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Persistent Identifier
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perma:LIST.NWCBMV |
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Publication Date
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2026-07-06 |
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Title
| Land Surface Temperature Retrieval From Sentinel-3A SLSTR Data: Comparison Among Split-Window, Dual-Window, Three-Channel, and Dual-Angle Algorithms [* Cross-Reference *] |
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Other Identifier
| https://doi.org/10.1109/TGRS.2023.3288584
SCOPUS_ID:85163507128 |
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Author
| Li, Ruibo (Aerospace Information Research Institute, Shandong University of Science and Technology) - ORCID: 0000-0002-0857-7707
Li, Hua (Aerospace Information Research Institute, Shandong University of Science and Technology) - ORCID: 0000-0003-3834-2682
Hu, Tian (Luxembourg Institute of Science and Technology, Shandong University of Science and Technology)
Bian, Zunjian (Aerospace Information Research Institute, Shandong University of Science and Technology) - ORCID: 0000-0002-2433-9901
Liu, Fangjian (Aerospace Information Research Institute, Shandong University of Science and Technology)
Cao, Biao (Aerospace Information Research Institute, Shandong University of Science and Technology) - ORCID: 0000-0001-7877-8398
Du, Yongming (Aerospace Information Research Institute, Shandong University of Science and Technology) - ORCID: 0000-0001-7823-3566
Sun, Lin (Aerospace Information Research Institute, Shandong University of Science and Technology) - ORCID: 0000-0002-7105-4263
Liu, Qinhuo (Aerospace Information Research Institute, Shandong University of Science and Technology) - ORCID: 0000-0002-3713-9511 |
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Point of Contact
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Use email button above to contact.
LIST RDS (LIST) |
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Description
| Land surface temperature (LST) is a vital parameter for studying global ecological, climatic, and environmental changes. Although various LST retrieval algorithms have been proposed, including split-window (SW), dual-window (DW), three-channel (TC), and dual-angle (DA) algorithms, few studies have compared these algorithms using the same satellite observations. The Sea and Land Surface Temperature Radiometer (SLSTR) onboard Sentinel-3A provides a unique opportunity to conduct this comparison due to its DA viewing capability and multiple thermal infrared (TIR) and mid-infrared (MIR) channels. Here, we implemented two SW algorithms, one DW algorithm, two TC algorithms, and one DA algorithm for the SLSTR data. The LST retrievals from these six algorithms were validated, along with the SLSTR operational LST product based on an emissivity-implicit SW algorithm. Temperature- and radiance-based validation methods were used to evaluate different LST retrievals across different land cover types (LCTs). The results indicated that the proposed SW algorithm had the highest accuracy, followed by the Pérez-Planells SW and the official algorithms. The overall root-mean-square errors (RMSEs) of these three SW algorithms were 1.42, 1.79, and 2.05 K. The three algorithms involving the MIR channel (one DW and two TC algorithms) were more suitable for nighttime LST retrieval and had similar performances to the three SW algorithms, with a nighttime RMSE of approximately 1.36 K. The LST retrieval accuracy of the DA algorithm had the highest uncertainty and was closely related to the angular variation in surface emissivity and brightness temperature (BT). The findings of this study contribute to a better understanding of the different LST retrieval algorithms and facilitate potential improvements in the official LST retrieval algorithm for SLSTR. (2023-01-01)
***This entry has been automatically imported via Infodoc(ASO) CSV by LIST harvest scripts. Please refer to https://doi.org/10.1109/TGRS.2023.3288584 for the original and latest version of the dataset and data downloads*** (2026-06-19) |
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Subject
| Earth and Environmental Sciences |
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Keyword
| Land surface temperature (LST)
Sea and Land Surface Temperature Radiometer (SLSTR)
split-window (SW) algorithm
validation |
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Deposit Date
| 2023-01-01 |
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Data Type
| Article |
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Data Source
| IEEE Transactions on Geoscience and Remote Sensing; ISSN: 01962892, eISSN: 15580644, vol. 61, 2023 |
