Reconstruction of land surface temperature under cloudy conditions from Landsat 8 data using annual temperature cycle model
文献类型：期刊论文
| 作者 | Zhu, Xiaolin3,4; Duan, Si-Bo4; Li, Zhao-Liang3,4; Wu, Penghai2; Wu, Hua6; Zhao, Wei5; Qian, Yonggang1 |
| 刊名 | REMOTE SENSING OF ENVIRONMENT
 |
| 出版日期 | 2022-11-01 |
| 卷号 | 281页码:16 |
| ISSN号 | 0034-4257 |
| 关键词 | Land surface temperature Cloudy conditions Annual temperature cycle model Landsat 8 |
| DOI | 10.1016/j.rse.2022.113261 |
| 通讯作者 | Duan, Si-Bo(duansibo@caas.cn) |
| 英文摘要 | Land surface temperature (LST) is an important parameter in the processes of energy exchange and water cycle between the land surface and the atmosphere. The impact of cloud cover leads to spatially incomplete of thermal infrared (TIR)-based LST products, which seriously hinders the applications of LST products in various fields. Several methods have been developed to reconstruct LST under cloudy conditions in previous studies, but there is a lack of an effective method for the reconstruction of cloudy LST at the spatial resolution of Landsat pixel (30 m). In this study, a novel method was proposed to reconstruct LST under cloudy conditions from Landsat 8 data. The LST reconstruction method includes four main steps: (1) identification of cloud-free, cloud-shadow, cloudobscured, and cloud-covered pixels by integrating the Fmask method with a cloud-shape matching method; (2) calculation of annual temperature cycle (ATC)-based reference LST by fitting an ATC model to all available Landsat 8 LST product during 2013-2020; (3) estimation of LST residual from spatially adjacent similar pixels; and (4) estimation of reconstructed LST in terms of the sum of ATC-based reference LST and LST residual. The performance of the LST reconstruction method was evaluated using Landsat 8 LST images under clear-sky conditions as reference data. The root mean squared error (RMSE) between reconstructed LST and Landsat 8 reference LST ranges from 0.9 K to 2.5 K. The LST reconstruction method was further applied to reconstruct actual Landsat 8 LST images under cloudy conditions. Compared with original Landsat 8 LST images, the spatial distribution of reconstructed LST images is more complete. The pattern of reconstructed LST images reflects the spatial variability of LST well. The accuracy of the LST reconstruction method was validated against in situ LST measurements at six SURFRAD (Surface Radiation Budget Network) sites. The overall bias and RMSE between reconstructed LST and in situ LST at all sites are approximately -0.3 K and 3.5 K, respectively. The LST reconstruction method has great potentials to improve the applications of Landsat LST product in urban thermal environment monitoring and crop water stress monitoring. |
| WOS关键词 | TIME-SERIES ; PRACTICAL APPROACH ; ENERGY FLUXES ; SATELLITE ; MODIS ; COVER ; PREDICTION ; FRAMEWORK ; ALGORITHM ; SURFRAD |
| 资助项目 | National Natural Science Foundation of China ; China Scholarship Council (CSC) ; [41921001] ; [42171362] |
| WOS研究方向 | Environmental Sciences & Ecology ; Remote Sensing ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| 出版者 | ELSEVIER SCIENCE INC |
| WOS记录号 | WOS:000862500100003 |
| 资助机构 | National Natural Science Foundation of China ; China Scholarship Council (CSC) |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/184908]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Duan, Si-Bo |
| 作者单位 | 1.Chinese Acad Sci, Aerosp Informat Res Inst, Key Lab Quantitat Remote Sensing Informat Technol, Beijing 100094, Peoples R China 2.Anhui Univ, Anhui Prov Key Lab Wetland Ecosyst Protect & Resto, Hefei 230601, Peoples R China 3.Univ Strasbourg, CNRS, ICube Lab, UMR 7357, 300 Bd Sebastien Brant,CS 10413, F-67412 Illkirch Graffenstaden, France 4.Chinese Acad Agr Sci, Inst Agr Resources & Reg Planning, Key Lab Agr Remote Sensing, Minist Agr & Rural Affairs, Beijing 100081, Peoples R China 5.Chinese Acad Sci, Inst Mt Hazards & Environm, Chengdu 610041, Peoples R China 6.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zhu, Xiaolin,Duan, Si-Bo,Li, Zhao-Liang,et al. Reconstruction of land surface temperature under cloudy conditions from Landsat 8 data using annual temperature cycle model[J]. REMOTE SENSING OF ENVIRONMENT,2022,281:16. |
| APA | Zhu, Xiaolin.,Duan, Si-Bo.,Li, Zhao-Liang.,Wu, Penghai.,Wu, Hua.,...&Qian, Yonggang.(2022).Reconstruction of land surface temperature under cloudy conditions from Landsat 8 data using annual temperature cycle model.REMOTE SENSING OF ENVIRONMENT,281,16. |
| MLA | Zhu, Xiaolin,et al."Reconstruction of land surface temperature under cloudy conditions from Landsat 8 data using annual temperature cycle model".REMOTE SENSING OF ENVIRONMENT 281(2022):16. |
入库方式： OAI收割
来源：地理科学与资源研究所
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