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Proceedings Paper

Land surface temperature retrieval from Landsat 8 TIRS: comparison between split window algorithm and SEBAL method
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Paper Abstract

Land surface temperature (LST) is a key parameter in the physics of the earth surface through the process of energy and water exchange with the atmosphere, which plays an important role in a wide variety of scientific studies, such as ecology, hydrology, and global change studies. Thermal infrared (TIR) remote sensing provides a unique method for obtaining LST information at the regional and global scales since most of the energy detected by the sensor in this spectral region is directly emitted by the land surface. Landsat 8 Thermal Infrared Sensor (TIRS), because of two adjacent thermal bands, band 10 between 10.30-11.30 μm and band 11 between 11.30-12.30 μm, and availability of its images is a good source for retrieving LST. In this study, we compared two different methods for LST inversions from TIRS including the Split Window method and the SEBAL method for Tehran , Iran.. Results show that the LST inverted from the Split Window method has the accuracy with RMSE lower than 1.17 ˚ C, while the SEBAL method has the accuracy with 3.27 ˚ C, so the Split Window algorithm is appropriate method for this study area.

Paper Details

Date Published: 19 June 2015
PDF: 12 pages
Proc. SPIE 9535, Third International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2015), 953503 (19 June 2015); doi: 10.1117/12.2192491
Show Author Affiliations
Khalil Valizadeh Kamran, Univ. of Tabriz (Iran, Islamic Republic of)
Mojtaba Pirnazar, Univ. of Tabriz (Iran, Islamic Republic of)
Vida Farhadi Bansouleh, Univ. of Tabriz (Iran, Islamic Republic of)


Published in SPIE Proceedings Vol. 9535:
Third International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2015)
Diofantos G. Hadjimitsis; Kyriacos Themistocleous; Silas Michaelides; Giorgos Papadavid, Editor(s)

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