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Roads Management Insights

Use Google's road data to help make proactive, data-driven decisions that improve road network safety and efficiency while enabling rapid, scalable deployment.

Drive proactive, data-driven decisions for road networks

Access rich, comprehensive road data with near real-time traffic in over 200 countries and territories. Comprehensive road network data including road geometries and priorities constitutes an operational layer for roads management infrastructure analysis and driving operational efficiencies.

Achieve rapid deployment & scalability

Go live across your network in weeks, not years. Effortlessly scale data collection from a single corridor to an entire jurisdiction without any hardware. You can also instantly remove the capital expenses and ongoing maintenance burden of physical infrastructure like cameras, sensors, and roadside hardware.

Improve safety and efficiency

Analyze live data to instantly identify unusual patterns and abnormalities that may signal an incident or disruption and inform decisions on the next steps. Collect useful data like hard braking events and vehicle plans to improve planning.

Put Roads Management Insights to work

Manage traffic intelligently

Analyze traffic patterns to isolate your recurring congestion hotspots and most inefficient corridors. Target improvements and build models cost-effectively, improving conditions in the future.

Improve planning and investment

Gain a complete picture of live traffic conditions with up-to-the-minute information on flow, speed, and congestion. Instantly identify unusual patterns and anomalies for traffic managers to respond.

Places Insights

Derive custom statistical insights by securely joining your data with Google's comprehensive Places dataset in BigQuery to uncover real-world insights for use cases like site selection, market research, and location performance evaluation.

Unlock flexible analysis

Write custom SQL queries in BigQuery that are tailored to your specific business need, using over 70 distinct place attributes. Use familiar tools by bringing statistical analysis of Google’s data directly in your existing BQ environment, and take advantage of tools like BigQuery ML, Gemini Enterprise Agent Platform and Looker.

Access Google’s comprehensive and fresh Places data

Analyze over 300 place types and 70 attributes, including ratings, price level, hours, parking, and wheelchair accessibility, to understand the nuanced characteristics of any location. Gain a competitive edge using Google's fresh and comprehensive dataset of over 300 million places worldwide.

Make confident, data-driven decisions securely

Safely combine your proprietary data with Google's Places data in BigQuery, allowing you to run analysis without ever exposing sensitive information. Move from anecdotal evidence to a data-driven approach, enabling you to build statistical models that predict performance and drive business growth.

Put Places Insights to work

Make smarter site selections

Use current and historic data to choose optimal locations for new facilities, businesses, or assets. Identify key drivers of success from existing locations to prioritize prospect sites.

Understand why certain physical locations perform

Analyze factors like average ratings and reviews, proximity to other businesses, and other geographic characteristics.

Population Dynamics Insights

Turn search trends, mobility, and environmental data into secure ML-ready embeddings to instantly predict location performance, fill data gaps, and model human behavior.

Make better predictions with pre-trained human dynamics

Understand human behavior and the physical landscape to capture why certain locations thrive. Leverage these underlying patterns to replicate success in new regions and sharpen your forecasts.

Use universal, geospatial data in your spatial models

Eliminate the overhead of normalizing, aligning, and aggregating raw geospatial signals. Get privacy preservation and aggregation that give you vectors ready for your machine learning models.

Overcome data gaps and blind spots

Access ML-ready embeddings that are globally standardized and comparable, enabling your organization to apply insights from a known market to new, unanalyzed regions. Work with a consistent feature set available for 17+ countries.

Street View Insights

Tap into Google Street View’s vast repository of over 280 billion 360° and 3D images covering infrastructure across 110+ countries. Reduce costly, time-consuming field surveys and gain actionable infrastructure insights right from your desk.

Eliminate the need for field surveys

Extract actionable insights much faster than before, reducing the need for costly and time-consuming field surveys. Using natural language queries to Gemini allows you to reduce the expertise required to evaluate infrastructure.

Automate asset management

Combine rich imagery and LiDAR precision to remotely measure assets like never before. Validate project design ideas before conducting expensive site visits to improve project preparation and efficiency.

Shift maintenance from reactive to proactive

Get accurate, timely data and AI-powered analysis to help you anticipate infrastructure issues before they become critical, leading to significant cost savings and enhanced safety and sustainability of infrastructure networks.

