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遥感技术与应用  2015, Vol. 30 Issue (6): 1113-1121    DOI: 10.11873/j.issn.1004-0323.2015.6.1113
模型与反演     
地表温度遥感中大气平均作用温度估算模型研究
龚绍琦1,2,张茜茹1,王少峰3,周寅1,4,张世乔1,国文哲1
(1.南京信息工程大学遥感学院,江苏 南京210044;
2.南京师范大学虚拟地理环境教育部重点实验室,江苏 南京210046;
3.中国人民解放军73608部队,江苏 南京210028;
4.中国人民解放军94857部队61分队,安徽 芜湖241007)
Study on the Estimated Model of Effective Mean Atmospheric Temperature for Land Surface Temperature Remote Sensing
Gong Shaoqi1,2,Zhang Xiru1,Wang Shaofeng3,Zhou Yin1,4,Zhang Shiqiao1,Guo Wenzhe1
(1.School of Remote Sensing,Nanjing University of Information Science
and Technology,Nanjing 210044,China;
2 Key Lab of Virtual Geographic Environment,Nanjing Normal University,
Ministry of Education 210046,China;
3.NO.73608 of the Chinese Peoples Liberation Army,Nanjing 210028,China;
4.Unit 61,No.94857 of Chinese People's Liberation Army,Wuhu 241007,China)
 全文: PDF(1761 KB)  
摘要:

大气平均作用温度Ta是地表温度遥感单窗算法中一个关键的参数,利用2008~2011年全国123个探空站点资料,针对大气水汽量的垂直分布特征,分析了利用近地层气温T0估算大气有效平均温度的可行性;进一步分析了T0和Ta之间的相关性,建立了适合我国地区大气平均温度估算的最佳模型Ta=44.97098+0.80512 T0,模型的决定系数R2为0.859,均方根误差为4.198 K。通过对44幅HJ\|1B/IRS热红外图像地温反演的敏感性分析,结果表明:模型估算的Ta用于地表温度反演时的误差为1.734 K;当大气透射率τ很小时,模型估算的Ta误差对地温反演很敏感,较小的估算误差会给地温反演带来很大的误差;随着大气透射率τ的增加,Ta的估算误差对地温反演的敏感性逐渐降低。

关键词: 地表温度遥感大气平均作用温度单窗算法模型    
Abstract:

Effective mean atmospheric temperature,Ta is a key parameter for the mono-window algorithm in the land surface temperature,LST remote sensing.Using radiosonde data of 123 stations within Chinese continent from 2008 to 2011,the vertical distribution characteristics of water vapor in atmospheric profile is discovered and the feasibility of Ta is esimated by air temperature near land surface T0is displayed,then their relationship is discussed,the results show that the best estimated model of Ta is deduced for land surface temperature remote sensing in China,and that is Ta=44.97098+0.80512T0,its determination coefficient is 0.859 and the root-mean-square error,RMSE is 4.198 K.The sensitivity analysis of Ta model for the land surface temperature remote sensing is carried out by 44 HJ-1B/IRS thermal infrared images,and the results show that the RMSE of the retrieval LST is 1.734 K using the estimated Ta,and the estimated error of Ta is very sensitive for the retrieval LST when the atmospheric transmittance,τ is very low,and a small Ta estimated error will result in a big LST retrieval error,however,as the transmittance increases,the sensitivity of the retrieval error will decrease with the Ta estimated error.

Key words: Land surface temperature(LST)    Remote sensing    Effective mean atmospheric temperature    Mono-window algorithm    Model
收稿日期: 2014-04-16 出版日期: 2016-01-25
:  P 237  
基金资助:

国家自然科学基金项目(40801145),江苏高校优势学科建设工程资助项目,南京师范大学虚拟地理环境教育部重点实验室开放基金资助项目,2012年度国家级大学生实践创新训练计划项目(201210300008),2013年度江苏省大学生实践创新训练计划项目(201310300063Y)。

作者简介: 龚绍琦(1979-),男,江西上饶人,副教授,硕士生导师,主要从事资源与环境遥感研究。Email:shaoqigong@163.com。
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引用本文:

龚绍琦,张茜茹,王少峰,周寅,张世乔,国文哲. 地表温度遥感中大气平均作用温度估算模型研究[J]. 遥感技术与应用, 2015, 30(6): 1113-1121.

