This course provides a comprehensive introduction to flood mapping using Landsat satellite imagery and Google Earth Engine (GEE). Starting with the fundamentals of remote sensing, you’ll learn how satellites capture Earth’s surface data using various electromagnetic wavelengths and understand essential concepts like spatial, spectral, temporal, and radiometric resolution. You’ll explore why remote sensing is vital for environmental monitoring, especially in flood-prone areas like Bangladesh.
Next, the course highlights the critical importance of flood monitoring, showing how satellite technology enhances traditional methods by providing timely, large-scale flood detection and analysis. You will discover key water indices, such as the Normalized Difference Water Index (NDWI), which help differentiate flooded areas from dry land.
A major focus will be on Google Earth Engine, a cloud-based platform that allows you to access, process, and analyze vast archives of satellite data without needing local software. You’ll learn to navigate the GEE interface, load and filter Landsat imagery, and write scripts for data manipulation.
The course then dives into Landsat spectral bands, explaining how specific bands are used to calculate NDWI for detecting water bodies. You’ll gain hands-on experience calculating NDWI and understanding spectral resolution to improve accuracy.
Finally, you’ll apply all these skills in GEE by building a complete flood mapping workflow: selecting an area of interest, filtering data by date and cloud cover, computing NDWI for pre- and post-flood periods, and generating flood masks. This practical knowledge will empower you to monitor floods efficiently using satellite data and cloud computing tools.
- Students, researchers and professionals in agriculture, environmental science, geography, or remote sensing looking to apply satellite data in real-world scenarios.
