These projects translate large-scale transportation data into clear visual narratives that support understanding and decision making. I collaborated with planners, engineers, and data scientists to develop comparative frameworks that reveal system-level patterns and impacts.
The first project, pictured below and developed in collaboration with Amazon’s data scientists and engineers, examines the commute implications of relocating employees from South Lake Union to Bellevue. Transit accessibility drops significantly, with 68% of employees able to reach South Lake Union within 55 minutes by transit, compared to 28% for Bellevue. Average transit commute times increase from 35 to 50 minutes, and fewer walking and biking options further reduce viable alternatives. As a result, the shift in location would likely increase reliance on driving.
Comparing commutes between South Lake Union and Bellevue. Transit access is better to South Lake Union, while limited options in Bellevue results in a reliance on driving.
The project below examines how summer holiday traffic affects Interstate 90 and surrounding county roads. By comparing speeds, volumes, and congestion over time, the graphic reveals how increased demand on I-90 leads to diversion and localized impacts on adjacent road networks.
Infographic showing how holiday congestion on I-90 causes drivers to divert onto county roads, increasing local traffic volumes and extending congestion beyond the highway.