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Towards an Operational, Split Window-Derived Surface Temperature Product for the Thermal Infrared Sensors Onboard Landsat 8 and 9
Open AccessFeature PaperArticle

Evaluation of Land Surface Temperature Retrieval from Landsat 8/TIRS Images before and after Stray Light Correction Using the SURFRAD Dataset

by Jinxin Guo 1,2, Huazhong Ren 1,2,*, Yitong Zheng 1,2, Shangzong Lu 1,2 and Jiaji Dong 1,2
1
Institute of Remote Sensing and Geographical Information System, School of Earth and Space Sciences, Peking University, Beijing 100871, China
2
Beijing Key Lab of Spatial Information Integration and Its Application, Peking University, Beijing 100871, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(6), 1023; https://doi.org/10.3390/rs12061023
Received: 10 February 2020 / Revised: 17 March 2020 / Accepted: 20 March 2020 / Published: 22 March 2020
(This article belongs to the Special Issue Remote Sensing Monitoring of Land Surface Temperature (LST))
Landsat 8/thermal infrared sensor (TIRS) is suffering from the problem of stray light that makes an inaccurate radiance for two thermal infrared (TIR) bands and the latest correction was conducted in 2017. This paper focused on evaluation of land surface temperature (LST) retrieval from Landsat 8 before and after the correction using ground-measured LST from five surface radiation budget network (SURFRAD) sites. Results indicated that the correction increased the band radiance at the top of the atmosphere for low temperature but decreased such radiance for high temperature. The root-mean-square error (RMSE) of LST retrieval decreased by 0.27 K for Band 10 and 0.78 K for Band 11 using the single-channel algorithm. For the site with high temperature, the LST retrieval RMSE of the single-channel algorithm for Band 11 even reduced by 1.4 K. However, the accuracy of two of three split-window algorithms adopted in this paper decreased. After correction, the single-channel algorithm for Band 10 and the linear split-window algorithm had the least RMSE (approximately 2.5 K) among five adopted algorithms. Moreover, besides SURFRAD sites, it is necessary to validate using more robust and homogeneous ground-measured datasets to help solely clarify the effect of the correction on LST retrieval. View Full-Text
Keywords: land surface temperature; Landsat 8; stray light correction; split-window algorithm; single-channel algorithm land surface temperature; Landsat 8; stray light correction; split-window algorithm; single-channel algorithm
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Guo, J.; Ren, H.; Zheng, Y.; Lu, S.; Dong, J. Evaluation of Land Surface Temperature Retrieval from Landsat 8/TIRS Images before and after Stray Light Correction Using the SURFRAD Dataset. Remote Sens. 2020, 12, 1023.

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