tool· draft
Google Earth AI Geospatial Reasoning agent
Experimental Gemini-based agent from Google Research that plans a multi-step spatial analysis, calls Earth AI models and geospatial data sources, and returns the result with its plan and sources shown.
Cities & placesPeople & societyWeather & climateEnergy
The Geospatial Reasoning agent is the orchestrating part of Google Earth AI, built by Google Research on Gemini. Given a question in plain language it drafts a step-by-step plan, then calls a set of modular skills that wrap Earth AI models (WeatherNext, flood forecasting, the Population Dynamics Foundation Model, AlphaEarth Foundations, Remote Sensing Foundations) and data sources such as Earth Engine, Data Commons and BigQuery public datasets, and combines what comes back. Answers show the plan and the data used so a specialist can check them. Users can add their own data as CSV files, GeoJSON boundaries or cloud tables. A companion piece, the Planetary Prediction Engine, takes a user's local outcome data and trains predictive models for spatial prediction, downscaling and forecasting.
Google's October 2026 account gives several uses. During the 2026 Ebola outbreak in the Democratic Republic of the Congo, WHO AFRO used the agent to map mining corridors with high exposure and mobility risk, finding 48 exposed settlements and more than 45,500 people at risk; the INRB used the Planetary Prediction Engine for weekly estimates of spread into uninfected health zones. People in Need analysed 14 historical cyclone tracks to find high-exposure villages. GiveDirectly uploaded its own boundaries to estimate population exposure by wind-speed zone during Tropical Cyclone Maila and to benchmark tornado damage in Mississippi. The Milken Institute screened over 1,500 candidate buildings for community resilience hubs.
It runs as a hosted Google service. Access in October 2026 is by limited early-access programme through three tracks: Ask Google Earth, an experimental headless Agent-to-Agent API for developers building their own workflows, and the Planetary Prediction Engine. Applicants express interest through a form on the Geospatial Reasoning page. Pricing and terms are not stated.
Status: experimental. A prototype was introduced with Earth AI in October 2025. A technical report (arXiv 2610.15750, submitted 11 October 2026) compares four configurations on Gemini 3.1 Pro and 3.8 Flash and introduces two benchmarks, GeoExpertQueries and GeoKTools, whose development sets are released on GitHub; the authors describe the agent's output on open-ended problems as a first draft for expert review.
- homepage
- https://sites.research.google/gr/geospatial-reasoning/
- form
- experimental agent
is a part of this larger thing
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Google's family of geospatial AI models and agents, covering satellite imagery, weather, floods and population, reached through Google Earth, Earth Engine, BigQuery, Maps Platform and Google Cloud.
uses this engine, platform or technique
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Weather prediction and supporting components, with different distribution and developer options.
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Geospatial representations and foundation models for downstream mapping tasks.
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Google Research geospatial foundation model that turns aggregated search trends, place busyness, maps, weather and air quality into an embedding vector per postal code or county, for predicting local health, economic and environmental indicators.
discussed in
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Benchmark from Google Research of open-ended GIS analysis problems written and cross-checked by geospatial experts, used to test how well an AI agent plans an expert-level spatial analysis.
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Benchmark from Google Research of generated geospatial queries with known answers that require chaining one to four kinds of geospatial tool; used to test an AI agent's multi-step tool use and exact spatial computation.
Tags: geospatial, agent, gemini, satellite, analysis, gis