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machine learning · GIS · workflow

ML Workflow for Riverbank Erosion Susceptibility Mapping

Type OrganigrammeNorme Sugiyama layered DAG + orthogonal routingMoteur schematex-flowchartMis à jour 26/09/2026
ML Workflow for Riverbank Erosion Susceptibility Mapping
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Le scénario

A GIS analyst needs to map riverbank erosion susceptibility by training a Random Forest classifier on multiple environmental layers and validating the output.

Ce que contient ce dessin

Comprenez les décisions qui le sous-tendent.

01

Choose to proceed with Random Forest after preprocessing GIS layers

02

Loop back for hyperparameter tuning or feature adjustment when performance is insufficient

03

Finalize only after field validation and expert review

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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