| _version_ | 1866901662681006080 |
|---|---|
| author | Jie Cheng Weihan Liu Chenze Wu |
| author_facet | Jie Cheng Weihan Liu Chenze Wu |
| contents | <p>The <strong>E</strong>ssential therma<strong>L</strong> <strong>I</strong>nfrared remo<strong>T</strong>e s<strong>E</strong>nsing (<strong>ELITE</strong>) product suite currently has four types of products, including land surface temperature (LST: clear-sky and all-sky), emissivity (NBE: narrowband emissivity; BBE: broadband emissivity; and spectral emissivity), the component of surface radiation and energy budget (SLUR: surface longwave upwelling radiation; SLDR: surface longwave downward radiation SLDR; SLNR: surface longwave net radiation), and the component of Earth's radiation budget (OLR; outgoing longwave radiation; RSR: reflected solar radiation). The spatial-temporal resolutions of the ELITE products are mainly determined by the employed satellite data sources. For more information about ELITE products, please refer to the website (<a href="https://elite.bnu.edu.cn">https://elite.bnu.edu.cn</a>).</p> <p>This dataset is the ELITE hourly seamless 4 km LST dataset covering the FY-4A/AGRI nominal fixed disc (80.6°N-80.6°S, 24.1°E-174.7°W). First, an improved temperature and emissivity separation algorithm was used to obtain the clear-sky LST. Then, under the framework of the SEB theory, a unique way was proposed to solve the temperature difference between the cloudy-sky LST and hypothetical clear-sky LST caused by cloud radiative effects. The in situ validation results show that the bias (RMSE) of the AGRI hourly seamless LST is 0.02 K (2.84 K). The temporal resolution and spatial resolution of this dataset are 1 hour and 4 km, respectively.</p> <p>This is the ELITE FY-4A/AGRI seamless LST product in 2023. Please <a href="../records/10595576"><strong><em>click here</em></strong></a> to download the ELITE LST product in 2022.</p> <p><strong>Dataset Characteristics:</strong></p> <ul> <li>Spatial Coverage: AGRI nominal fixed disc (80.6°N-80.6°S, 24.1°E-174.7°W)</li> <li>Temporal Coverage: 2023.1-2023.5</li> <li>Spatial Resolution: 4 km (subsatellite point)</li> <li>Temporal Resolution: one hour</li> <li>Data Format: HDF</li> <li>Scale: 0.01</li> </ul> <p><strong>Citation </strong>(Please cite these papers when using the data)<strong>:</strong></p> <ol> <li>Liu, W., Cheng, J. & Wang, Q. (2023). Estimating Hourly All-Weather Land Surface Temperature From FY-4A/AGRI Imagery Using the Surface Energy Balance Theory. <em>IEEE Transactions on Geoscience and Remote Sensing, 61</em>,<em> 5001518</em></li> </ol> <p>If you have any questions, please contact Prof. Jie Cheng (eliteqrs@126.com).</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_10671815 |
| institution | Zenodo |
| language | |
| publishDate | 2024 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | ELITE land surface temperature: FY-4A/AGRI hourly 4km seamless LST (2023.1-2023.5) Jie Cheng Weihan Liu Chenze Wu land surface temperature FY-4A/AGRI thermal infrared remote sensing seamless land surface temperature <p>The <strong>E</strong>ssential therma<strong>L</strong> <strong>I</strong>nfrared remo<strong>T</strong>e s<strong>E</strong>nsing (<strong>ELITE</strong>) product suite currently has four types of products, including land surface temperature (LST: clear-sky and all-sky), emissivity (NBE: narrowband emissivity; BBE: broadband emissivity; and spectral emissivity), the component of surface radiation and energy budget (SLUR: surface longwave upwelling radiation; SLDR: surface longwave downward radiation SLDR; SLNR: surface longwave net radiation), and the component of Earth's radiation budget (OLR; outgoing longwave radiation; RSR: reflected solar radiation). The spatial-temporal resolutions of the ELITE products are mainly determined by the employed satellite data sources. For more information about ELITE products, please refer to the website (<a href="https://elite.bnu.edu.cn">https://elite.bnu.edu.cn</a>).</p> <p>This dataset is the ELITE hourly seamless 4 km LST dataset covering the FY-4A/AGRI nominal fixed disc (80.6°N-80.6°S, 24.1°E-174.7°W). First, an improved temperature and emissivity separation algorithm was used to obtain the clear-sky LST. Then, under the framework of the SEB theory, a unique way was proposed to solve the temperature difference between the cloudy-sky LST and hypothetical clear-sky LST caused by cloud radiative effects. The in situ validation results show that the bias (RMSE) of the AGRI hourly seamless LST is 0.02 K (2.84 K). The temporal resolution and spatial resolution of this dataset are 1 hour and 4 km, respectively.</p> <p>This is the ELITE FY-4A/AGRI seamless LST product in 2023. Please <a href="../records/10595576"><strong><em>click here</em></strong></a> to download the ELITE LST product in 2022.</p> <p><strong>Dataset Characteristics:</strong></p> <ul> <li>Spatial Coverage: AGRI nominal fixed disc (80.6°N-80.6°S, 24.1°E-174.7°W)</li> <li>Temporal Coverage: 2023.1-2023.5</li> <li>Spatial Resolution: 4 km (subsatellite point)</li> <li>Temporal Resolution: one hour</li> <li>Data Format: HDF</li> <li>Scale: 0.01</li> </ul> <p><strong>Citation </strong>(Please cite these papers when using the data)<strong>:</strong></p> <ol> <li>Liu, W., Cheng, J. & Wang, Q. (2023). Estimating Hourly All-Weather Land Surface Temperature From FY-4A/AGRI Imagery Using the Surface Energy Balance Theory. <em>IEEE Transactions on Geoscience and Remote Sensing, 61</em>,<em> 5001518</em></li> </ol> <p>If you have any questions, please contact Prof. Jie Cheng (eliteqrs@126.com).</p> |
| title | ELITE land surface temperature: FY-4A/AGRI hourly 4km seamless LST (2023.1-2023.5) |
| topic | land surface temperature FY-4A/AGRI thermal infrared remote sensing seamless land surface temperature |
| url | https://doi.org/10.5281/zenodo.10671815 |