DeepAI AI Chat
Log In Sign Up

Physically-Consistent Generative Adversarial Networks for Coastal Flood Visualization

by   Björn Lütjens, et al.

As climate change increases the intensity of natural disasters, society needs better tools for adaptation. Floods, for example, are the most frequent natural disaster, and better tools for flood risk communication could increase the support for flood-resilient infrastructure development. Our work aims to enable more visual communication of large-scale climate impacts via visualizing the output of coastal flood models as satellite imagery. We propose the first deep learning pipeline to ensure physical-consistency in synthetic visual satellite imagery. We advanced a state-of-the-art GAN called pix2pixHD, such that it produces imagery that is physically-consistent with the output of an expert-validated storm surge model (NOAA SLOSH). By evaluating the imagery relative to physics-based flood maps, we find that our proposed framework outperforms baseline models in both physical-consistency and photorealism. We envision our work to be the first step towards a global visualization of how climate change shapes our landscape. Continuing on this path, we show that the proposed pipeline generalizes to visualize arctic sea ice melt. We also publish a dataset of over 25k labelled image-pairs to study image-to-image translation in Earth observation.


page 1

page 2

page 3

page 4

page 5

page 6

page 10

page 11


Physics-informed GANs for Coastal Flood Visualization

As climate change increases the intensity of natural disasters, society ...

Predicting Landscapes from Environmental Conditions Using Generative Networks

Landscapes are meaningful ecological units that strongly depend on the e...

Visualization techniques for data mining of Latur district satellite imagery

This study presents a new visualization tool for classification of satel...

Image-to-Height Domain Translation for Synthetic Aperture Sonar

Observations of seabed texture with synthetic aperture sonar are depende...

Seamless Satellite-image Synthesis

We introduce Seamless Satellite-image Synthesis (SSS), a novel neural ar...

Simulating cloud-aerosol interactions made by ship emissions

Satellite imagery can detect temporary cloud trails or ship tracks forme...

Machine Learning for Generalizable Prediction of Flood Susceptibility

Flooding is a destructive and dangerous hazard and climate change appear...