, doi: 10.1029/2009 JD012038.
[81]杨眉,王世新,周艺等DMSP/OLS夜间灯光数据应用研究综述[J].遥感技术与研究,2011,26(1)：45-51.
[82]Croft T A. Nighttime images of the earth from space[J]. Scientific American,1978,239: 86-89.
[83]He Chunyang, Shi Peijun, Li Jinggang, et al. Restoring urbanization process in China in the 1990s by using non-radiance-calibrated DMSP/OLS nighttime light imagery and statistical data[J]. Chinese Science Bulletin,2006,51(13):1614-1620.
[84]Elvidge C D, Baugh K E, Kihn E A, et al. Mapping of city lights using DMSP Operational Linescan System data[J]. Photogrammetric Engineering and Remote Sensing,1997,63: 727-734