MACHINE LEARNING
Machine Learning Erosion Prediction Workflow
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CASE ANALYSIS
Scenario
A GIS team needs a reproducible pipeline to predict soil erosion risk from satellite imagery and rainfall data using machine learning, with model validation and map generation.
Key decisions
- Choosing whether to impute missing rainfall before feature engineering
- Deciding when model accuracy is sufficient for production mapping
When to reuse this
When building ML pipelines for environmental risk mapping with satellite and climate tabular data.
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