What you'll learn:
- Students will gain access to and a thorough knowledge of the Google Earth Engine platform
- Implement machine learning algorithms on geospatial (satellite images) data in Earth Engine for LULC mapping
- Get introduced and advance JavaScript skills on Google Earth Engine platform
- Fully understand the main types of Machine Learning (supervised and unsupervised learning)
- Learn how to apply supervised and unsupervised Machine Learning algorithms in Google Earth Engine
- Learn how to obtain satellite data, apply image preprocessing, create training and validation data in Google Earth Engine
- Implement calculation of change detection (pre and post-event detection) based on spectral indices
- You'll have a copy of the codes used in the course for your reference
Land Use and Land Cover (LULC) Mapping and Change Detection with Machine Learning in Google Earth Engine
This course provides a complete, practical introduction to machine learning and change detection using Google Earth Engine (GEE). Designed for learners with basic GIS and Remote Sensing knowledge, this course will equip you with the skills to map land use and land cover, detect changes over time, and work confidently with satellite imagery for environmental analysis.
Course Highlights
• Extensive coverage of supervised and unsupervised machine learning algorithms
• Hands-on LULC classification and change detection workflows
• Real projects using Landsat, Sentinel, and other satellite datasets
• Step-by-step image preprocessing, spectral indices, and classification design
• Downloadable datasets and JavaScript code files
• Access to future updates and resources
Course Focus
The course emphasizes practical, project-based learning. You will build complete workflows in Google Earth Engine, from data acquisition and preprocessing to machine learning classification and change detection. By the end of the course, you will be able to apply state-of-the-art geospatial methods to your own professional or research projects.
Why Choose This Course
Unlike many theoretical courses, every lecture here focuses on actionable skills. You will develop real, applied expertise in Google Earth Engine, machine learning for Remote Sensing, and change detection analysis. These skills are highly in demand in GIS, environmental science, climate studies, land management, and academic research.
What You Will Learn
• How to sign in and navigate the Google Earth Engine interface
• Cloud-based data preprocessing and spectral indices calculation
• Introduction to JavaScript for geospatial analysis
• Fundamentals of machine learning for GIS and Remote Sensing
• Supervised and unsupervised image classification using GEE
• Training and validation data creation and accuracy assessment
• LULC change detection methods for multi-date satellite imagery
• How to build and complete your own geospatial project on GEE
Ideal For
This course is suited for geographers, GIS analysts, Remote Sensing professionals, environmental scientists, programmers, social scientists, geologists, and anyone who needs to produce LULC maps or perform change detection for their work or research.
Hands-On Practical Experience
You will complete multiple practical exercises using real satellite data. Step-by-step instructions, datasets, and code files are included so you can follow along and build your own cloud-based geospatial workflows.
Included in the Course
• All datasets used in lectures
• JavaScript code files for GEE
• Access to future resources and updates
Enroll Today
Start mastering land use and land cover mapping, Remote Sensing machine learning, and change detection in Google Earth Engine. Enroll now to unlock powerful skills for environmental monitoring and geospatial analysis.
