gee tutorials

In these tutorials, you’ll get an introduction to using Google Earth Engine (GEE) for remote sensing analysis. Even if you have no prior experience with programming, you should be able to follow along with the examples.

If you’re interested in learning a bit more, you can also check out Google’s Introduction to JavaScript for Earth Engine, which covers some more of the basics (at least enough to get you started).

For a more in-depth introduction to javascript, there are a number of free courses available online – Codecademy’s javascript course is a good place to start.

GEE is “a cloud-based platform for planetary-scale geospatial analysis” (Gorelick et al., 20171). With it, users have access to a number of tools, including entire satellite archives, machine-learning algorithms for classification, and computational power above what an average desktop user has access to.

In addition to being an introduction to GEE, these tutorials are also meant to serve as an introduction, or a refresher, on some of the fundamental concepts and techniques in remote sensing. The explanations will by no means be exhaustive, but they should serve as a starting point from which you can deepen your knowledge and understanding of remote sensing, and I will do my best to include links and references along the way.

getting an earth engine account

If you do not already have an Earth Engine account set up, head on over to https://earthengine.google.com/ to sign up (click the ‘Sign up’ button in the upper right-hand corner of the page). If you already have a Google account, you can use that to sign up; otherwise, you can also set it up using a different e-mail address.

script repository

For each of the different tutorials, I’ve created a script that will show the different steps. You are welcome to use these, or create your own scripts using the sample code provided as you read through the tutorial.

You can access the repository (collection) of scripts here.

When you open the repository, it will be added in your account under Reader. You will be able to view, and run, each of the scripts from your own account. If you want to save them to your acount, you’ll first have to edit the script (the easiest way to do this is by adding a comment at the top of the script), then click Save – you’ll then be asked if you want to make a copy of the script.

data catalog

The GEE data catalog is vast and ever-growing. If you have a particular application in mind, be sure to have a look through the catalog - you might find a number of datasets that will help you.

For the most part, these tutorials will stick to so-called optical images. Optical sensors use light in the visible and infrared portions of the electromagnetic spectrum (between about 400 nm – 3000 nm, or up to about 12000 nm for thermal infrared wavelengths).

Optical sensors differ based on the wavelengths acquired and the general operation, but for the most part the images look similar to what we can see with our eyes, which helps with interpretation. The optical sensors that we will make use of in these tutorials will primarily be Landsat or Sentinel-2 images, though we may use some others depending on the application.

contents

• getting started
  • adding and exporting images
  • spectral signatures
  • image collections and vectors
  • manual mapping (digitizing)
  • band maths
  • zonal statistics
• image classification
  • unsupervised classification
  • pixel-based classification
  • object-based classification
• change detection
  • visual analysis of changes
  • band maths and thresholding
  • repeat classification
  • change vector analysis
  • time series analysis
• image enhancement
  • image filtering
  • pansharpening
  • edge detection
  • spectral unmixing
  • principle component analysis
• advanced topics
  • creating an animation

references

1

Gorelick, N., M. Hancher, M. Dixon, S. Ilyushchenko, D. Thau, and R. Moore (2017). Google Earth Engine: Planetary-scale geospatial analysis for everyone. Rem. Sens. Env. 202, 18-27. doi: 10.1016/j.rse.2017.06.031