Welcome! We are about to learn something incredible: how to see our planet from space and make sense of what we see. By the end of this course, we will be loading satellite images, computing vegetation and water indices, classifying land cover, and building interactive maps that answer real questions about our changing world. Let's get started.
Course goals
- Navigate the Earth Engine Code Editor confidently.
- Load, filter, and visualize satellite imagery.
- Calculate spectral indices (NDVI, NDWI) and apply thresholds.
- Classify land cover using supervised and unsupervised methods.
- Export results and build interactive apps.
Why remote sensing matters
Think about this: satellites are photographing every corner of Earth, every single day. That data is sitting there, waiting for someone to ask the right questions. Environmental monitoring, urban planning, disaster response, agriculture, climate science: these fields all need people who can work with satellite imagery. The skills we build here are in high demand, and they are genuinely fun to learn.
Our first map in 60 seconds
Before we dive into theory, let's get a quick win. Copy this code into the Earth Engine Code Editor and click Run:
// Your first Earth Engine map!
var image = ee.Image('LANDSAT/LC08/C02/T1_L2/LC08_044034_20210623');
Map.centerObject(image, 8);
Map.addLayer(image, {
bands: ['SR_B4', 'SR_B3', 'SR_B2'],
min: 7000,
max: 12000
}, 'San Francisco Bay');
print('Congratulations! You just loaded a Landsat 8 image.');What you should see
A true-color satellite image of San Francisco Bay appears on the map. The console shows your success message. You've just used Earth Engine!
What we will learn together
- The basics of digital image processing and how sensors collect data from orbit.
- How to use Google Earth Engine to access and analyze satellite imagery.
- Methods for classifying land, water, and vegetation in images.
- Real-world case studies: tracking deforestation, mapping floods, monitoring crops, and more.
Prerequisites
No previous experience with Earth Engine or JavaScript is required. We will learn everything from scratch. That said, if you have some programming background or GIS experience, that will give you a head start.
Get ready
Take a look at the course schedule on the home page. The full syllabus will be posted on the course site and Canvas.
If you do not already have one, sign up for a Google Earth Engine account at earthengine.google.com/signup. Approval can take a few days, so let's get that started right away.
About this textbook
We designed this textbook to be a welcoming, accessible introduction to remote sensing. Many of the materials have been adapted and simplified so that the concepts feel approachable, even if you have never touched remote sensing or programming before.
Our goal is to give you a solid foundation in remote sensing fundamentals, practical skills in Google Earth Engine, and hands-on experience analyzing real environmental data. Everything is presented in a way that we hope feels engaging and clear.
Continue Your Learning Journey
Upon completing this textbook, you are warmly invited to continue your learning with more advanced resources. We especially recommend Cloud-Based Remote Sensing with Google Earth Engine: Fundamentals and Applications, a comprehensive free textbook created by over 100 contributors from around the world.
About the EEFA Book
The EEFA Book offers:
- 31 Fundamental Labs: Taking you from novice to advanced Earth Engine user
- 24 Application Chapters: Showcasing real-world uses across diverse fields
- Independent Chapters: Jump to any section that interests you
This resource represents the cutting edge of Earth Engine education and is perfect for deepening your expertise after mastering the fundamentals in this course.
Think of this course as your welcoming introduction to remote sensing, and the EEFA Book as your next step toward becoming an expert practitioner. Together, these resources provide a complete pathway from beginner to advanced remote sensing analyst.