Put Street View Insights to work

Manage inventory assets deployed in the wild

Accurately inventory distributed assets, such as utility poles and road signs. Then find the accurate locations, sub-classify the equipment, and update your inventory.

Streamline infrastructure maintenance

By automating identification and condition assessments, transportation departments can yield significant cost savings while enhancing the safety and sustainability of the road network.

Aerial & Satellite Insights

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

Make optimal site selections

Augment your site selection data with high-resolution aerial imagery to efficiently enable broad and deep site selection analysis. The richer but more efficient methodology enables more comprehensive considerations.

Track your asset inventory

Conduct comprehensive inventory audits of your properties and catalog their key surrounding attributes with advanced vision models. Compare against previous insights and historical imagery to detect changes and predict patterns.

Conduct preliminary risk assessments

Analyze commercial properties for underwriting risks related to natural and built environment factors - for example, proximity to combustible vegetation and roof conditions, respectively.

Aerial and Satellite Models

Securely license stand-alone models to build custom applications on any overhead imagery source, using zero-shot detection and natural language queries within your private cloud.

Apply Google-quality intelligence to your pixels

Bring and ingest imagery from any provider and run our models to extract value. This allows you to unify analysis across multi-satellite constellations and process private data that never leaves your control. Build unique, differentiated intellectual property and applications within your own secure cloud environment.

Build and commercialize unique solutions

Use pre-built models to build differentiated solutions and power your own downstream applications, from roadway maintenance platforms to global agricultural intelligence tools. Provide a unique user interface and business logic to your end customers.

Achieve state-of-the-art performance with less data

Find specific objects in your own or Google’s satellite and aerial imagery simply by describing them. Use it on your own data to build tools that locate anything using just text, without needing to train the AI beforehand. Find similar images, detect changes, or identify objects using natural language queries instead of complex code.
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Get more value from your data

Securely integrate your data and Google’s geospatial datasets into BigQuery, a fully managed, AI-ready data analytics platform. It’s designed to be multi-engine, multi-format, and multi-cloud.

Extract valuable location insights

Seamlessly integrate analysis-ready imagery and datasets into your existing BigQuery workflows using data clean rooms.

Achieve actionable answers

Harness the power of the Cloud ecosystem such as BigQuery ML, Vertex AI, and Looker Studio.

Power your geospatial analytics needs with Google

Explore data covering 250+ countries and territories

Unlock planetary-scale analysis with Earth Engine’s multi-petabyte catalog of satellite imagery and geospatial datasets.

280B+

Street View images of 100+ countries1

1,000+

earth observation datasets

300M+

POI data that covers 300M+ businesses and places1

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Get more value from your data

Securely integrate your data with Google’s datasets in BigQuery, an AI-ready analytics platform designed to be multi-engine, multi-format, and multi-cloud.

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Unleash the power of generative AI

Combine Google Earth AI's models, datasets and reasoning agents with structured and unstructured data for an entirely new class of analytical applications.

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Save time with no-code geospatial tools

Integrate iconic imagery with professional-grade geospatial data, no-code tools, and Gemini to make better, faster decisions.

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Datasets & Models

Combine unmatched geospatial data with the power of Earth AI to unlock valuable insights

Imagery

Earth AI transforms diverse imagery into actionable intelligence, helping you automate asset management, monitor environmental changes, and shift to proactive maintenance.

Population

Get the bigger picture of populations and places by using Earth AI to combine search trends, demographics, business mobility, and geospatial data.

Google Earth AI

Query the planet

Built on years of modeling the world and the power of Gemini, Google Earth AI is helping organizations of all kinds with everything from environmental monitoring to disaster response.

