Workshop Description:
Join us on October 15th, 2026 for a hands-on workshop where participants will learn how to interact with Google Earth Engine's (GEE) JavaScript API through an exploration of NDVI analysis. During this workshop participants will learn how to create a GEE Script for GEE's JavaScript interface that utilizes NDVI analysis as a means to learn how to interact with GEE, analyze images, produce charts, and export results for further analysis.
During the workshop the instructor will walk participants through creating a GEE script that classifies NDVI for two time periods in a specific region of interest, how to display the final product in Google Earth Engine, and how to export the resulting files to utilize for analysis in QGIS. Building the script will give participants the tools to conduct their own analysis utilizing GEE in the future.
The instructor will build the script live alongside participants, but participants will have a copy of the script prior to the workshop to follow along with as well. Participants are encouraged to ask questions or refer to the provided script for any bugs that may come up as they follow along with the workshop. At the end of the workshop participants will have a script they can customize for other analysis going forward.
Speaker:
Kaylan Soares is a 2024 graduate of the University of Washington, while she studied Environmental Science and Natural Resource Management and Urban Ecological Design. She is currently based in the Boston area. She has been developing her skills in Google Earth Engine over the past 4 years and shared some of her past work with Women in GIS. Her goal is to aid communities in reaching climate resiliency through the democratization of spatial technology and knowledge.
Format:
This workshop is 3-hours long and will be broken up into four separate parts:
Part 1: Introduction to Google Earth Engine
Participants will learn how to set up a Google Earth Engine Account, gain a brief introduction into how image processing in GEE works, learn some of the benefits and drawbacks of the technology, and begin to understand how to interact with GEE JavaScript API by looking at a single image in GEE.
Part 2: Image Processing in Google Earth Engine
Participants will learn how to create analysis areas by practicing uploading shape files, drawing polygons using GEE geometry tools, and creating polygons by dictating coordinates. They will also learn how to select image collections and images and prepare them for analysis. Lastly in this section, participants will learn how to add bands to images and image collections, and how to display their results on a map in GEE.
Part 3: Analyzing Google Earth Engine Images
In this section participants will learn how to analyze Google Earth Engine Images by running a series of calculations on the NDVI results of two time periods in the region of interest, ending in an unsupervised classification of NDVI. Participants will then learn how to create charts, legends, and a swipe panel in the GEE interface to further interact with the results of the classification and NDVI analysis.
Part 4: Exporting Results and Further Exploration
Participants will be walked through how to export their results from Google Earth Engine; this will include exporting images, .shp files, and charts. Following this, participants will conduct a brief analysis of the data in QGIS. To save time on the QGIS analysis, participants will be provided with a folder containing the copies of the files created during the script to bring into QGIS.
What folks need:
- Computer or laptop
- A GMail account, please follow this link to create one if you do not already have one: http://gmail.com
- The latest version of QGIS downloaded and set up on the device you are using, please download at this link if you do not already have it: https://www.qgis.org/download/
Key Takeaways:
- Understand how to interact with GEE API through JavaScript coding.
- Learn how to create new image bands and analyze images in Google Earth Engine.
- Gain an understanding of what the applications and limitations of this technology are, and how this technology can be paired with other free tools for powerful analysis.
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