paper
2019
Applications & impacts
Sub-seasonal to seasonal Application study
Classical ML (trees, GP, linear, kernels)Seasonal to annual Other
2019-01-07
008
Jan 2019
Francisco Zambrano, Anton Vrieling, Andy D. Nelson et al.
preprint
Neural network and linear models predict Chilean agricultural drought from ENSO, PDO and precipitation indices at 1-6 month lead times.
Prediction of agricultural drought in Chile from multiple spatio-temporal data sources
In one sentence. Neural network and linear models predict Chilean agricultural drought from ENSO, PDO and precipitation indices at 1-6 month lead times.
Labels
- Topic
- Applications & impacts, Sub-seasonal to seasonal
- Type
- Application study
- Method
- Classical ML (trees, GP, linear, kernels)
- Time scale
- Seasonal to annual
- Domain
- Regional
- Data
- Satellite, Other
- Status
- Research
- Identifiers
- DOI:10.1002/essoar.10500350.1 OpenAlex:W3138535517
- Added
- 2026-10-22
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