AI-Powered Thermal Earth Observation: Advancing Wildfire Detection and Risk Prediction from Ground to Orbit

Spotlight: Pi School of AI Alumni Success Stories

Tech talk with Johanna Strebl

Join us for a tech talk with Johanna Strebl, a former Pi School of AI Fellow who has turned her passion for wildfire prediction into a meaningful career. At the Pi School, Johanna worked with the National Observatory of Athens and ESA on AI-driven solutions for wildfire prediction. Now, as a data scientist at OroraTech, she is applying AI to detect and predict wildfires from space. Johanna will share insights from her journey and explore how technology shapes the future of wildfire management.
Reserve your spot here for this talk.

Abstract

As mega-fires become more frequent and severe, the need for advanced technology to manage these disasters is more urgent than ever. At OroraTech, Johanna and her team are using AI to turn thermal infrared data into powerful tools for wildfire detection and disaster preparedness.

In this talk, she’ll explore how OroraTech’s FOREST satellites are using machine learning to detect wildfires from space, providing early warnings critical for rapid response. They’re also improving the resolution of thermal imagery with multi-spectral super-resolution, providing a clearer, more detailed view of fire activity.

But detecting fires is just the beginning. You’ll also hear about their innovative approach to predicting wildfire risk by incorporating local conditions in high-risk areas such as Australia, Brazil and Greece, enabling better preparedness strategies.

They will also explain how their fire spread product, which uses AI to optimise fuel parameters, makes their models more accurate and reflective of real-world conditions. These models predict how fires will evolve over the next 12 hours, providing critical information for emergency response teams.

Join us to learn how AI is changing the way we detect, prepare for and respond to wildfires, ultimately helping to protect lives and ecosystems on a global scale.

Bio

Johanna Strebl is a data scientist at OroraTech, where she applies AI and thermal infrared data to address environmental challenges, particularly wildfire detection and risk prediction for disaster preparedness and response, helping protect communities and ecosystems through advanced technology.

She completed her MSc thesis on wildfire hazard modelling using remote sensing data. In 2023, she was a fellow at the Pi School of AI and gained experience in Explainable AI by participating in the Advancing Wildfire Forecasting using Explainable AI challenge with the National Observatory of Athens.

Her career includes roles at Infineon, Munich RE, and Reply, where she developed expertise in cloud migration, data science and machine learning.

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