| Technology and Methodology |
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ESTIMATING OF THE ESSENTIAL ATMOSPHERIC PARAMETERS OF MONO-WINDOW ALGORITHM FOR LAND SURFACE TEMPERATURE RETRIEVAL FROM LANDSAT TM6 |
| QIN Zhi-hao1, LI Wen-juan2, ZHANG Ming-hua3, Arnon Karnieli4, Pedro Berliner4 |
1. International Institute for the Earth System Science, Nanjing University, Nanjing 210093, China;
2. The Spatial Modeling Centre, Umea University, Kiruna 98028, Sweden;
3. Dept. of Land Air and Water Resources, University of California, Davis CA 96515, USA;
4. J. Blaustein Inst. for Desert Research, Ben Gurion University of the Negev, Sede Boker Campus 84990, Israel |
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Abstract The thermal band data of Landsat TM (TM6) is highly suitable for analyzing the spatial patterns of the Earth's heat flux variation and surface temperature. Based on the thermal radiance transfer equation and several approximations to its terms, the authors developed a mono-window algorithm for retrieving land surface temperature (LST) from TM6 data. Unlike the conventional atmospheric correction which requires the in situ atmospheric profile data to estimate the atmospheric thermal radiance and absorption, the proposed mono-window algorithm directly involves the impacts of both atmosphere and the emitted ground into its computation, hence avoids the consequence of inaccurate atmospheric radiance estimate. The proposed algorithm requires two essential atmospheric parameters for LSTretrieval; transmittance and atmospheric average temperature. This paper discusses the estimation of the essential atmospheric parameters. Atmospheric effective mean temperature can be estimated using the ground meteorological observation data. Equations also have been constructed for estimation of atmospheric transmittance using the atmospheric water vapor content in the profile. Moderate errors in estimating the two essential atmospheric parameters may cause a bias of about 1.2℃ to the LSTretrieval, which is within the acceptable accuracy of 1.5℃ for most applications.
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| Keywords
Province level
Digital land
Resource
Information system
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Issue Date: 02 August 2011
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| [1] 覃志豪, Zhang M, Karnieli A, et al.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.[2] Qin Z, 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.[3] Schneider K, Mauser W.Processing and accuracy of Landsat Thematic Mapper data for lake surface temperature measurement［J］. International Journal of Remote Sensing,1996,17: 2027-2041.[4] Sugita M, Brutsaert W.Comparison of land surface temperatures derived from satellite observations with ground truth during FIFE［J］. International Journal of Remote Sensing,1993,14:1659-1676.[5] Sobrino J A, Coll C, Caselles V.A tmospheric correction for land surface temperature using NOAA-11 AVHRR channels 4 and 5［J］. Remote Sensing of Environment, 1991,38: 19-34.[6] 覃志豪, Zhang Minghua, Arnon Karnieli.用NOAA-AVHRR热通道数据演算地表温度的劈窗算法［J］.国土资源遥感,2001,(2):33-42.[7] Qin Z, Dall'Olmo G, 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.[8] Franca G B, Cracknell A P. Retrieval of land and sea surface temperature using NOAA-11 AVHRR data in northeastern Brazil［J］.International Journal of Remote Sensing, 1994,15:1695-1712. |
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2003,
Vol. 15
