Google Earth Engine is a cloud-based platform that enables large-scale processing of satellite imagery to detect changes, map trends, and quantify differences on the Earth’s surface. This course covers the full range of topics in Earth Engine to give the participants practical skills to master the platform and implement their remote sensing projects.
16 Hours Live Instruction + 8 Hours of Self-study (Videos+Assignment)
The course is typically conducted in 4 sessions of 4 hours each.
- Familiarity with remote sensing concepts
- Implement remote sensing workflows in Earth Engine.
- Scale your analysis to large regions and over long periods of time.
- Build interactive apps for data exploration.
Upon successful completion of the course, participants will be issued an employer-verifiable certificate from Spatial Thoughts. Learn more.
Course Pre-work (Self-study, 2-hours)
- Introduction to Remote Sensing (video)
- Introduction to Earth Engine (video)
Session 1: Earth Engine Basics (Live Session, 4-hours)
- Introduction to the Code Editor
- Working with Image Collections
- Creating Mosaics and Composites
- Working with Feature Collections
Session 2: Earth Engine Intermediate (Live Session, 4-hours)
- Map/Reduce Programming Concepts
- Calculating Indices
- Cloud Masking
- Calculating Area and Statistics
- Time-series Charts
Session 3: Supervised Classification (Live Session, 4-hours)
- Introduction to Supervised Classification
- Classifying images
- Accuracy Assessment
- Hyperparameter Tuning
- Change Detection
Session 4: Earth Engine Advanced (Live Session, 4 hours)
- Client vs. Server
- Scaling your analysis and overcoming common errors
- Building User Interfaces in Earth Engine
- Publishing your first Earth Engine App
- Using the Google Earth Engine Python API
Post-Course Assignment: End-to-End Applications (Self-study, 6 hours)
Participants will be provided Step-by-step video-based walkthrough of implementing the following analysis using Earth Engine. Participants can continue their learning journey by implementing these projects for their region of interest after the class.
- Drought Monitoring: Calculating Rainfall Deviation from the 30-year mean using CHIRPS Gridded Rainfall Data (Video, 2-hours)
- Flood Mapping: Rapid mapping of a flood using Sentinel-1 SAR Data. (Video, 2-hours)
- Extracting Time-Series: Extracting a 10-year NDVI time-series over multiple polygons using MODIS data. (Video, 2-hours)
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Do check Ujaval’s new course on Applied Remote Sensing with Google Earth Engine. The way he structured his course is awesome and it covers all aspects of GEE along with its use case. I strongly recommend this course for those who want to master GEE.Raja Sivaranjan, Remote Sensing & GIS Specialist, Louis Dreyfus Company
Extremely useful course for water resources management. As the data and technology to access and analyse becomes easy and powerful, it is necessary to know how to use them. Spatial thoughts course is very useful in this regard.Sashikumar N, Water Resources Specialist, ACIWRM