浏览全部资源
扫码关注微信
Received：10 October 2017，
Accepted：30 January 2018，
Published：2018-09
移动端阅览
地表温度是区域和全球尺度地表物理过程的一个重要参数，目前已有的地表温度产品空间分辨率较低，缺乏高空间分辨率的地表温度产品。Landsat系列卫星提供了大量免费的高空间分辨率遥感数据，然而对应的高空间分辨率地表温度产品还未见到，为了获取长时间序列的高空间分辨率地表温度数据，针对Landsat 8 TIRS数据提出了一个物理单通道地表温度反演算法。该算法首先利用ASTER全球地表发射率产品(ASTER GED)结合Landsat 8地表反射率产品计算Landsat 8影像的地表发射率，然后利用快速辐射传输模型RTTOV结合MERRA大气廓线数据对热红外影像进行大气校正，最后利用物理单通道地表温度反演算法得到地表温度。利用黑河流域HiWATER试验2013年—2015年15个站点的实测地表温度数据对本文方法和普适性单通道算法进行了验证，同时对验证站点的空间异质性进行了分析。结果表明，本文方法和普适性单通道算法估算的地表温度整体精度均较高，能够获取高精度、高空间分辨率的地表温度数据，可以服务于城市热岛效应、地表蒸散发估算等相关研究。
Land Surface Temperature (LST) is an important parameter in land surface physical processes in regional and global scales. LST plays an crucial role in the interaction and energy exchanges between the atmosphere and land. LST has been widely used in weather forecasting
ocean circulation
drought monitoring
and energy balance. At present
the spatial resolution of LST products is relatively low
which can no longer meet the demand for monitoring urban heat island and estimating regional evapotranspiration. Landsat satellites offer numerous high-spatial-resolution data of land surface. However
an operational Landsat8 LST product is unavailable
thereby limiting the use of the data. In this study
we developed a physical single-channel algorithm to retrieve LST from Landsat 8 TIRS database
which can be used for retrieving Landsat LST with long time series. A physical single channel algorithm was developed to retrieve the LST from Landsat 8 TIRS data. First
ASTER Global Emissivity Database and vegetation cover method were used to calculate the land surface emissivity. Then
MERRA reanalysis data and fast radiative transfer model RTTOV 11.3 were utilized for atmospheric correction of Landsat8 thermal infrared images. The validation results were divided into two parts: (1) validation using the simulated data and (2) validation based on the ground measured data. First
simulation data calculated by TIGR atmospheric profile and MODTRAN were used to validate the accuracy of the algorithm
and the in situ LSTs between 2013 and 2015 acquired from the HiWATER experiment were used to evaluate Landsat LST. The transmittance and atmospheric upward radiance simulated by RTTOV are close to those of MODTRAN. The mean bias of transmittance between RTTOV and MODTRAN is approximately 0.01
and that for atmospheric upward radiance is approximately 0.04 W/(m
2
·sr·μm). Compared with the NDVI threshold method
the proposed method can both reflect the dynamic change trend of land surface emissivity over vegetations and reflect the variation among different soil types. The validation results show that the overall deviation for both PSC algorithm and JMS method is within ±0.2 K. Moreover
the RMSE of the PSC algorithm is around 2.2 K
whereas that for JMS algorithm is 2.4 K. LST with high spatial resolution and precision could be obtained using the proposed method for monitoring urban heat island and estimating regional evapotranspiration.
