Floods are among the most destructive natural disasters globally, causing significant damage to lives, infrastructure, and economies. Effective flood risk mapping is critical for disaster preparedness, mitigation, and urban planning. This comprehensive course on Flood Risk Mapping Using Remote Sensing and Google Earth Engine equips learners with the knowledge and tools to analyze flood hazards using satellite data and cloud-based geospatial processing.
Starting with an introduction to the fundamentals of remote sensing, students will explore various satellite sensors and data types essential for flood analysis, including Digital Elevation Models (DEMs) and rainfall datasets. The course then delves into risk mapping principles, teaching how to combine multiple environmental factors such as elevation and precipitation to assess flood vulnerability.
A significant portion of the course focuses on Google Earth Engine (GEE), a powerful cloud platform for geospatial data analysis. Students will learn to use GEE’s coding environment, access diverse datasets, and perform data normalization and combination to generate flood risk indices.
The final module offers hands-on experience implementing flood risk mapping in GEE, covering data acquisition, preprocessing, risk score calculation, classification, and visualization. Learners will understand how to interpret and export their results for practical applications.
By completing this course, students will gain the skills to create reliable flood risk maps, enabling better decision-making for emergency response, urban planning, and resource management. This course is ideal for environmental scientists, GIS professionals, urban planners, and anyone interested in geospatial risk assessment and disaster management.
- Students, researchers and professionals in agriculture, environmental science, geography, or remote sensing looking to apply satellite data in real-world scenarios.
