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Set of solutions using remote sensing and supervised learning to replace autoregressive integrated moving average models to forecast weather
| Content Provider | Consultative Group on International Agricultural Research (CGIAR) |
|---|---|
| Description | Meteorological indices can be used as substitutes for AIs. We discuss meteorological indexes and review SL approaches that are suitable for predicting drought based on historical satellite data. |
| Sponsorship | CGIAR Research Program on Wheat |
| Related Links | https://cgspace.cgiar.org/items/0f986ba6-dd77-4433-8c61-65546909beb9 |
| File Format | |
| Language | English |
| Publisher Date | 2020-12-31 |
| Access Restriction | Open |
| Subject Keyword | Wheat Models Drought Remote Sensing Development Rural Development Data Learning Systems Weather Agrifood Systems Approaches Solutions Satellite |
| Content Type | Text |
| Resource Type | Report |
| Subject | Agronomy and Crop Science Food Science Plant Science |