A Nonlinear Split-Window Algorithm for Retrieving Land Surface Temperatures From Fengyun-4B Thermal Infrared Data
文献类型：期刊论文
| 作者 | Zhao, Junli1,2; Tang, Bo-Hui1,2; Sima, Ouyang1,2,3 |
| 刊名 | IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
 |
| 出版日期 | 2024 |
| 卷号 | 62页码:12 |
| 关键词 | Atmospheric modeling Land surface temperature Satellites Ocean temperature Land surface Temperature distribution Sea surface Fengyun-4B (FY-4B) land surface temperature (LST) nonlinear split-window (NSW) algorithm temperature and emissivity separation (TES) |
| ISSN号 | 0196-2892 |
| DOI | 10.1109/TGRS.2023.3348526 |
| 通讯作者 | Tang, Bo-Hui(tangbh@kust.edu.cn) |
| 英文摘要 | This article proposes a combination method of nonlinear split-window (NSW) algorithm and temperature and emissivity separation (TES) algorithm to estimate land surface temperature (LST) from the remotely sensed data observed by the Advanced Geosynchronous Radiation Imager (AGRI) onboard Fengyun-4B (FY-4B), China's second-generation meteorological geostationary satellite. The atmospheric radiation transfer model MODTRAN5.2 is used to simulate the AGRI thermal infrared (TIR) channel satellite observations in ten different viewing zenith angles (VZAs) from 0 degrees to 70 degrees. The optimal thermal channel combination and coefficients of the NSW algorithm are determined using a statistical regression method according to the grouping of the mean emissivity, the atmospheric water vapor content (WVC), and the LST. ERA5 reanalysis data provide atmospheric profiles for atmospheric correction, and then, the land surface emissivity (LSE) could be estimated according to the TES algorithm. The combination of Channel-12 (centered at 8.55 mu m ) and Channel-14 (centered at 12.00 mu m ) or the combination of Channel-13 (centered at 10.80 mu m ) and Channel-14 (centered at 12.00 mu m ) depends on different groups and VZAs. The statistical regression analysis showed that the root-mean-square error (RMSE) between the simulated and estimated LST is less than 0.7 and 1.8 K with the determined emissivity under VZA = 0 degrees and VZA = 60 degrees, respectively. Compared with the MODIS LST products (MYD11A1), the retrieved LST image has a similar spatial distribution, with the RMSE of 1.71 K. |
| WOS关键词 | EMISSIVITY ; WATER ; VALIDATION ; ASTER |
| 资助项目 | National Natural Science Foundation of China |
| WOS研究方向 | Geochemistry & Geophysics ; Engineering ; Remote Sensing ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| WOS记录号 | WOS:001166445400017 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| 资助机构 | National Natural Science Foundation of China |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/203568]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Tang, Bo-Hui |
| 作者单位 | 1.Kunming Univ Sci & Technol, Fac Land Resource Engn, Kunming 650093, Peoples R China 2.Dept Educ Yunnan Prov, Key Lab Plateau Remote Sensing, Kunming 650093, Peoples R China 3.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 | Zhao, Junli,Tang, Bo-Hui,Sima, Ouyang. A Nonlinear Split-Window Algorithm for Retrieving Land Surface Temperatures From Fengyun-4B Thermal Infrared Data[J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,2024,62:12. |
| APA | Zhao, Junli,Tang, Bo-Hui,&Sima, Ouyang.(2024).A Nonlinear Split-Window Algorithm for Retrieving Land Surface Temperatures From Fengyun-4B Thermal Infrared Data.IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,62,12. |
| MLA | Zhao, Junli,et al."A Nonlinear Split-Window Algorithm for Retrieving Land Surface Temperatures From Fengyun-4B Thermal Infrared Data".IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 62(2024):12. |
入库方式： OAI收割
来源：地理科学与资源研究所
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