SAR is independent of weather and day or nighttime conditions; its signal can penetrate solid objects and measure millimeter-scale land deformations. But unlike optical data, SAR is difficult to use. It needs a lot of preprocessing under various different parameters, and deep learning SAR models don’t work reliably in novel regions.

With this challenge, the SAR team developed a flexible machine learning pipeline to leverage the wealth of information contained in different SAR input imagery. They also fine tuned these pre-trained models on a variety of labeled downstream tasks. This included dealing with complex and missing data, generalizing across time and space domains, and developing tooling to facilitate easy analysis and compelling visualizations.

You can read more about our FDL-X 2023 teams and research challenges here and about our FDL Europe 2023 teams and research challenges here.

Extracting the direction and density of coronal mass ejections (CMEs) is crucial for predicting their impact. The upcoming ESA VIGIL mission will provide a much needed additional viewpoint to allow triangulation and 3D construction of CMEs — and the ability to do so onboard can save valuable time. The SSA Live Twin for Space Weather team was up for the challenge and developed a machine learning pipeline that could analyze data both onboard the spacecraft and from Earth observatories, significantly reducing downlink bandwidth requirements and alert latency.

Climate change is already causing more frequent and extreme weather events; floods are some of the most prevalent and dangerous. Disaster reports are needed to make better flood relief decisions and resilience plans, but disaster reporting is not an easy task.

The FM Adaptors for Disasters team combined Earth Observation (EO), flood prediction models, flood-mapping tools, human-in-the-loop, and weather monitoring systems with LLMs to create an NLP agent that can create accurate and tailored flood reports that can be used to assess disaster impact across the globe. Check out their work at floodbrain.com (password: floodbrain).