Google Earth Engine for Water Resources Management

GIS and Remote Sensing plays a critical role in the management of water resources. Many practitioners in this field are constrained by the availability of tools and computing resources to use these techniques effectively. Recent advances in cloud computing technology have given rise to platforms such as Google Earth Engine, which provide free access to a large pool of computational resources and datasets. The course is designed for researchers in the water sector, academicians, water managers, and stakeholders with basic knowledge of Remote Sensing. It will enable them to leverage this platform for water resource management applications.


The aim of this course is to introduce Google Earth Engine platform to apply remote sensing techniques using openly available Earth Observation datasets. The course will also teach participants how to build water related applications for state and country-wide analysis, mapping and monitoring.


24 Hours Live Instruction with 8 Hours of Self-study materials (Videos+Assignment)

The course is typically conducted in 6 sessions of 4 hours each.


  • Familiarity with remote sensing concepts

Learning Outcomes

  • Implement remote sensing workflows in Earth Engine.
  • Scale your analysis to large regions and over long periods of time.
  • Build interactive apps for data exploration.

Course Outline

Course Pre-work (Self-study, 2-hours)

  • Introduction to Remote Sensing (video)
  • Introduction to Earth Engine (video)

Session 1: Google Earth Engine Fundamentals (Live Session, 4-hours)

  • Introduction to the Code Editor
  • Fundamentals of Javascript programming
  • Working with Image Collections
  • Working with Feature Collections
  • Creating Mosaics and Composites
  • Calculating Indices (NDVI, MNDWI, AWEI)
  • Computation on Images (Simple Thresholding, Raster Algebra)
  • Exporting Raster Data

Session 2: Surface Water Mapping (Live Session, 4-hours)

  • Introduction to Water Detection Techniques
    • Simple Thresholding
    • Dynamic Thresholding using Otsu’s method
    • Unsupervised Clustering
  • Introduction to the Global Surface Water (GSW) dataset
  • Extracting Seasonal and Permanent Waterbodies
  • Image Processing (Kernels, Convolutions, and Morphological Operations)
  • Image Masking
  • Raster to Vector Conversion
  • Exporting Vector Data

Session 3: Precipitation Time Series Analysis (Live Session, 4-hours)

  • Introduction to Gridded Precipitation and Climate Datasets
  • Map/Reduce Programming Concepts
  • Calculating Total Rainfall in a Region
  • Creating Time-series Charts
  • Exporting a Time-series of Rainfall in a Region
  • Calculating Long-Term Monthly Average Rainfall
  • Trend Analysis using Sen’s Slope Statistic

Assignments (Self Study, 2-hours)

  • Assignment 1: Extracting Waterbodies in a Watershed
  • Assignment 2: Time Series Analysis of Evapotranspiration

Session 4: Land Use Land Cover Mapping (Live Session, 4-hours)

  • Introduction to Machine Learning and Supervised Classification
  • Land cover classification
  • Accuracy Assessment
  • Calculating Area

Session 5: Flood Mapping (Live Session, 4-hours)

  • Introduction to Radar Remote Sensing
  • Visualizing SAR Imagery
  • Change Detection Methods for Detecting Floods
  • Rapid Flood Mapping using UN-SPIDER methodology

Session 6: Drought Mapping and Creating Earth Engine Apps (Live Session, 4-hours)

  • Introduction to Drought Mapping and Monitoring
  • Calculating Vegetation Condition Index (VCI)
  • Introduction to the User Interface (UI) API
  • Building your First GEE App
  • Publishing the GEE App on Google Cloud


Upon successful completion of all the live online sessions and completing the assignments, participants will be issued an employer-verifiable certificate from Spatial Thoughts. Learn more.

See our other Course Offerings.

This course set the right path for me to start my journey with Remote Sensing. Working in the humanitarian sector in a country heavily affected by Climate Change, this course provided me with the basic and intermediate skills that I need to make a real impact.

Ahmad Fandy, REACH Initiatives, Iraq.

The lecture on the Google Earth Engine For Water Resources Management was fantastic to me. I gained a great deal of knowledge from both Ujaval Sir and Santhosh Da. I completed the course with a wide range of practical knowledge and skills. The course is well-structured, and the content is presented understandably. I wholeheartedly recommend this class to others.

Deb kumar Maity, West Bengal State University, India

Loved the sessions. The whole course was very well laid out and detailed. Even though I had a very less experience in this domain, I could grasp a good amount to knowledge delivered. Really appreciate the help and the Q&A sessions.

Shreyansh Vishwakarma, IGIDR Mumbai, India

I took this course after attempting to demystify and understand how Google Earth Engine works and take advantage on how to apply it in remote sensing data related to water resources. Excellent examples, a great structured program and plenty of experience are put to the service of the students. Every day, new material was received based on student’s interests and class discussion. Highly recommended. Thank you, Ujaval and Santhosh, for another great course!

Norman Avila, Climaya, Guatemala.

I was skeptical about taking this course initially as I had taken a similar course on GEE, but a friend urged me to take it. I was very surprised how much more knowledge Ujaval exposed me to. In the end, I did not only grab tips, tricks and more applicability especially workable workflows but also an in-depth understanding of GEE and even advanced features. I recommend this course to everybody, including experts in the Remote Sensing field.

John Dogbey, Deutsche Gesellschaft, Ghana