Aires F, Chédin A, Scott N A and Rossow W B. 2010. A regularized neural net approach for retrieval of atmospheric and surface temperatures with the IASI instrument. Journal of Applied Meteorology, 41(2): 144–159
Anderson M C, Allen R G, Morse A and Kustas W P. 2012. Use of Landsat thermal imagery in monitoring evapotranspiration and managing water resources. Remote Sensing of Environment, 122: 50–65
Baldridge A M, Hook S J, Grove C I and Rivera G. 2009. The ASTER spectral library version 2.0. Remote Sensing of Environment, 113(4): 711–715
Barsi J A, Barker J L and Schott J R. 2003. An atmospheric correction parameter calculator for a single thermal band earth-sensing instrument // Proceedings of the 2003 IEEE International Geoscience and Remote Sensing Symposium. Toulouse, France: IEEE: 3014–3016
Barsi J A, Schott J R, Hook S J, Raqueno N G, Markham B L and Radocinski R G. 2014. Landsat-8 Thermal Infrared Sensor (TIRS) vicarious radiometric calibration. Remote Sensing, 6(11): 11607–11626
陈军, 陈晋, 廖安平, 曹鑫, 陈利军, 陈学泓, 彭舒, 韩刚, 张宏伟, 何超英, 武昊, 陆苗. 2014. 全球30 m地表覆盖遥感制图的总体技术. 测绘学报, 43(6): 551–557
Chen J, Chen J, Liao A P, Cao X, Chen L J, Chen X H, Peng S, Han G, Zhang H W, He C Y, Wu H and Lu M. 2014. Concepts and key techniques for 30 m global land cover mapping. Acta Geodaetica et Cartographica Sinica, 43(6): 551–557 (
Cheng J, Liang S L, Wang J D and Li X W. 2010. A stepwise refining algorithm of temperature and emissivity separation for hyperspectral thermal infrared data. IEEE Transactions on Geoscience and Remote Sensing, 48(3): 1588–1597
Cheng J, Liang S L, Yao Y J, Ren B Y, Shi L P and Liu H. 2014. A comparative study of three land surface broadband emissivity datasets from satellite data. Remote Sensing, 6(1): 111–134
Coll C, Galve J M, Sanchez J M and Caselles V. 2010. Validation of landsat-7/ETM+ thermal-band calibration and atmospheric correction with ground-based measurements. IEEE Transactions on Geoscience and Remote Sensing, 48(1): 547–555
Coll C, Valor E, Galve J M, Mira M, Bisquert M, García-Santos V, Caselles E and Caselles V. 2012. Long-term accuracy assessment of land surface temperatures derived from the advanced along-track scanning radiometer. Remote Sensing of Environment, 116: 211–225
Cook M, Schott J, Mandel J and Raqueno N. 2014. Development of an operational calibration methodology for the Landsat thermal data archive and initial testing of the atmospheric compensation component of a land surface temperature (LST) product from the archive. Remote Sensing, 6(11): 11244–11266
Ellicott E, Vermote E, Petitcolin F and Hook S J. 2009. Validation of a new parametric model for atmospheric correction of thermal infrared data. IEEE Transactions on Geoscience and Remote Sensing, 47(1): 295–311
Gao B C and Kaufman Y J. 2015. MODIS Atmosphere L2 Water Vapor Product. NASA MODIS Adaptive Processing System, Goddard Space Flight Center, USA [DOI: 10.5067/MODIS/MOD05_L2.006]
Gillespie A, Rokugawa S, Matsunaga T, Cothern J S, Hook S and Kahle A B. 1998. A temperature and emissivity separation algorithm for advanced spaceborne thermal emission and reflection radiometer (ASTER) images. IEEE Transactions on Geoscience and Remote Sensing, 36(4): 1113–1126
Global Modeling and Assimilation Office (GMAO). 2015. M2I6NPANA: MERRA-2 inst6_3d_ana_Np: 3d, 6-Hourly, Instantaneous, Pressure-Level, Analysis, Analyzed Meteorological Fields V5.12.4. Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC) [DOI: 10.5067/A7S6XP56VZWS]
