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An integrated approach of field, weather, and satellite data for monitoring maize phenology
Efficient, more accurate reporting of maize (Zea mays L.) phenology, crop condition, and progress is crucial for agronomists and policy makers. Integration of satellite imagery with machine learning models has shown great potential to improve crop classification and facilitate in-season phenological...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8333045/ https://www.ncbi.nlm.nih.gov/pubmed/34344979 http://dx.doi.org/10.1038/s41598-021-95253-7 |