Geonova

A New Intelligence, for the Earth.

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Inspiration

Urban planning decisions affect millions of people, yet they're often made without comprehensive spatial analysis or consideration of global best practices. We envisioned a platform that democratizes advanced urban planning by combining interactive 3D geospatial visualization, real-time environmental data, AI-powered analysis, and comparative urban intelligence to enable better decision-making for city planners, developers, and policymakers worldwide.

What It Does

Geonova is an AI-powered urban planning platform that transforms how cities are analyzed and planned. Users can search for any location on Earth, instantly visualizing it in stunning 3D detail with terrain, buildings, and real-time environmental metrics. The system performs comprehensive spatial analysis to understand density patterns, connectivity, green coverage, and zoning distribution, then generates AI-powered planning recommendations by comparing regions with world-class reference cities like Copenhagen and Singapore. Users can visualize these recommendations directly on an interactive 3D globe with color-coded planning zones, view a 2D map representation with urban interventions, and explore future growth scenarios with population projections and infrastructure requirements.

How We Built It

Geonova is built with a modern full-stack architecture combining Next.js and TypeScript for a robust foundation, CesiumJS for interactive 3D Earth visualization with real-time terrain and building rendering, Leaflet with OpenStreetMap for 2D urban planning maps, and Recharts for data visualization. The spatial analysis engine uses Haversine distance calculations and network connectivity algorithms to understand urban patterns, while Groq AI provides intelligent context generation and planning recommendations. Real-time environmental data comes from OpenStreetMap's Nominatim API for geocoding and live weather data from Open-Meteo. The entire application is styled with Tailwind CSS featuring a dark, professional aesthetic with glassmorphism effects, and is deployed on Vercel for seamless scalability.

Challenges We Ran Into

Integrating CesiumJS required careful token management to access 3D terrain and buildings without authentication errors. Loading Leaflet in a Next.js environment presented MIME type issues that required CDN-based loading instead of npm imports. Synchronizing 3D globe interactions with 2D map views demanded complex state management to ensure both visualizations stayed in sync. The spatial analysis calculations needed optimization to run smoothly on the browser while providing real-time feedback. Managing the Groq API integration in the Next.js runtime environment required special configuration with dangerouslyAllowBrowser flags to bypass SDK security checks designed for browser environments.

Accomplishments We're Proud Of

We created a fully functional 3D Earth visualization system that instantly loads detailed terrain and buildings for any city searched. The spatial analysis engine successfully calculates density metrics, connectivity patterns, green coverage percentages, and zoning distributions in real-time. Our AI integration generates contextually relevant urban planning recommendations by comparing cities with global best practices. The synchronized 3D/2D visualization system allows users to seamlessly switch between globe view and map view while maintaining all analysis data and planning overlays. The application successfully demonstrates future urban growth scenarios with realistic population projections and infrastructure recommendations, all rendered visually on both 3D and 2D interfaces.

What We Learned

CesiumJS is incredibly powerful for 3D geospatial visualization but requires careful attention to asset loading, token management, and performance optimization. Spatial analysis algorithms translate directly into visual planning insights when properly visualized. AI models like Groq excel at generating contextual recommendations when provided with well-structured spatial data. Building production-ready geospatial applications requires understanding the nuances of projections, coordinate systems, and rendering performance. The combination of 3D visualization with traditional 2D maps creates a more intuitive user experience for urban analysis, allowing users to understand both form and data in complementary ways.

What's Next for Geonova

Future enhancements include real-time collaboration features allowing multiple planners to work on the same region simultaneously, advanced scenario modeling where users can manually adjust planning parameters and see real-time impact on projections, integration with additional data sources like traffic data APIs, building permit databases, and climate models, mobile application support for field-based urban analysis, and community features enabling knowledge sharing between urban planners globally. We also plan to expand the AI recommendation system to provide cost-benefit analysis, environmental impact assessments, and implementation roadmaps with timeline estimates for major urban interventions.

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