6 stories
Public health decisions rely heavily on timely, granular data. For health conditions, such as cardiovascular disease or postpartum depression, that data shows us where to focus resources and support.
Methane is a potent greenhouse gas; over a 100-year timeframe, its warming potential is 30 times greater than that of carbon dioxide. In fact, it has driven approximately 25% of human-induced warming since the start of the industrial era.
As part of Google Earth AI, we introduce the planetary prediction engine (PPE), an experimental research capability that autonomously executes the full geospatial modeling workflow — from data discovery to model training — achieving improvements across diverse prediction tasks in public health,…
We introduce a dynamic, mobility-informed framework that allows AI models to understand the temporal activity rhythms of places over time, and, in doing so, significantly improve predictions about real-world attributes like opening hours, price levels, and busyness.
We’re releasing an expanded dataset of building-level rooftop reflectivity covering 50+ global cities to help urban planners implement cool-roof solutions and mitigate extreme heat. This dataset is being made accessible through a new high-resolution Heat Resilience Earth Engine App.
We developed a high-resolution deep learning framework to reveal fine-scale ecological features, like hedgerows and copses, that are typically invisible to standard satellite detection.
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