Simulating urban greening before anyone picks up a shovel

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Added by Martin on 2026-01-12 21:05

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As cities get hotter, planners need good temperature data to figure out where to focus their cooling efforts. But there’s a bit of a problem. Traditional machine learning models need tons of local data to make accurate predictions, and that data often doesn’t exist for the cities that need it most. A new study from IBM Research tests whether geospatial foundation models (GFMs) can fill this gap.

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Simulating urban greening before anyone picks up a shovel As cities get hotter, planners need good temperature data to figure out where to focus their cooling efforts. But there’s a bit of a problem. Traditional machine learning models need tons of local data to make accurate predictions, and that data often doesn’t exist for the cities that need it most. A new study from IBM Research tests whether geospatial foundation models (GFMs) can fill this gap.