# Building Damage Assessment

Page: https://stenobird.com/podcast/satellite-image-deep-learning-5989248/building-damage-assessment
Text version: https://stenobird.com/podcast/satellite-image-deep-learning-5989248/building-damage-assessment.md
Podcast: [Satellite image deep learning](https://stenobird.com/podcast/satellite-image-deep-learning-5989248)
Published: 2025-01-08T08:33:57+00:00
Episode link: https://www.satellite-image-deep-learning.com/p/building-damage-assessment
Audio file: https://api.substack.com/feed/podcast/153847809/f0188af0c8c4502543e88e7a0576c945.mp3
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JSON: https://stenobird.com/v1/public/podcasts/satellite-image-deep-learning-5989248/episodes/building-damage-assessment
Duration seconds: 1030

## Resource

In this episode, I caught up with Caleb Robinson to learn about the building damage assessment toolkit from the Microsoft AI for Good lab. This toolkit enables first responders to carry out an end-to-end workflow for assessing damage to buildings after natural disasters using post-disaster satellite imagery. It includes tools for annotating imagery, fine-tuning deep learning models, and visualizing model predictions on a map. Caleb shared an example where an organisation was able to train a useful model with just 100 annotations and complete the entire workflow in half a day. I believe this represents a significant new capability, enabling more rapid response in times of crisis. * 📺 Video of this conversation on YouTube * 👤 Caleb on LinkedIn * 🖥️ The toolkit on Github Bio: Caleb is a Research Scientist in the Microsoft AI for Good Research Lab. His work focuses on tackling large scale problems at the intersection of remote sensing and machine learning/computer vision. Some of the projects he works on include: estimating land cover, poultry barns, solar panels, and cows from high-resolution satellite imagery. Caleb is interested in research topics that facilitate using remotely sensed imagery more effectively. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.satellite-image-deep-learning.com

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## Transcript

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