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STAC Overflow: Map Floodwater from Radar Imagery
Help Microsoft AI for Earth and Cloud to Street detect floodwater through cloud coverage using Sentinel-1 synthetic-aperture radar (SAR) imagery. Accurate flood mapping can save lives by strengthening early warning systems and directing emergency relief. #disasters
Wind-dependent Variables: Predict Wind Speeds of Tropical Storms
Throughout a tropical cyclone, humanitarian response efforts hinge on accurate storm intensity estimates. Using satellite images assembled by Radiant Earth Foundation and the NASA IMPACT team, can you estimate the wind speeds of storms at different times? #disasters
Open Cities AI Challenge: Segmenting Buildings for Disaster Resilience
Can you map building footprints from drone imagery? This semantic segmentation challenge leverages computer vision and data from OpenStreetMap to support disaster risk management efforts in cities across Africa. #disasters
Open AI Caribbean Challenge: Mapping Disaster Risk from Aerial Imagery
Can you predict the roof material of buildings from drone imagery? Leverage aerial imagery in St. Lucia, Guatemala, and Colombia to more accurately map disaster risk at scale. #disasters
Richter's Predictor: Modeling Earthquake Damage
Can you predict the level of damage to buildings caused by the 2015 Gorkha earthquake in Nepal based on aspects of building location and construction? #disasters