Gong Shaoqi,Zhang Xiru,Wang Shaofeng,Zhou Yin,Zhang Shiqiao,Guo Wenzhe. Study on the Estimated Model of Effective Mean Atmospheric Temperature for Land Surface Temperature Remote Sensing. Remote Sensing Technology and Application, 2015, 30(6): 1113-1121.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2015.6.1113        http://www.rsta.ac.cn/CN/Y2015/V30/I6/1113

[1]Li Hua,Zeng Yongnian,Yun Peidong,et al.Study on Retrieval Urban Land Surface Temperature with Multi-source Remote Sensing Data[J].Journal of Remote Sensing,2007,11(6):891-898.[历华,曾永年,贠培东,等.利用多源遥感数据反演城市地表温度[J].遥感学报,2007,11(6):891-898.]

[2]Baldridge A M,Hook S J,Grove C I,et al.The ASTER Spectral Library Version 2.0[J].Remote Sensing of Environment,2009,113:711-715.

[3]Gillespie A,Rokugawa S,Matsunaga T,et al.A Temperature and Emissivity Separation Algorithm for Advanced Spaceborne Thermal Emission and Reflection Radiometer(ASTER)Images[J].IEEE Transactions on Geoscience and Remote Sensing,1998,36(4):1113-1126.

[4]Barducci A,Pippi I.Temperature and Emissivity Retrieval from Remotely Sensed Images Using the ‘Grey Body Emissivity’ Method[J].IEEE Transactions on Geoscience and Remote Sensing,1996,34(3):681-695.

[5]Kealy P S,Hook S J.Separating Temperature and Emissivity in Thermal Infrared Multispectral Scanner Data:Implications for Recovering Land Surface Temperatures[J].IEEE Transactions on Geoscience and Remote Sensing,1993,31(6):1155-1164.

[6]Wan Z M,Li Z L.A Physics-based Algorithm for Retrieving Land-Surface Emissivity and Temperature from EOS/MODIS Data[J].IEEE Transactions on Geoscience and Remote Sensing,1997,35(4):980-996.

[7]Watson K.Spectral Ratio Method for Measuring Emissivity[J].Remote Sensing Environment,1992,42:113-116.

[8]Valor E,Caselles V.Mapping Land Surface Emissivity from NDVI:Application to European,African and South American Areas[J].Remote Sensing Environment,1996,57:167-184.

[9]Qin Zhihao,Li Wenjuan,Xu Bin,et al.The Estimation of Land Surface Emissivity for Landsat TM6[J].Remote Sensing for Land & Resources,2004,(3):28-35.[覃志豪,李文娟,徐斌,等.陆地卫星TM6波段范围内地表比辐射率的估计[J].国土资源遥感,2004,(3):28-35.]

[10]Qin Zhihao,Li Wenjuan,Zhang Minghua,et al.Estimating of The Essential Atmospheric Parameters of Mono-window Algorithm for Land Surface Temperature Retrieval from Landsat TM6[J].Remote Sensing for Land & Resources,2003,(2):37-43.[覃志豪,李文娟,张明华,等.单窗算法的大气参数估计方法[J].国土资源遥感,2003,(2):37-43.]

[11]Ding Lidong,Qin Zhihao,Mao Kebiao.A Research of Split Window Algorithm based on MODIS Image Data and Parameter Determination[J].Remote Sensing Technology and Application,2005,20(2):284-289.[丁莉东,覃志豪,毛克彪.基于MODIS影像数据的劈窗算法研究及其参数确定[J].遥感技术与应用,2005,20(2):284-289.]

[12]Qin Z H,Karnieli A,Berliner P.A Mono-window Algorithm for Retrieving Land Surface Temperature from Landsat TM Data and Its Application to the Israel-Egypt Border Region[J].International Journal of Remote Sensing,2001,22(18):3719-3746.

[13]Qin Zhihao,Zhang Minghua,Arnon Karnieli,et al.Mono-window Algorithm for Retrieving Land Surface Temperature from Landsat TM6 Data[J].Acta Geographica Sinica,2001,56(4):456-466.[覃志豪,张明华,Arnon Karnieli,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.]

[14]Huang Miaofen,Xing Xufeng,Wang Peijuan,et al.Comparison between Three Different Methods of Retrieving Surface Temperature from Landsat TM Thermal Infrared Band[J].Arid Land Geography,2006,29(1):132-137.[黄妙芬,邢旭峰,王培娟,等.利用 LANDSAT/TM 热红外通道反演地表温度的三种方法比较[J].干旱区地理,2006,29(1):132-137.]

[15]Du Jia,Zhang Bai,Song Kaishan,et al.A Comparative Study on Estimated Surface Temperature based on Landsat5 TM in the Honghe Wetland[J].Remote Sensing Technology and Application,2009,24(3):312-320.[杜嘉,张柏,宋开山,等.基于Landsat-5 TM的洪河湿地地表温度估算方法对比研究[J].遥感技术与应用,2009,24(3):312-320.]

