Interdisciplinary Project SS2025: Techniques for Dynamic Visualization of Time-Varying Flood Data

Supervisors: Thais Beham, Martin Schobben

Students: Jakob Nicko, Jonas Schindler, Adam Domoslawski

Project Goal

Propose new ways and improvements for visualizing time-dependent flood data. We will work with the Global Flood Monitoring dataset.

Research questions:

• How to combine flood likehood and flood extention in one visualization?
• How to visualize the flood uncertainty?
• How to better visuliaze dynamic flood events to facilitate decision-makers to promptly take actions based on the results?
• How to optimize performance to allow real-time analysis?

Use cases

• Nothern Germany (as shown in the jupyter notebook)
• Pakistan 2022 (https://repositum.tuwien.at/handle/20.500.12708/189403)
• Greece 2018 (https://www.mdpi.com/2072-4292/14/15/3673)

Important links

• Paper explaining how the flood was calculated based on the satelite images: Satellite-Based Flood Mapping through Bayesian Inference from a Sentinel-1 SAR Datacube. https://doi.org/10.3390/rs14153673.
• Metadata: https://services.eodc.eu/browser/#/v1/collections/GFM
• https://extwiki.eodc.eu/en/GFM
• https://ieeexplore.ieee.org/document/10186373/
• https://ieeexplore.ieee.org/document/9554214/