Inversion and Validation of FY-4A Official Land Surface Temperature Product
The thermal infrared data of Fengyun 4A (FY-4A) geostationary meteorological satellite can be used to retrieve hourly land surface temperature (LST). In this paper, seven candidate algorithms are compared and evaluated. The Ulivieri (1985) algorithm is determined to be optimal for the algorithm of F...
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MDPI AG
2023-05-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/15/9/2437 |
| _version_ | 1797601779548946432 |
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| author | Lixin Dong Shihao Tang Fuzhou Wang Michael Cosh Xianxiang Li Min Min |
| author_facet | Lixin Dong Shihao Tang Fuzhou Wang Michael Cosh Xianxiang Li Min Min |
| author_sort | Lixin Dong |
| collection | DOAJ |
| description | The thermal infrared data of Fengyun 4A (FY-4A) geostationary meteorological satellite can be used to retrieve hourly land surface temperature (LST). In this paper, seven candidate algorithms are compared and evaluated. The Ulivieri (1985) algorithm is determined to be optimal for the algorithm of FY-4A LST official products. The refined algorithm coefficients for distinguishing dry and moist atmosphere were established for daytime and nighttime, respectively. Then, FY-4A LST official products under clear-sky conditions are produced. The validation results show that: (1) Compared with in-situ measured LST data at the HeBi crop measurement network, the root mean square errors (RMSE) were 2.139 and 2.447 K. Compared with in-situ measured LST data at Naqu alpine meadow site of Tibet plateau, the RMSE was 2.86 K. (2) When compared with the MODIS LST product, the RMSE was 1.64, 2.17, 2.6, and 1.73 K in March, July, October, and December, respectively. By the bias long-time change at a single site, RMSE of the XLHT (city) and GZH (desert) sites were 2.735 and 2.97 K, respectively. Overall, the preferred algorithm exhibits good accuracy and meets the required accuracy of the FY-4A mission. |
| first_indexed | 2024-03-11T04:08:37Z |
| format | Article |
| id | doaj.art-ff6b5e26a88e4a28a57ba1be76f6e327 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-11T04:08:37Z |
| publishDate | 2023-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-ff6b5e26a88e4a28a57ba1be76f6e3272023-11-17T23:40:11ZengMDPI AGRemote Sensing2072-42922023-05-01159243710.3390/rs15092437Inversion and Validation of FY-4A Official Land Surface Temperature ProductLixin Dong0Shihao Tang1Fuzhou Wang2Michael Cosh3Xianxiang Li4Min Min5Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites, National Satellite Meteorological Center (National Center for Space Weather), China Meteorological Administration, Beijing 100081, ChinaKey Laboratory of Radiometric Calibration and Validation for Environmental Satellites, National Satellite Meteorological Center (National Center for Space Weather), China Meteorological Administration, Beijing 100081, ChinaHebi Meteorological Bureau of Henan Province, Hebi 458000, ChinaHydrology and Remote Sensing Laboratory, Agricultural Research Service, USDA, Beltsville, MD 20705, USASchool of Atmospheric Sciences, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Sun Yat-sen University (Zhuhai), Zhuhai 519082, ChinaSchool of Atmospheric Sciences, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Sun Yat-sen University (Zhuhai), Zhuhai 519082, ChinaThe thermal infrared data of Fengyun 4A (FY-4A) geostationary meteorological satellite can be used to retrieve hourly land surface temperature (LST). In this paper, seven candidate algorithms are compared and evaluated. The Ulivieri (1985) algorithm is determined to be optimal for the algorithm of FY-4A LST official products. The refined algorithm coefficients for distinguishing dry and moist atmosphere were established for daytime and nighttime, respectively. Then, FY-4A LST official products under clear-sky conditions are produced. The validation results show that: (1) Compared with in-situ measured LST data at the HeBi crop measurement network, the root mean square errors (RMSE) were 2.139 and 2.447 K. Compared with in-situ measured LST data at Naqu alpine meadow site of Tibet plateau, the RMSE was 2.86 K. (2) When compared with the MODIS LST product, the RMSE was 1.64, 2.17, 2.6, and 1.73 K in March, July, October, and December, respectively. By the bias long-time change at a single site, RMSE of the XLHT (city) and GZH (desert) sites were 2.735 and 2.97 K, respectively. Overall, the preferred algorithm exhibits good accuracy and meets the required accuracy of the FY-4A mission.https://www.mdpi.com/2072-4292/15/9/2437FY-4Ageostationary meteorological satelliteAGRIland surface temperature |
| spellingShingle | Lixin Dong Shihao Tang Fuzhou Wang Michael Cosh Xianxiang Li Min Min Inversion and Validation of FY-4A Official Land Surface Temperature Product Remote Sensing FY-4A geostationary meteorological satellite AGRI land surface temperature |
| title | Inversion and Validation of FY-4A Official Land Surface Temperature Product |
| title_full | Inversion and Validation of FY-4A Official Land Surface Temperature Product |
| title_fullStr | Inversion and Validation of FY-4A Official Land Surface Temperature Product |
| title_full_unstemmed | Inversion and Validation of FY-4A Official Land Surface Temperature Product |
| title_short | Inversion and Validation of FY-4A Official Land Surface Temperature Product |
| title_sort | inversion and validation of fy 4a official land surface temperature product |
| topic | FY-4A geostationary meteorological satellite AGRI land surface temperature |
| url | https://www.mdpi.com/2072-4292/15/9/2437 |
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