Guillevic P C, Biard J C, Hulley G C, Privette J L, Hook S J, Olioso A, Göttsche F M, Radocinski R, Román M O, Yu Y Y and Csiszar I. 2014. Validation of land surface temperature products derived from the Visible Infrared Imaging Radiometer Suite (VIIRS) using ground-based and heritage satellite measurements. Remote Sensing of Environment, 154: 19–37
Hulley G, Veraverbeke S and Hook S. 2014. Thermal-based techniques for land cover change detection using a new dynamic MODIS multispectral emissivity product (MOD21). Remote Sensing of Environment, 140: 755–765
Hulley G C, Hook S J, Abbott E, Malakar N, Islam T and Abrams M. 2015. The ASTER global emissivity dataset (ASTER GED): mapping earth’s emissivity at 100 meter spatial scale. Geophysical Research Letters, 42(19): 7966–7976
Jiménez-Muñoz J C and Sobrino J A. 2003. A generalized single-channel method for retrieving land surface temperature from remote sensing data. Journal of Geophysical Research, 108(D22): 4688
Jiménez-Muñoz J C, Sobrino J A, Gillespie A, Sabol D and Gustafson W T. 2006. Improved land surface emissivities over agricultural areas using ASTER NDVI. Remote Sensing of Environment, 103(4): 474–487
Jiménez-Muñoz J C, Cristobal J, Sobrino J A, Sòria G, Ninyerola M and Pons X. 2009. Revision of the single-channel algorithm for land surface temperature retrieval from Landsat Thermal-Infrared data. IEEE Transactions on Geoscience and Remote Sensing, 47(1): 339–349
Jiménez-Muñoz J C, Sobrino J A, Skoković D, Mattar C and Cristóbal J. 2014. Land surface temperature retrieval methods from landsat-8 thermal infrared sensor data. IEEE Geoscience and Remote Sensing Letters, 11(10): 1840–1843
Kalma J D, McVicar T R and McCabe M F. 2008. Estimating land surface evaporation: a review of methods using remotely sensed surface temperature data. Surveys in Geophysics, 29(4/5): 421–469
历华, 杜永明, 柳钦火, 徐大琦, 曹彪, 蒋金雄, 王合顺. 2014. 天宫一号数据地表温度反演及其在城市热岛效应中的应用. 遥感学报, 18(z1): 133–143
Li H, Du Y M, Liu Q H, Xu D Q, Cao B, Jiang J Q and Wang H S. 2014. Land surface temperature retrieval from Tiangong-1 data and its applications in urban heat island effect. Journal of Remote Sensing, 18(z1): 133–143 (
Li H, Liu Q H, Jiang J X, Wang H S and Sun L. 2011. Validation of the land surface temperature derived from HJ-1B/IRS data with ground measurements // 2011 IEEE International Geoscience and Remote Sensing Symposium. Vancouver, BC: IEEE: 293–296 [DOI: 10.1109/IGARSS.2011.6048950]
Li H, Liu Q H, Zhong B, Du Y M, Wang H S and Wang Q. 2010. A Single-channel algorithm for land surface temperature retrieval from HJ-1B/IRS data based on a parametric model // 2010 IEEE International Geoscience and Remote Sensing Symposium (IGARSS). Honolulu, HI: IEEE: 2448–2451 [DOI: 10.1109/IGARSS.2010.5649801]
Li H, Sun D L, Yu Y Y, Wang H Y, Liu Y L, Liu Q H, Du Y M, Wang H S and Cao B. 2014. Evaluation of the VIIRS and MODIS LST products in an arid area of Northwest China. Remote Sensing of Environment, 142: 111–121
Li X, Cheng G D, Liu S M, Xiao Q, Ma M G, Jin R, Che T, Liu Q H, Wang W Z, Qi Y, Wen J G, Li H Y, Zhu G F, Guo J W, Ran Y H, Wang S G, Zhu Z L, Zhou J, Hu X L and Xu Z W. 2013. Heihe watershed allied telemetry experimental research (HiWATER): scientific objectives and experimental design. Bulletin of the American Meteorological Society, 94(8): 1145–1160
李召良, 段四波, 唐伯惠, 吴骅, 任华忠, 阎广建, 唐荣林, 冷佩. 2016. 热红外地表温度遥感反演方法研究进展. 遥感学报, 20(5): 899–920
Li Z L, Duan S B, Tang B H, Wu H, Ren H Z, Yan G J, Tang R L and Leng P. 2016. Review of methods for land surface temperature derived from thermal infrared remotely sensed data. Journal of Remote Sensing, 20(5): 899–920 (
