Your Learning Path

Follow this progression to master Google Earth Engine

🎯 Skills You'll Master

JavaScript Basics
Image Loading
Band Math & Indices
Cloud Masking
Compositing
Classification
Accuracy Assessment
Exports
Time Series & Charting
Change Detection
Joins & Filtering
UI & Apps
Water Mapping
Forest Monitoring
Agricultural Analysis
Urban Analysis
SAR / Radar

Week 0: Welcome

Get set up and see what you'll achieve

Welcome Earth Engine API Why JavaScript?
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Week 1: JavaScript Fundamentals

Learn the language that powers Earth Engine

JavaScript Intro Client vs Server âš¡ Variables Functions Lab 1 Lab 2 Lab 3
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Week 2: Working with Images

Load, filter, and analyze satellite imagery

Image Collections Image Operations Cloud Masking âš¡ Band Arithmetic Spectral Indices NDVI Lab 6 Lab 8
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Week 3: Classification

Turn imagery into meaningful categories

Classification Intro âš¡ Unsupervised Supervised vs Unsupervised Accuracy Assessment âš¡ Lab 11 Lab 12
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Week 4: Data Export & Analysis

Aggregate data and export your results

Reducers Temporal Compositing âš¡ Exporting Data Batch Exports âš¡ Best Practices Lab 14 Lab 16
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Week 5: Case Studies

Apply your skills to real-world problems

Case Studies Overview Lab 17 Lab 18
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Week 6: Public Engagement & Apps

Share your work with the world

Public Engagement UI Widgets âš¡ App Examples âš¡ Publishing Apps Lab 19 Lab 20
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🎓 Advanced Topics

Deep dives into specific applications

River Morphology Snow Observatory Urban Heat Islands Fire Monitoring
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Week 4B: Intermediate Analysis

Bridge the gap between foundations and applications with key analytical techniques

Time Series Charting âš¡ Change Detection âš¡ Joins and Filtering Lab 21 Lab 22
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🌊 Domain Applications

Apply your skills to specific domains: water, forests, agriculture, cities, and radar

Hydrology âš¡ JRC Surface Water Deforestation âš¡ Agriculture Urban Analysis SAR Fundamentals âš¡ Lab 23 Lab 24 Lab 25 Lab 26 Lab 27

📚 Essential Resources

Debugging Guide GEE Best Practices Further Readings Official GEE Docs →

🚀 Ready for More? Continue with the EEFA Book

This course prepares you with the foundation to tackle the advanced Cloud-Based Remote Sensing with Google Earth Engine (EEFA Book, Springer Open Access). That 55-chapter textbook covers LandTrendr, CCDC, harmonic regression, object-based analysis, spectral unmixing, and integration with R and Python.

EEFA Book (Free) → EEFA Code Repository →

Legend:

Module Lab âš¡ = Key module