Visualizing Geospatial Data with Mapbox GL JS
Every business has location data. Customer addresses, delivery routes, store locations, service territories, asset positions. Most of it sits in a spreadsheet or a database column that nobody looks at. The challenge is not collecting it. The challenge is turning it into something a team can actually explore and act on.
That's why we built FlightPulse: an interactive flight tracking visualization that demonstrates how geospatial data can be brought to life on a map. While the domain is aviation, the patterns apply to any business that cares about where things are and where they're going.
Why Mapbox GL JS
We chose Mapbox GL JS for its performance with large datasets and its flexibility in styling. When you're rendering hundreds of markers with real-time updates, the rendering engine matters. Mapbox uses WebGL under the hood, which means smooth panning and zooming even with thousands of data points on screen.
The custom styling capability was equally important. A map that looks like Google Maps tells your users "this is a generic tool." A map with your own visual language says "this was built for this purpose."
Building the Visualization Layer
FlightPulse visualizes aircraft positions from ADSBExchange data. Each aircraft has a position, heading, altitude, and flight identifier. The interesting engineering challenge was layering multiple visualization modes on top of each other:
- Position markers showing current aircraft locations with directional indicators
- Flight path trails that can be toggled on or off per aircraft
- Altitude-based coloring that visually distinguishes cruising altitude from approach patterns
- Temporal filtering via a time slider that reveals patterns across different periods
- Individual aircraft selection for isolating a single flight path from the noise
The React + TypeScript Architecture
The application is built with React and TypeScript, using functional components and hooks throughout. Mapbox GL JS integrates well with React when you treat the map as a controlled component: React manages the application state, and the map renders whatever that state describes.
TypeScript was essential for this project. Geospatial data has a lot of nested structure (coordinates, properties, feature collections), and type safety catches errors at build time that would otherwise surface as silent rendering bugs on the map.
Applications Beyond Aviation
The same architecture that powers FlightPulse can be applied to any domain with location data:
- Logistics: Real-time fleet tracking with route visualization and delivery status
- Retail: Store performance heat maps, customer density analysis, site selection
- Real estate: Property portfolio visualization with market data overlays
- Emergency response: Incident mapping with resource allocation visualization
- Infrastructure: Asset monitoring across geographic territories
Getting Started with Your Data
If your business has location data that's sitting unused, the gap between "data in a spreadsheet" and "interactive map your team uses daily" is smaller than you think. The key ingredients are clean coordinate data, a clear question you want the map to answer, and a visualization layer that makes the answer obvious.
Try the live FlightPulse demo to see what this looks like in practice, or reach out to discuss how we could build something similar for your use case.
