Arid
DOI10.1109/TGRS.2023.3288584
Land Surface Temperature Retrieval From Sentinel-3A SLSTR Data: Comparison Among Split-Window, Dual-Window, Three-Channel, and Dual-Angle Algorithms
Li, Ruibo; Li, Hua; Hu, Tian; Bian, Zunjian; Liu, Fangjian; Cao, Biao; Du, Yongming; Sun, Lin; Liu, Qinhuo
通讯作者Li, H
来源期刊IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
ISSN0196-2892
EISSN1558-0644
出版年2023
卷号61
英文摘要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 Perez-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.
英文关键词Land surface temperature (LST) Sea and Land Surface Temperature Radiometer (SLSTR) split-window (SW) algorithm validation
类型Article
语种英语
收录类别SCI-E
WOS记录号WOS:001030654100001
WOS关键词THERMAL-INFRARED EMISSIVITY ; RADIANCE-BASED VALIDATION ; NIGHTTIME MIDDLE ; ARID AREA ; SATELLITES ; PRODUCTS ; MODELS ; VIIRS ; SEA
WOS类目Geochemistry & Geophysics ; Engineering, Electrical & Electronic ; Remote Sensing ; Imaging Science & Photographic Technology
WOS研究方向Geochemistry & Geophysics ; Engineering ; Remote Sensing ; Imaging Science & Photographic Technology
资源类型期刊论文
条目标识符http://119.78.100.177/qdio/handle/2XILL650/396910
推荐引用方式
GB/T 7714
Li, Ruibo,Li, Hua,Hu, Tian,et al. Land Surface Temperature Retrieval From Sentinel-3A SLSTR Data: Comparison Among Split-Window, Dual-Window, Three-Channel, and Dual-Angle Algorithms[J],2023,61.
APA Li, Ruibo.,Li, Hua.,Hu, Tian.,Bian, Zunjian.,Liu, Fangjian.,...&Liu, Qinhuo.(2023).Land Surface Temperature Retrieval From Sentinel-3A SLSTR Data: Comparison Among Split-Window, Dual-Window, Three-Channel, and Dual-Angle Algorithms.IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,61.
MLA Li, Ruibo,et al."Land Surface Temperature Retrieval From Sentinel-3A SLSTR Data: Comparison Among Split-Window, Dual-Window, Three-Channel, and Dual-Angle Algorithms".IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 61(2023).
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