Key Features

Unites decades of state-of-the-art geospatial models with Gemini's reasoning.
Provides actionable intelligence for planetary-scale challenges.
Supports complex natural language queries about the physical world.
Powers features across Google Search, Maps, and Google Cloud platforms.
Integrates high-fidelity data from Google Maps for native grounding in applications.
Features specialized Imagery models for object detection and scene classification on satellite data.
Offers advanced environmental insights including flood forecasting and high-resolution weather predictions.
Enables advanced population dynamics analysis to understand human behavior and environmental interplay.

The core strength of Earth AI lies in its ability to derive immediate, tangible answers from vast datasets, moving beyond simple data visualization to provide true intelligence. For instance, users can pose complex natural language queries about specific geographical features, risks, or similarities between global locations, and receive grounded, precise results derived from years of curated Earth observation data. This functionality is seamlessly integrated across major Google platforms, including Google Earth, Google Maps Platform, and the Vertex AI platform within Google Cloud, ensuring that actionable, location-aware intelligence is accessible wherever critical decisions are being made.


Beyond direct user interaction, the underlying Earth AI models are actively powering numerous features relied upon by billions daily, demonstrating its practical impact at a massive scale. This includes enhancements to weather forecasting, such as providing highly accurate, localized flood warnings and improved tropical cyclone predictions, as well as informing public safety through real-time air quality monitoring. Furthermore, the technology is being utilized to create foundational datasets, like the Open Buildings project, which maps global infrastructure with unprecedented detail, allowing for accelerated scientific discovery and more resilient urban planning.

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