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Utilizing Collocated Crop Growth Model Simulations to Train Agronomic Satellite Retrieval Algorithms
Due to its worldwide coverage and high revisit time, satellite-based remote sensing provides the ability to monitor in-season crop state variables and yields globally. In this study, we presented a novel approach to training agronomic satellite retrieval algorithms by utilizing collocated crop growt...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
2018
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6349260/ https://www.ncbi.nlm.nih.gov/pubmed/30701108 http://dx.doi.org/10.3390/rs10121968 |