Harmonizing Agricultural Data for AI-Powered Intelligent Agricultural Systems Advisory Tool (ISAT) in Ethiopia
Agricultural decision making in Ethiopia is highly influenced by climate variability, however the effective use of agricultural data remains limited across meteorological, soil, and crop management domains. Differences in formats, spatial and temporal scales, and metadata standards reduce the usabil...
| Autores principales: | , , , , , , , |
|---|---|
| Formato: | Artículo preliminar |
| Lenguaje: | Inglés |
| Publicado: |
International Crops Research Institute for the Semi-Arid Tropics
2025
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/180317 |
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