4. Introduction to Google Earth Engine (GEE) (5 min)¶
4.1. Google Earth Engine (GEE) Overview¶
Since geographical data are often large and complicated to store, GEE provides a quickly accessible collection of ready-to-use data products. In addition, it is open and free to the public (for non-commercial use).
GEE consists of a multi-petabyte “ready-to-use” data catalog alongside a high-performance, intrinsically parallel computation service. It can be accessed and controlled through an Internet-accessible application programming interface (API) and an associated web-based interactive development environment (IDE) that enables rapid prototyping and visualization of results [GHD+17].
Because all the datasets are available on the GEE platform, there is no need to manage the data, download them, change the file format, or update the geographic projection. It uses the power of thousands of computers located in Google data centers to carry out its heavy processing. This distributed network allows the user to finish a task in a few minutes for small areas and few days for a world-scale study.
GEE provides access to numerous remotely sensed datasets and derived products, including DMSP-OLS and VIIRS DNB. Some of the data is already provided in the platform processed and “ready-to-use”.
4.2. GEE Access¶
Accessing GEE is easy. Aspiring users will first need to sign up to the platform with their Google account. It is the same account, people use to access Youtube, Google drive, Gmail and any Google service. Google usually gives access to new users within 24 hours. Then, all a user needs to access GEE from anywhere in the world is an internet connection.
Data in GEE can be analyzed in two ways:
through the Javascript API via the GEE code editor, or
a Python API, geemap, that can be accessed through any Python environment, such as Jupyter notebooks. More on that in GEE Python API and geemap (5 min)
4.2.1. GEE Code editor¶
code.earthengine.google.com is the code editor that uses JavaScript to access, transform, analyze, visualize and manage satellite data in GEE.
4.2.2. Get to know the data¶
It will really help you to understand some of the exercises in this tutorial if you spend a little time getting familiar with the data in GEE.
For example, take a look at the DMSP-OLS dataset description in GEE. It provides summary information on how the data are collected and organized and what they represent as well as links to more detailed technical information on the source. You’ll also notice an “Earth Engine Snippet” (such as: ee.ImageCollection("NOAA/DMSP-OLS/NIGHTTIME_LIGHTS") – we will re-visit this as it is the key for pulling particular datasets in GEE.
You can also review the page on VIIRS-DNB stray-light corrected monthly composites in GEE.
You may notice that many datasets have multiple vintages and versions. The description usually give insight into what this means (otherwise you may have to go to the source information), but it is important to understand that there can be differences in the data from particular satellite systems.