Furkejuvvon:
| Váldodahkkit: | , , , , , |
|---|---|
| Materiálatiipa: | Recurso digital |
| Giella: | |
| Almmustuhtton: |
Zenodo
2025
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| Fáttát: | |
| Liŋkkat: | https://doi.org/10.5281/zenodo.17060846 |
| Fáddágilkorat: |
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Sisdoallologahallan:
- <p><span lang="EN-US">The LST dataset contains the surface temperature data of cultivated land worldwide during the period from 2003 to 2022. The unit is in degrees Celsius, with a time resolution of daily and a spatial resolution of 1000 meters.</span><a name="OLE_LINK5"></a><span lang="EN-US">It is produced by</span><span><span lang="EN-US"> </span></span><span><span lang="EN-US">combing</span></span><span><span lang="EN-US"> </span></span><span><span lang="EN-US">Fengyun and MODIS </span></span><span><span lang="EN-US">daily data</span></span><span><span lang="EN-US">, </span></span><span><span lang="EN-US">and meteorological station data</span></span><span><span lang="EN-US"> to </span></span><span><span lang="EN-US">reconst</span></span><span><span lang="EN-US">ruct</span></span><span><span lang="EN-US"> real </span></span><span><span lang="EN-US">LST</span></span><span><span lang="EN-US"> under cloud coverage</span></span><span><span lang="EN-US"> in </span></span><span><span lang="EN-US">dai</span></span><span><span lang="EN-US">ly </span></span><span><span lang="EN-US">LST images, </span></span><span><span lang="EN-US">and then a regression analysis model is constructed to further improve accuracy in </span></span><span><span lang="EN-US">six natural subregions with different climatic conditions</span></span><span><span lang="EN-US">. The accuracy analysis shows that the reconstruction result is closely correlated with the in-situ measurements, with an average MAE of 1-2 K.</span></span></p>