刘超, 历华, 杜永明, 曹彪, 柳钦火, 孟翔晨, 胡友健. 2017. Himawari 8 AHI数据地表温度反演的实用劈窗算法. 遥感学报, 21(5): 702–714
Liu C, Li H, Du Y M, Cao B, Liu Q H, Meng X C and Hu Y J. 2017. Practical split-window algorithm for retrieving land surface temperature from Himawari 8 AHI data. Journal of Remote Sensing, 21(5): 702–714 (
Mannstein H. 1987. Surface energy budget, surface temperature and thermal inertia // Remote Sensing Applications in Meteorology and Climatology. Dordrecht: Springer: 391–410 [DOI: 10.1007/978-94-009-3881-6_21]
Matricardi M, Chevallier F, Kelly G and Thépaut J N. 2004. An improved general fast radiative transfer model for the assimilation of radiance observations. Quarterly Journal of the Royal Meteorological Society, 130(596): 153–173
孟翔晨, 历华, 杜永明, 曹彪, 柳钦火, 孙林, 朱金山. 2016. 基于ASTER GED产品的地表发射率估算. 遥感学报, 20(3): 382–396
Meng X C, Li H, Du Y M, Cao B, Liu Q H, Sun L and Zhu J S. 2016. Estimating land surface emissivity from ASTER GED products. Journal of Remote Sensing, 20(3): 382–396 (
Meng X C, Li H, Du Y M, Liu Q H, Zhu J S and Sun L. 2016. Retrieving land surface temperature from Landsat 8 TIRS data using RTTOV and ASTER GED // 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS). Beijing: IEEE: 4302–4305 [DOI: 10.1109/IGARSS.2016.7730121]
Palade B and Serrano M. 2014. Long-term high-frequency validation of MODIS LST products in a Mediterranean mountain environment. International Journal of Remote Sensing, 35(3): 818–829
Qin Z H, Karnieli A and Berliner P. 2001. A mono-window algorithm for retrieving land surface temperature from Landsat TM data and its application to the Israel-Egypt border region. International Journal of Remote Sensing, 22(18): 3719–3746
Snyder W C, Wan Z, Zhang Y and Feng Y Z. 1998. Classification-based emissivity for land surface temperature measurement from space. International Journal of Remote Sensing, 19(14): 2753–2774
Sobrino J A, Jiménez-Muñoz J C, Sòria G, Romaguera M, Guanter L, Moreno J, Plaza A and Martinez P. 2008. Land surface emissivity retrieval from different VNIR and TIR sensors. IEEE Transactions on Geoscience and Remote Sensing, 46(2): 316–327
Sobrino J A, Oltra-Carrió R, Sòria G, Bianchi R and Paganini M. 2012. Impact of spatial resolution and satellite overpass time on evaluation of the surface urban heat island effects. Remote Sensing of Environment, 117: 50–56
Sobrino J A and Raissouni N. 2000. Toward remote sensing methods for land cover dynamic monitoring: application to Morocco. International Journal of Remote Sensing, 21(2): 353–366
Sobrino J A, Skoković D and Jiménez-Muñoz J C. 2015. Spatial analysis of the homogeneity of the land surface temperature in three Spanish test sites. International Journal of Remote Sensing, 36(19/20): 4793–4807
Sun D L and Pinker R T. 2003. Estimation of land surface temperature from a Geostationary Operational Environmental Satellite (GOES-8). Journal of Geophysical Research: Atmospheres, 108(D11): 4326
Tang B H, Bi Y Y, Li Z L and Xia J. 2008. Generalized split-window algorithm for estimate of land surface temperature from Chinese geostationary Fengyun meteorological satellite (FY–2C) data. Sensors, 8(2): 933–951
Tang B H, Shao K, Li Z L, Wu H and Tang R L. 2015. An improved NDVI-based threshold method for estimating land surface emissivity using MODIS satellite data. International Journal of Remote Sensing, 36(19/20): 4864–4878
Tardy B, Rivalland V, Huc M, Hagolle O, Marcq S and Boulet G. 2016. A software tool for atmospheric correction and surface temperature estimation of Landsat infrared thermal data. Remote Sensing, 8(9): 696
