Google’s submission showcases how its existing geospatial ecosystem—spanning products like Google Maps, Earth Engine, and Vertex AI—advances the goals of a modern Spatial Data Infrastructure (SDI). By promoting interoperability, AI-driven insights, open data partnerships, and scalable cloud-native tools, Google offers practical examples of how private sector innovation can enhance national and global SDI efforts. The proposal focuses on collaboration, intelligent systems, and open standards under the SDI themes of Data & Technology and People.

Key Features

• Public-Private Partnerships
  • Google Maps Content Partners (GMCP): Empowers governments to integrate authoritative data (e.g., roads, boundaries) into Google Maps.
  • Waze for Cities: Real-time, crowdsourced data from citizens used by local authorities to improve transportation and safety.
• Geospatial Reasoning with AI
  • Use of LLMs (like Gemini) to analyze and generate geospatial insights across datasets for climate, crisis response, and public health. Creation of agentic workflows for AI-powered geospatial problem-solving.

• Satellite Embedding Dataset
  • Deep learning-powered image embeddings in Earth Engine enable rapid classification, change detection, and similarity searches without extensive manual training.

• Open Standards and APIs
  • Expansion of Common Alerting Protocol (CAP) for multi-hazard alerting.
  • Use of OGC 3D Tiles for immersive visualization.
  • Google Places API provides persistent place identifiers to connect disparate datasets.

• Cloud-Native Platform Integration
  • Combines Earth Engine, BigQuery Geospatial, Google Maps, and Vertex AI into a unified analytics platform. Enables planetary-scale analysis, intelligent search, and automated workflows using petabytes of satellite imagery.

Benefits and Impact

• Authoritative Data at Scale
  • Through government collaboration, authoritative datasets reach hundreds of millions of users globally.
• Enhanced Mobility and Safety
  • Real-time data from Waze and USDOT integrations improve navigation and traffic management.
• AI-Driven Insights
  • Reduces human burden through automation and intelligent geospatial analytics.
• Data Interoperability
  • Persistent place IDs and open API standards promote seamless data sharing.
• Public-Private Collaboration
  • Models how tech companies and governments can co-develop modern SDIs with mutual benefits.
• Operational Readiness
  • Existing platforms and tools are already in use, providing immediate applicability and scalability.

Use Cases

• Urban navigation and infrastructure
• Disaster response
• Environmental monitoring
• Public service delivery
• Climate and health analytics