Robust geospatial datasets with integrated BigQuery capabilities that empower you to unlock business and sustainability insights, without remote sensing or GIS expertise.

Leverage Google's comprehensive road data to empower local authorities, utility providers, logistics and roadside assistance companies to build safer, more efficient networks. By eliminating hardware costs and providing near real-time visibility, RMI enables rapid deployment across entire jurisdictions. New capabilities like vehicle counts and real-time disruptions data provide even deeper signals to identify safety risks and drive proactive operational efficiencies.

Securely integrate proprietary datasets with the scale of the Google Maps rich Points of Interest (POI) data using Places Insights in BigQuery. Access analysis-ready granular attributes such as place types, ratings, store hours, and wheelchair accessibility to power use cases like site selection, market research, and location performance evaluation. Utilize pre-computed POI counts to bypass complex feature engineering or instantly generate custom location scores. Analyze historical monthly trends to track how business landscapes and neighborhood characteristics evolve, turning location data into strategic action.

Skip the data engineering bottlenecks and move straight to modeling. Access pre-computed “digital fingerprints” that integrate Google Search trends, mobility, and environmental data into rich, privacy-preserving embeddings designed for immediate use. Leverage these differentiated signals to predict performance, fill critical data gaps, and model human behavior globally, Drive faster, data-driven decisions with unprecedented precision and zero feature engineering.

Transform your operational model, workflows, and decision-making with large-scale remote sensing and AI-powered insights from our imagery. Use image analysis to automate asset identification and simplify complex planning processes. Gain visibility from design to maintenance, using a 3D digital twin integrated with your GIS systems. Control costs and meet operational demands of scaled distributed infrastructure assets.

Access global high-resolution overhead imagery to enhance your analysis and decision-making. Utilize Gemini and advanced AI vision models to scale operations while reducing in-the-field presence, risk, and costs. Combine with your data in the Google Earth Engine for planetary-scale geospatial analysis.

Apply Google’s state-of-the-art geospatial AI to your own proprietary imagery. Securely license our Aerial and Satellite Models to build custom applications on any overhead imagery source, leveraging zero-shot detection and natural language queries within your private cloud. This allows you to automate large-scale analysis, accelerate time-to-market, and derive high-confidence insights while maintaining total data sovereignty.

Enrich your geospatial data in BigQuery with Earth Engine's deep collection of data about the world, all from within BigQuery Studio. Analyze and visualize earth data at scale to quickly access insights and build powerful solutions for a more sustainable future. Run custom machine learning models using the capabilities of Gemini Enterprise Agent Platform and the 90+ petabytes of data in Earth Engine’s data catalog.

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Helps you understand Google Cloud geospatial capabilities and how you can use these capabilities in your geospatial analytics applications. This document is intended for geographic information systems (GIS) professionals, data scientists, and application developers who want to learn how to use the products and services available in Google Cloud to deliver geospatial insights to business stakeholders.

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Find tutorials, JavaScript and Python guides, API References, connect with the Earth Engine developer community, and more.

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All the information you need to bring the real world to your web and mobile apps with Google Maps Platform SDKs and APIs for Maps, Routes, and Places.

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