Valor E and Caselles V. 1996. Mapping land surface emissivity from NDVI: Application to European, African, and South American areas. Remote Sensing of Environment, 57(3): 167–184
Vermote E, Justice C, Claverie M and Franch B. 2016. Preliminary analysis of the performance of the Landsat 8/OLI land surface reflectance product. Remote Sensing of Environment, 185: 46–56
Voogt J A and Oke T R. 2003. Thermal remote sensing of urban climates. Remote Sensing of Environment, 86(3): 370–384
Wan Z M. 2008. New refinements and validation of the MODIS land-surface temperature/emissivity products. Remote Sensing of Environment, 112(1): 59–74
Wan Z M and Dozier J. 1996. A generalized split-window algorithm for retrieving land-surface temperature from space. IEEE Transactions on Geoscience and Remote Sensing, 34(4): 892–905
Wang F, Qin Z H, Song C Y, Tu L L, Karnieli A and Zhao S H. 2015. An improved mono-window algorithm for land surface temperature retrieval from Landsat 8 thermal infrared sensor data. Remote Sensing, 7(4): 4268–4289
Weng Q H, Fu P and Gao F. 2014. Generating daily land surface temperature at Landsat resolution by fusing Landsat and MODIS data. Remote Sensing of Environment, 145: 55–67
Windahl E and de Beurs K. 2016. An intercomparison of Landsat land surface temperature retrieval methods under variable atmospheric conditions using in situ skin temperature. International Journal of Applied Earth Observation and Geoinformation, 51: 11–27
徐涵秋. 2016. Landsat 8热红外数据定标参数的变化及其对地表温度反演的影响. 遥感学报, 20(2): 229–235
Xu H Q. 2016. Change of Landsat 8 TIRS calibration parameters and its effect on land surface temperature retrieval. Journal of Remote Sensing, 20(2): 229–235 (
Xu Z W, Liu S M, Li X, Shi S J, Wang J M, Zhu Z L, Xu T R, Wang W Z and Ma M G. 2013. Intercomparison of surface energy flux measurement systems used during the HiWATER-MUSOEXE. Journal of Geophysical Research: Atmospheres, 118(23): 13140–13157
Yu X L, Guo X L and Wu Z C. 2014a. Land surface temperature retrieval from Landsat 8 TIRS—comparison between radiative transfer equation-based method, split window algorithm and single channel method. Remote Sensing, 6(10): 9829–9852
Yu W P, Ma M G, Wang X F, Geng L Y, Tan J L and Shi J N. 2014b. Evaluation of MODIS LST products using longwave radiation ground measurements in the northern arid region of China. Remote Sensing, 6(11): 11494–11517
Yu Y Y, Privette J L and Pinheiro A C. 2008. Evaluation of split-window land surface temperature algorithms for generating climate data records. IEEE Transactions on Geoscience and Remote Sensing, 46(1): 179–192
Yu Y Y, Tarpley D, Privette J L, Goldberg M D, Rama Varma Raja M K, Vinnikov K Y and Xu H. 2009. Developing algorithm for operational GOES-R land surface temperature product. IEEE Transactions on Geoscience and Remote Sensing, 47(3): 936–951
Zhou J, Li J, Zhang L X, Hu D Y and Zhan W F. 2012. Intercomparison of methods for estimating land surface temperature from a landsat-5 TM image in an arid region with low water vapour in the atmosphere. International Journal of Remote Sensing, 33(8): 2582–2602
Zhou J, Zhan W F, Hu D Y and Zhao X. 2010. Improvement of mono-window algorithm for retrieving land surface temperature from HJ-1B satellite data. Chinese Geographical Science, 20(2): 123–131
Zhu Z, Wang S X and Woodcock C E. 2015. Improvement and expansion of the Fmask algorithm: cloud, cloud shadow, and snow detection for Landsats 4-7, 8, and Sentinel 2 images. Remote Sensing of Environment, 159: 269–277
相关文章
相关作者
相关机构
京公网安备11010802024621