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IBM and ESA open-source AI models trained on a new dataset for analyzing extreme floods and wildfires

Press Release by IBM: “Record-setting wildfires across Bolivia last year scorched an area the size of Greece, displacing thousands of people and leading to widespread loss of crops and livestock. The cause of the fires was attributed to land clearing, pasture burning, and a severe drought during what was Earth’s warmest year on record.

The Bolivia wildfires are just one, among hundreds, of extreme flood and wildfire events captured in a new global, multi-modal dataset called ImpactMesh, open-sourced this week by IBM Research in Europe and the European Space Agency (ESA). The dataset is also multi-temporal, meaning it features before-and-after snapshots of flooded or fire-scorched areas. The footage was captured by the Copernicus Sentinel-1 and Sentinel-2 Earth-orbiting satellites over the last decade.

To provide a clearer picture of landscape-level changes, each of the extreme events in the dataset is represented by three types of observations — optical images, radar images, and an elevation map of the impacted area. When storm clouds and smoky fires block optical sensors from seeing the extent of flood and wildfires from space, radar images and the altitude of the terrain can help to reveal the severity of what just happened…(More)”.

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