"Google is the founder of much of the geospatial cloud-base ecosystem and shares Perennial’s mission of using advanced technologies and artificial intelligence to increase sustainability and climate resilience globally. Since migrating to Google Cloud and Earth Engine, our AI model iteration speed is 10 times faster, the volume of data per iteration is 10 times larger, and the geographic footprint our data covers is five times bigger."
David Schurman
Perennial Co-founder and Chief Product Officer
"Thanks to RMI, we can now enable our road authority customers with a clearer, more complete picture of their road network than ever before. RMI provides timely and actionable data, and together with our TraceMark Flow tool, we can provide customized traffic intelligence with coverage and accuracy not seen before. Ultimately this improves road safety and network efficiency for our customers and their citizens."
Oliver Looker
General Manager at NGIS
"Knowing where critical assets such as healthcare facilities or educational buildings are spatially distributed is essential for planning and responding to disasters. Places Insights is a game changer for organizations like the Global Earthquake Model Foundation that has the remit to calculate and communicate earthquake risk."
Vitor Silva
Global Earthquake Model Foundation
"The combination of Vantor’s spatial foundation and Google’s Aerial and Satellite Models is creating a new class of geospatial intelligence systems that can interpret activity across the planet, surface meaningful signals, and deliver insights directly into operational workflows. In demonstrations with customers, where we’ve integrated models into our persistent monitoring application called Sentry, the level of insight has been remarkable."
Peter Wilczynski
Chief Product Officer, Vantor
"We are leveraging Roads Management Insights, accessed through Google Cloud’s BigQuery environment, together with Google Cloud’s advanced analytics and AI capabilities. This combination allows us to analyze traffic patterns, detect anomalies, and develop predictive models with the scalability and robustness required for real operational use cases."
Antonio Durán
Abertis Global Innovation Head
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Frequently asked questions

No, Google Earth AI is a Google-wide program representing a family of geospatial AI models and reasoning agents. Google Earth is a no-code geospatial analytics platform and one of several products through which Google Earth AI capabilities are available. Learn more about Google Earth AI here.

No, to gain access to these datasets, you’ll need to purchase a separate subscription from Google Maps Platform (sign up here).

All of these Insights datasets are available to purchase for use in BigQuery.

Embeddings in geospatial data are compact, numerical vector representations of complex, high-dimensional, and multi-temporal geographic information. They translate raw data—such as satellite imagery, GPS trajectories, and text—into a format that machine learning models can understand. Population Dynamics Insights embeddings can be accessed here.

Yes, these datasets can be combined for analytical workflows in BigQuery. Read our documentation to learn more.

Yes, you can combine your proprietary data with these datasets, all under the control of your GCP environment. Read our documentation to learn more.

Yes, these datasets can be used in Gemini Enterprise Agent Platform for model training, fine-tuning and inference. For the specific datasets special service terms, read our documentation to learn more.

These datasets are in an analytics-friendly scale, format, and commercial structures. The APIs do not allow analytics use cases.

These datasets are sold as annual subscriptions, billed monthly. Sign up to learn more.

No, Google Earth AI is a Google-wide program representing a family of geospatial AI models and reasoning agents. Google Earth is a no-code geospatial analytics platform and one of several products through which Google Earth AI capabilities are available. Learn more about Google Earth AI here.

Yes, you can combine your proprietary data with these datasets, all under the control of your GCP environment. Read our documentation to learn more.

No, to gain access to these datasets, you’ll need to purchase a separate subscription from Google Maps Platform (sign up here).

Yes, these datasets can be used in Gemini Enterprise Agent Platform for model training, fine-tuning and inference. For the specific datasets special service terms, read our documentation to learn more.

All of these Insights datasets are available to purchase for use in BigQuery.

These datasets are in an analytics-friendly scale, format, and commercial structures. The APIs do not allow analytics use cases.

Embeddings in geospatial data are compact, numerical vector representations of complex, high-dimensional, and multi-temporal geographic information. They translate raw data—such as satellite imagery, GPS trajectories, and text—into a format that machine learning models can understand. Population Dynamics Insights embeddings can be accessed here.

These datasets are sold as annual subscriptions, billed monthly. Sign up to learn more.

Yes, these datasets can be combined for analytical workflows in BigQuery. Read our documentation to learn more.

  • 1 Street View has captured over 280 billion images of every single continent and over 100 countries. Imagery Insights uses Street View imagery and will launch initially in fewer countries.

  • Product availability, functionality and terms may differ for customers with billing addresses in the European Economic Area (EEA). Learn more

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