[16]Jiménez-Munoz J C,Sobrino J A.A Generalized Single-channel Method for Retrieving Land Surface Temperature from Remote Sensing Data[J].Journal of Geophysical Research,2003,108(D22):4688.doi:10.1029/2003JD003480.

[17]Hu Juyang,Tang Shihao,Dong Lixin.Land Surface Temperature Retrieval from FY3A/MERSI[J].Remote Sensing Technology and Application,2014,29(4):531-538.[胡菊旸,唐世浩,董立新.FY3A/MERSI地表温度反演[J].遥感技术与应用,2014,29(4):531-538.]

[18]Wan Z M,Dozier J.A Generalized Split-window Algorithm for Retrieving Land-surface Temperature from Space[J].IEEE Transactions on Geoscience and Remote Sensing,1996,34(4):892-905.

[19]Qin Z H,DallOlmo J,Karnieli A,et al.Derivation of Split Window Algorithm and Its Sensitivity Analysis for Retrieving Land Surface Temperature from NOAA-advanced very High Resolution Radiometer Data[J].Journal of Geophysical Research,2001,106(D19):22655-22670.

[20]Schmugge T,French A.Temperature and Emissivity Separation from Multispectral Thermal Infrared Observations[J].Remote Sensing of Environment,2002,79:189-198.

[21]Li Xiuxia,Nan Ying,Liu Zhifeng,et al.Comparison of Two Algorithms for Retrieving Land Surface Temperature from Landsat TM Thermal Infrared Band in Yanji City[J].Journal of Yanbian University(Natural Science Edition),2010,36(2):177-182.[ 李秀霞,南颖,刘志锋,等.基于Landsat TM数据的延吉市地表温度的2种反演算法比较研究[J].延边大学学报(自然科学版),2010,36(2):177-182.]

[22]Zhao Shaohua,Qin Qiming,Zhang Feng,et al.Research on Using a Mono-Window Algorithm for Land Surface Temperature Retrieval from Chinese Satellite for Environment and Natural Disaster Monitoring (HJ-1B) Data[J].Spectroscopy and Spectral Analysis,2011,31(6):1552-1556.[ 赵少华,秦其明,张 峰,等.基于环境减灾小卫星(HJ-1B)的地表温度单窗反演研究[J].光谱学与光谱分析,2011,31(6):1552-1556.]〖JP〗

[23]Wang Xiuxin,Qin Limei,Nong Jinghui,et al.Land Surface Temperature Retrieval with Mono-window Algorithm in Karst City[J].Journal of Guangxi Normal University(Natural Science Edition),2010,28(3):10-14.[王修信,秦丽梅,农京辉,等.利用单窗算法反演喀斯特城市地表温度[J].广西师范大学学报(自然科学版),2010,28(3):10-14.][24]Liu Xin,Gan Shu.Land Surface Temperature Inversion of Kunming Area based on Mono-window Algorithm and Configuration Analysis of Thermal Environment[J].Journal of Kunming University of Science and Technology(Natural Science Edition),2011,36(5):8-13.[刘鑫,甘淑.基于单窗算法的昆明地表温度反演及热格局分析[J].昆明理工大学学报(自然科学版),2011,36(5):8-13.]

[25]Sobrino J A,Coll C,Caselles V.Atmospheric Correction for Land Surface Temperature Using NOAA-11 AVHRR Channels 4 and 5[J].Remote Sensing of Environment,1991,38:19-34.

[26]Zhang Xuewen.The Vertical Distribution Law of Vapor Pressure in Xinjiang,China[J].Xinjiang Meteorology,2002,25(4):1-3.[张学文.新疆水汽压力的铅直分布规律[J].新疆气象,2002,25(4):1-3.]

[27]Duan Sibo,Yan Guangjian,Qian Yonggang,et al.Two Single-channel Retrieval Algorithms of Land Surface Temperature Using HJ-1B Simulation Data[J].Progress in Natural Science,2008,18(9):1001-1008.[段四波,阎广建,钱永刚,等.利用HJ-1B模拟数据反演地表温度的两种单通道算法[J].自然科学进展,2008,18(9):1001-1008.]

[28]Sun Jun,Zhang Hui,Wang Qiao,et al.Three Methods for Inverting Land Surface Temperature of the Taihu Lake Basin Using HJ-1 Satellite Thermal Infrared Channel[J].Journal of Ecology and Rural Environment,2011,27(2):100-104.[孙俊,张慧,王桥,等.利用环境一号卫星热红外通道反演太湖流域地表温度的3种方法比较[J].生态与农村环境学报,2011,27(2):100-104.] 

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