BayGeo’s Remote Sensing Intro to Google Earth Engine (Fall 2025)

This course introduces the basics of radar remote sensing and interpreting Synthetic Aperture Radar (SAR) images. Learn the preprocessing steps of a SAR image and analyze the data. Understand how SAR images play a critical role in flood and forest mapping and learn the process. Get hands-on experience with Sentinel Application Toolbox (SNAP) and Google Earth Engine for SAR image processing, analysis and application.

Learning Objectives

• Navigate and utilize the Google Earth Engine interface proficiently for remote sensing applications.
• Access and import diverse satellite imagery datasets available on Google Earth Engine for their specific research needs.
• Apply basic image processing techniques, such as normalization, and filtering, to enhance the quality of remote sensing data.
• Conduct spectral analysis to identify and classify land cover features within satellite imagery.
• Perform time series analysis, demonstrating an understanding of temporal dynamics and changes over multiple images.
• Students will be able to integrate Google Earth Engine with GIS tools, exporting and utilizing results for further analysis or visualization in external platforms.

Workshop Dates:

• Tuesday, October 7 (6:00 - 9:00 p.m.) Class meets on Zoom
• Tuesday, October 14 (6:00 - 9:00 p.m.) Class meets on Zoom
• Tuesday, October 21 (6:00 - 9:00 p.m.) Class meets on Zoom

Lesson Plan

Day 1: Introduction to Remote Sensing

• Welcome and course overview
• Introduction to Remote Sensing
• Introduction to geospatial data with a focus on Raster Data
• What is Google Earth Engine (GEE)?
• Accessing GEE and setting up your environment
• Exploring the GEE Code Editor
• How to use the GEE default lessons and tutorials

• Exercise:
• Ensuring everyone can login to their Google Earth Engine Code Editor
• Running through Google Earth Engine Templates
• Modifying templates with different data sources

Day 2: Google Earth Engine Part 2

• GEE's data catalog and datasets
• Basic GEE scripting

• More advanced analysis, time series
• Generating charts

• Exercise: Simple remote sensing analysis in GEE

Day 3: Advanced Google Earth Engine and Remote Sensing

• Advanced GEE scripting and functions
• Spectral indices and their applications

• Land cover classification with GEE
• Custom scripts for specific applications

• Exercise: Land cover classification project

Instructor: Preethi BalajiI

I earned my Ph.D. in Synthetic Aperture Radar (SAR) remote sensing for forest disturbance monitoring in Ireland before moving to the United States. My expertise also includes optical remote sensing, where I have worked on various applications such as forest and crop monitoring, flood mapping, and ecological forecasting. Recently, I completed the NASA DEVELOP program at Idaho State University, Pocatello. I also write blogs on Medium, offering tutorials on SAR foundational principles and applications: https://medium.com/@preet.balaji20. Outside of work, I enjoy nature photography, particularly bird photography.

Questions?

• Contact Rick Kos, BayGeo's Education Director, at rkos@baygeo.org
• For more information about BayGeo, the Bay Area's hub for the geospatial community, visit baygeo.org