An integrated approach of field, weather, and satellite data for monitoring maize phenology
Abstract 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 phe...
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| Auteurs principaux: | , , , , |
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| Format: | article |
| Langue: | EN |
| Publié: |
Nature Portfolio
2021
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| Accès en ligne: | https://doaj.org/article/c7875ae560b54618815e0502ea516170 |
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