Flooding is one of the most devastating natural disasters affecting millions of people globally each year. Rapid, accurate, and large-scale flood monitoring is essential for disaster management, emergency response, and long-term planning. This course teaches you how to use radar remote sensing—specifically Sentinel-1 SAR (Synthetic Aperture Radar)—in combination with Google Earth Engine (GEE) to map and analyze flood events with high precision.
You will start by understanding the basics of radar backscatter and why SAR is uniquely suited for flood detection, even under cloud cover. You’ll learn how to access and preprocess Sentinel-1 SAR data in GEE, apply filters, and create temporal composites. The course will guide you through flood mapping workflows by comparing pre-flood and flood-stage VV images and calculating backscatter differences to generate flood masks.
Key concepts include threshold-based flood detection, data visualization, and exporting results for integration with GIS or hydrological models. You’ll also explore how to adjust detection thresholds for different regions and surface types to enhance mapping accuracy.
Whether you’re a remote sensing student, disaster response analyst, or environmental professional, this hands-on course provides all the tools needed to monitor flooding using free, open-access satellite data and a powerful cloud platform. By the end of the course, you will have built a complete workflow to detect, visualize, and export flood maps using Sentinel-1 SAR in Google Earth Engine.
- Students, researchers and professionals in agriculture, environmental science, geography, or remote sensing looking to apply satellite data in real-world scenarios.
