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Fusing optical and SAR time series for LAI gap fillingwith multioutput Gaussian processes
The availability of satellite optical information is often hampered by the natural presence of clouds, which can be problematic for many applications. Persistent clouds over agricultural fields can mask key stages of crop growth, leading to unreliable yield predictions. Synthetic Aperture Radar (SAR...
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| Publicado no: | Remote Sens Environ |
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| Main Authors: | , , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
2019
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7613333/ https://ncbi.nlm.nih.gov/pubmed/36082234 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.rse.2019.111452 |
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