MACHINE LEARNING
ML Workflow for Riverbank Erosion Susceptibility Mapping
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CASE ANALYSIS
Scenario
A GIS analyst needs to map riverbank erosion susceptibility by training a Random Forest classifier on multiple environmental layers and validating the output.
Key decisions
- Choose to proceed with Random Forest after preprocessing GIS layers
- Loop back for hyperparameter tuning or feature adjustment when performance is insufficient
- Finalize only after field validation and expert review
When to reuse this
Use when automating erosion susceptibility mapping with supervised classification, especially with raster GIS inputs and a need for iterative model improvement.
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flowchart-ml-workflow-for-riverbank-erosion-susceptibility-mapping-usi