Disaster response posts
Explore the latest in our mission to build a better world using data science and AI.
Content list
Meet the winners of STAC Overflow: Map Floodwater from Radar Imagery Challenge
Meet the winners who were best able to detect floodwater using synthetic-aperture radar (SAR) imagery! These winners developed solutions that can help to strengthen early warning systems and direct emergency relief.
How to Map Floodwater from Radar Imagery using Semantic Segmentation - Benchmark
We'll show you how to tune a U-Net model to measure flood extent using Sentinel-1 synthetic-aperture radar imagery.
Meet the winners of Wind-dependent Variables: Predict Wind Speeds of Tropical Storms
Meet the winners who were best able to estimate the wind speeds of tropical storms at different points in time using satellite images.
How to Use Deep Learning to Predict Tropical Storm Wind Speeds - Benchmark
We'll show you how to start predicting wind speeds for our latest disaster preparedness challenge.
Meet the winners of the Open Cities AI Challenge
Meet the winners with the best building segmentation models and ethical perspectives for disaster risk management
Meet the winners of the Open AI Caribbean Challenge
Meet the winners who were best able to map disaster risk from aerial imagery!
Segmenting Buildings for Disaster Resilience - Benchmark
We'll show you how to start detecting building outlines for our latest disaster resilience challenge.
Mapping Disaster Risk from Aerial Imagery - Benchmark
In this post we'll show you how to start working with aerial imagery to classify the roof material of buildings in St. Lucia, Guatemala, and Colombia.
Richter's Predictor - Benchmark
In this post we'll show you how to start using data science to predict the extent of earthquake damage!
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