The academy's 4 modules
A progression designed so each module builds on the previous one.
Module 1 — GIS and QGIS
The fundamentals, from free software to automation
A complete QGIS course: vector and raster data, projections, spatial analysis, georeferencing, queries, automation, and must-have plugins.
Capstone project
Map a forest area end-to-end: import, analysis, professional map, and report.
Module 2 — Remote Sensing
Reading and exploiting satellite imagery
Image sources, spectral indices (NDVI and many others), classification, change detection, radar (SAR), and the latest AI uses in remote sensing.
Capstone project
Track a forest area's evolution over 3 years and prioritize monitoring zones.
Module 3 — Machine Learning
Random Forest, regression, rigorous evaluation
Preparing a geospatial dataset, regression and classification, Random Forest in depth, model evaluation, clustering, and a practical intro to Python.
Capstone project
Estimate forest biomass for an area from field measurements and satellite data.
Module 4 — GeoAI
Foundation models, agents, and generative AI
Deep Learning applied to satellite imagery, reference foundation models (Prithvi, Clay, AlphaEarth), geospatial agents, ethics, and validation.
Capstone project
A capstone project combining all 4 modules for a fictional partner.
Companion resource
Google Earth Engine
100 ready-to-use JavaScript scripts
A library of 100 GEE scripts across 10 themes: basics, spectral indices, time series, Machine Learning, agriculture, forestry, GEDI biomass, water and fires, climate and topography, advanced projects.
Companion resource
100 ready-to-use JavaScript scripts
Module 6 — Hydrology and watersheds
RUSLE, SWAT, HEC-HMS, HEC-RAS, HAND/TWI
Watershed delineation, water erosion modeling (RUSLE), integrated modeling (SWAT), rainfall-runoff simulation (HEC-HMS), hydraulic flood modeling (HEC-RAS), and machine-learning flood susceptibility (HAND/TWI, Random Forest).
Companion resource
Full erosion/flood risk diagnosis on the Oum Er-Rbia basin, focused on the Oued Lakhdar — case study results being validated against published reference data, with direct outreach to the field researchers under way.