MIT Scientists have developed a method to visualize potential impacts of a hurricane on people’s homes using realistic satellite images. The team applied the method to Houston, generating images that accurately depicted what certain locations would look like after a storm comparable to Hurricane Harvey.
MIT Scientists Develop Method to Visualize Potential Impacts of a Hurricane on People’s Homes
The researchers applied the method to Houston and generated satellite images depicting what certain locations around the city would look like after a storm comparable to Hurricane Harvey. They compared these generated images with actual satellite images taken of the same regions after Harvey hit.
Test Case: Houston and Hurricane Harvey
-
The team applied the method to Houston and generated satellite images depicting what certain locations around the city would look like after a storm comparable to Hurricane Harvey.
-
They compared these generated images with actual satellite images taken of the same regions after Harvey hit.
-
The team also compared AI-generated images that did not include a physics-based flood model.
Results
-
The team’s physics-reinforced method generated satellite images of future flooding that were more realistic and accurate.
-
The AI-only method, in contrast, generated images of flooding in places where flooding is not physically possible.
Methodology
The team’s method involves combining a generative artificial intelligence model with a physics-based flood model to create realistic, birds-eye-view images of a region. The AI model generates an image based on the input data, while the physics-based model ensures that the generated image is accurate and reflects the physical laws governing flooding.
Implications
The new method has significant implications for disaster preparedness and response. By generating satellite imagery from the future, the team’s method can help residents prepare and decide whether to evacuate before a storm hits. The method can also be used to visualize the potential impacts of a hurricane on people’s homes, helping them make informed decisions about their safety.
Availability
The team has made the new method available as an online resource for others to try. This will enable researchers and practitioners to explore the potential of this innovative approach and adapt it to other regions and applications.
Proof-of-Concept
-
The team’s method is a proof-of-concept, meant to demonstrate a case in which generative AI models can generate realistic, trustworthy content when paired with a physics-based model.
-
In order to apply the method to other regions to depict flooding from future storms, it will need to be trained on many more satellite images to learn how flooding would look in other regions.
Potential Applications
-
The idea is that one day, this could be used before a hurricane, providing an additional visualization layer for the public.
-
One of the biggest challenges is encouraging people to evacuate when they are at risk. Maybe this could be another visualization to help increase that readiness.
Online Resource
-
The team has made the new method available as an online resource for others to try.
-
The researchers report their results today in the journal IEEE TGRS.
