Interactive map with expert annotations for model corrections
ESA Earth Observation Processing Framework for Sentinel-1, 2 and 3 data access
Collaborative GIS environment for Jupyter - required to open .jGIS files
Conda environment specification with all Python dependencies
Main Jupyter notebook implementing the wetland classification workflow
Jupyter notebook to create a RO-Crate in ROHub
Expert corrections extracted from JupyterGIS annotations
Cloud Optimized GeoTIFF - RGB composite from Sentinel-2 L2A
Serialized Random Forest model retrained with expert corrections
Initial Random Forest classification - before expert corrections
Improved classification after retraining with expert corrections
Human-in-the-loop machine learning workflow for wetland classification using Sentinel-2 data from ESA EOPF. Demonstrates collaborative annotation using JupyterGIS, model retraining with expert corrections, and FAIR research practices.
JupyterGIS Wetland ML Classification Demo - ESA EOPF
Fouilloux, Anne. "JupyterGIS Wetland ML Classification Demo - ESA EOPF." ROHub. Dec 21 ,2025. https://w3id.org/ro-id/10dc322d-eedd-43ff-a4af-7adb6281cb6e.
Science and technology/Technology and engineering/IT-computer sciences
Environment/Natural resources/Water/Wetlands
Other Commerce, Management, Tourism and Services
JupyterGIS Wetland ML Classification Demo - ESA EOPF Human-in-the-loop machine learning workflow for wetland classification using Sentinel-2 data from ESA EOPF.
JupyterGIS Wetland ML Classification Demo
Other Agricultural and Veterinary Sciences
Other Studies in Creative Arts and Writing
Commerce, Management, Tourism and Services
Artifical Intelligence and Image Processing
Other Information and Computing Sciences
Labour/Employment/Employment training/Retraining
Demonstrates collaborative annotation using JupyterGIS, model retraining with expert corrections, and FAIR research practices.
Mathematical and computer sciences (general)
Institutional: Government policies and programs
Biodiversity: state of habitats and species