Land surface temperature retrieval from SDGSAT-1: assessment of different retrieval algorithms with different atmospheric reanalysis data
Land surface temperature (LST) is an important parameter, with significant implications for climate change, urban heat island effects, and agricultural drought monitoring. The thermal infrared payload of SDGSAT-1 has three thermal infrared channels with a spatial resolution of 30 m, which is signifi...
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2025-08-01
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| Series: | International Journal of Digital Earth |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/17538947.2025.2492314 |
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| author | Meng Zhou Huadong Guo Xiaoying Ouyang Dinoo Gunasekera Zhongchang Sun |
| author_facet | Meng Zhou Huadong Guo Xiaoying Ouyang Dinoo Gunasekera Zhongchang Sun |
| author_sort | Meng Zhou |
| collection | DOAJ |
| description | Land surface temperature (LST) is an important parameter, with significant implications for climate change, urban heat island effects, and agricultural drought monitoring. The thermal infrared payload of SDGSAT-1 has three thermal infrared channels with a spatial resolution of 30 m, which is significantly finer than many existing thermal infrared satellites. This study aims to evaluate the performance of different LST retrieval methods using SDGSAT-1 thermal infrared data in conjunction with different atmospheric reanalysis datasets. The methods examined include the single channel (SC), the split window (SW) and the temperature emissivity separation (TES) method. Since the SC and TES methods require atmospheric profile data for surface temperature inversion, they were compared using two atmospheric reanalysis datasets: MERRA2 and ERA5. To compare the accuracy of the surface temperature inversion results, site data from the Heihe River Basin Observation Network were used for validation. The results indicate that the SW algorithm achieved the highest retrieval accuracy, followed by the TES algorithm, with the SC algorithm showing lower accuracy. Additionally, ERA5 outperformed MERRA2. Seasonal analysis revealed that retrieval results were generally more accurate in autumn than in summer. This study provides theoretical support for the development of LST products based on SDGSAT-1 satellite data. |
| format | Article |
| id | doaj-art-321b68093e4249a6bc049b136bc81f2f |
| institution | Kabale University |
| issn | 1753-8947 1753-8955 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | International Journal of Digital Earth |
| spelling | doaj-art-321b68093e4249a6bc049b136bc81f2f2025-08-25T11:24:40ZengTaylor & Francis GroupInternational Journal of Digital Earth1753-89471753-89552025-08-0118110.1080/17538947.2025.2492314Land surface temperature retrieval from SDGSAT-1: assessment of different retrieval algorithms with different atmospheric reanalysis dataMeng Zhou0Huadong Guo1Xiaoying Ouyang2Dinoo Gunasekera3Zhongchang Sun4Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, People’s Republic of ChinaAerospace Information Research Institute, Chinese Academy of Sciences, Beijing, People’s Republic of ChinaAerospace Information Research Institute, Chinese Academy of Sciences, Beijing, People’s Republic of ChinaAerospace Information Research Institute, Chinese Academy of Sciences, Beijing, People’s Republic of ChinaAerospace Information Research Institute, Chinese Academy of Sciences, Beijing, People’s Republic of ChinaLand surface temperature (LST) is an important parameter, with significant implications for climate change, urban heat island effects, and agricultural drought monitoring. The thermal infrared payload of SDGSAT-1 has three thermal infrared channels with a spatial resolution of 30 m, which is significantly finer than many existing thermal infrared satellites. This study aims to evaluate the performance of different LST retrieval methods using SDGSAT-1 thermal infrared data in conjunction with different atmospheric reanalysis datasets. The methods examined include the single channel (SC), the split window (SW) and the temperature emissivity separation (TES) method. Since the SC and TES methods require atmospheric profile data for surface temperature inversion, they were compared using two atmospheric reanalysis datasets: MERRA2 and ERA5. To compare the accuracy of the surface temperature inversion results, site data from the Heihe River Basin Observation Network were used for validation. The results indicate that the SW algorithm achieved the highest retrieval accuracy, followed by the TES algorithm, with the SC algorithm showing lower accuracy. Additionally, ERA5 outperformed MERRA2. Seasonal analysis revealed that retrieval results were generally more accurate in autumn than in summer. This study provides theoretical support for the development of LST products based on SDGSAT-1 satellite data.https://www.tandfonline.com/doi/10.1080/17538947.2025.2492314SDGSAT-1thermal infrared data (TIR)land surface temperature (LST)Validation |
| spellingShingle | Meng Zhou Huadong Guo Xiaoying Ouyang Dinoo Gunasekera Zhongchang Sun Land surface temperature retrieval from SDGSAT-1: assessment of different retrieval algorithms with different atmospheric reanalysis data International Journal of Digital Earth SDGSAT-1 thermal infrared data (TIR) land surface temperature (LST) Validation |
| title | Land surface temperature retrieval from SDGSAT-1: assessment of different retrieval algorithms with different atmospheric reanalysis data |
| title_full | Land surface temperature retrieval from SDGSAT-1: assessment of different retrieval algorithms with different atmospheric reanalysis data |
| title_fullStr | Land surface temperature retrieval from SDGSAT-1: assessment of different retrieval algorithms with different atmospheric reanalysis data |
| title_full_unstemmed | Land surface temperature retrieval from SDGSAT-1: assessment of different retrieval algorithms with different atmospheric reanalysis data |
| title_short | Land surface temperature retrieval from SDGSAT-1: assessment of different retrieval algorithms with different atmospheric reanalysis data |
| title_sort | land surface temperature retrieval from sdgsat 1 assessment of different retrieval algorithms with different atmospheric reanalysis data |
| topic | SDGSAT-1 thermal infrared data (TIR) land surface temperature (LST) Validation |
| url | https://www.tandfonline.com/doi/10.1080/17538947.2025.2492314 |
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