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Floods are the most common, severe, and damaging natural disasters that can last hours, days, or weeks. Given its location along the great African Rift Valley, Malawi is especially vulnerable to floods due to its geography and low economic development (Figure 1). About 80 percent of Malawi‘s population lives in an agrarian economy. From January to March 2019, severe floods affected nearly 1 million people and claimed 56 lives in Malawi. The floods were caused by tropical cyclone Idai from March 4 to March 21, one of the worst tropical cyclones on record, and heavy rains that followed. The floods damaged crops, contaminated water supplies that resulted in cholera outbreaks, displaced people, and destroyed schools.

In response to the floods, UNICEF provided aid to identify flooded districts. All assistance was done by providing tents to be used as temporary schools, ensuring that children will be able to continue their classes, providing food, and giving medical treatment. This recovery effort was due to UNICEF mapping specific flood areas with drones to help people understand the need in those areas. However, some flood areas may have been misidentified due to technical limitations of drones- personal needed to fly, battery power, and lack of available drones. This may have resulted in areas not receiving humanitarian aid.

The purpose of this project is to use the European Space Agency (ESA) Sentinel-1A/B synthetic aperture radar (SAR) satellite data to improve flood mapping and identification to better direct humanitarian aid in Malawi. Sentinel-1A/B images from before and after the flood events were used in change detection and classification analysis. Using Sentinel-1A/B classified maps and the UNICEF flood areas from drones, we had compared the two to verify the accuracy of the Sentinel-1A/B generated maps for flood identification. The implications for this project could help identify which areas in Malawi may have been affected by floods to improve the distribution of humanitarian aid for relief efforts.


This project is supported by the national science foundation research REU geoscience internship program (grant 1801563) under the direction of Dr. Reginald A. Blake, Dr. Janet Liou Mark, and Ms. Julia Rivera. Special thanks to Aaron Davitt.



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