What I Built

I’ve created PDX Noise Map, a web-based visualization that tracks live aircraft around Portland International Airport and simulates their noise impact across the city. The map combines real flight data with calculated noise patterns to show how aircraft operations affect different Portland neighborhoods.

How It Works

The demonstration pulls live aircraft positions from the OpenSky Network API, showing actual planes flying in and out of PDX right now. Each aircraft’s position, altitude, and velocity are updated in real-time.

The noise visualization layer is generated through physics-based calculations: using each aircraft’s actual position and altitude, the system simulates how sound would propagate across the Portland metro area. While the noise levels themselves are simulated (not from physical sensors), they’re based on realistic acoustic modeling that considers distance, altitude, and typical aircraft noise profiles.

The result is a dynamic heatmap that changes as planes take off, land, and fly overhead – warmer colors indicate higher calculated noise levels based on proximity to active flight paths.

Current Features

• Live Aircraft Tracking: Real planes, real positions, updated every few seconds via OpenSky Network
• Dynamic Noise Heatmap: Calculated noise levels based on actual aircraft positions
• Neighborhood Monitoring Points: Virtual sensors showing estimated noise levels across Portland communities
• Interactive Audio: Integrated jet engine sounds that respond to your mouse position – move your cursor to experience how noise varies across the map
• Adjustable Controls: Toggle audio, adjust volume, change visualization opacity, sort monitors by various metrics

Built Through AI Collaboration

I’m not a trained coder, and I built this with what is being called “vibe coding” with AI. Rather than writing every line manually, I used Claude and ChatGPT to rapidly prototype and iterate on the concept.

The development process looked like:

1. Describing the vision: “I want to create a heatmap that shows airplane noise over Portland, OR.”
2. AI generating initial code structures
3. Testing and providing feedback: “Add fading flightpaths behind the planes, create a network of simulated sensors”
4. AI refining based on real-world results: “Make the default gradient more opaque, make the map full-screen”
5. Iterating until it I was satisfied

This approach allowed me to go from concept to working demonstration in days rather than weeks. The AI handled the technical implementation details while I focused on the user experience and visual design. It’s a glimpse into how creative coding might work in the future – human design intent combined with AI’s ability to rapidly implement and iterate.

Technical Implementation

The result is a single-file HTML application that runs entirely in the browser:

• Pure JavaScript with Canvas API for rendering
• OpenSky Network API for live flight data
• Real-time data updates every 10 seconds
• Physics-based noise propagation calculations
• No external dependencies beyond the flight data API
• Mobile responsive design

Why This Matters

A tool like PDX Noisemap matters because chronic environmental noise isn’t just annoying—it’s a measurable health and ecology issue. Decades of research (and the WHO’s noise guidelines) link transportation noise to poorer sleep, elevated blood pressure, cardiovascular disease, and impaired cognition, with nighttime exposure especially harmful. With health effects second only to air pollution, making noise pollution patterns visible helps residents and policymakers target mitigation where it counts. In Portland specifically, new OSU work maps unhealthy noise levels that disproportionately burden more socially vulnerable neighborhoods, underscoring an equity imperative. And it’s not only people: chronic anthropogenic noise disrupts wildlife communication, physiology, and community dynamics—birds, for example, shift song pitch, suffer stress responses, and show reduced reproductive success near persistent noise. Bringing these impacts into a live, transparent map lets communities see what’s happening, when, and to whom—so interventions can be timely, data-driven, and fair.

Try It Now

The demonstration is available here.

Note: The audio feature requires user interaction to start due to browser autoplay policies. Click anywhere on the page to activate sound, then move your mouse to explore the soundscape.

Future Possibilities

This demonstration shows what’s possible when environmental data is made accessible and immediate. Potential enhancements could include:

• Integration with actual noise monitoring stations for validation
• Historical pattern analysis
• Community reporting features
• Predictive modeling based on flight schedules

About the Approach

This project demonstrates the power of AI-assisted development for civic technology. By collaborating with AI, individual developers can create sophisticated visualizations that would traditionally require teams and significant resources. It’s democratizing not just access to data, but the ability to build tools that make that data meaningful.

PDX Noise Map is a demonstration of real-time flight tracking combined with simulated acoustic modeling to visualize aircraft noise impacts across Portland neighborhoods.