Gen AI creates accurate satellite images of flooding

Known as the ‘Earth Intelligence Engine’, the tool was developed as a visualisation aid to inform the public of the potential effects of impending storms. The MIT team has made the tool available online so that people can see its results in action. The work is published in the journal IEEE Transactions on Geoscience and Remote Sensing. 

“The idea is: One day, we could use this before a hurricane, where it provides an additional visualisation layer for the public,” said research lead Björn Lütjens, a postdoc in MIT’s Department of Earth, Atmospheric and Planetary Sciences.

“One of the biggest challenges is encouraging people to evacuate when they are at risk. Maybe this could be another visualisation to help increase that readiness.”

Initially, the researchers used AI on its own to create the synthetic images. They applied a generative adversarial network (GAN), a type of machine learning method that can generate realistic images using two competing neural networks. While this model produced realistic images, it also generated ‘hallucination’ floods at locations where flooding was not currently possible. 

“Hallucinations can mislead viewers,” said Lütjens. “We were thinking: How can we use these generative AI models in a climate-impact setting, where having trusted data sources is so important?” 

To overcome this issue, Lütjens and his colleagues reinforced the AI with segmentation maps of physics-based models that incorporate real, physical parameters such as an approaching hurricane’s trajectory, storm surge and flood patterns. The team was able to demonstrate that the physics-conditioned model outperformed the pure generative AI model.

“We show a tangible way to combine machine learning with physics for a use case that’s risk-sensitive, which requires us to analyse the complexity of Earth’s systems and project future actions and possible scenarios to keep people out of harm’s way,” said study co-author Dava Newman, Professor of AeroAstro and director of the MIT Media Lab.

“We can’t wait to get our generative AI tools into the hands of decision-makers at the local community level, which could make a significant difference and perhaps save lives.”