Johnny McGlone is the GIS Manager, Digital Solutions, STV

This interview was recorded by Todd Danielson, the editorial director of Informed Infrastructure. You can watch the full interview above or by visiting iimag.link/FEPOM.

Johnny McGlone has spent his career finding new ways to apply GIS across industries. At STV, a North American infrastructure-focused professional services firm, that means working at the intersection of data, infrastructure and mobility—often bringing together teams that don’t traditionally collaborate.

A recent project that was turned into a conference presentation, “Pedals and Platforms: A Spatial Look at Bike and Subway Access,” demonstrates how that approach can yield insights engineers can directly apply to design and planning decisions.

Understanding the Gaps in Access

The project began as part of an open-data challenge from New York’s Metropolitan Transportation Authority, which provides extensive public datasets on transit infrastructure. STV’s team focused on Brooklyn, analyzing how well bike infrastructure connects to subway entrances—and where gaps create safety risks.

“The idea is, someone commuting via train is typically a pedestrian or cyclist,” McGlone explains. “So how well can they actually access the system?”

To answer that, the team evaluated the spatial relationship between protected bike infrastructure and subway access points. A key method was a buffer analysis: mapping a 1,000-foot radius around bike facilities, based on the typical dimensions of a New York City block. Any station outside that range was considered disconnected.

According to their results, approximately 21 percent of subway stations in Brooklyn fell outside that threshold, indicating a meaningful gap between bike networks and transit access.

For engineers, that disconnect highlights a fundamental issue: bike infrastructure and transit access often are designed independently, even though they function as a combined system for many users.

Data That Go Beyond the Map

STV didn’t stop at identifying spatial gaps. They layered in four years of open-source crash data from the New York Police Department—filtered specifically for cyclist and pedestrian incidents—and analyzed them across multiple dimensions.

“We didn’t just look at high and low counts,” he says. “We pushed into hotspot analysis, outlier analysis and even spatial-temporal patterns to really understand what’s happening.”

That deeper analysis revealed patterns engineers can use to inform design decisions. Crashes were most frequent in the evening peak between 4 p.m. and 6 p.m. as well as during summer months and midweek days. Northern Brooklyn showed both the highest “bikeability” scores and the highest crash rates, suggesting increased usage may drive higher incident counts.

More importantly, the team created a relationship map combining bikeability and crash data. This allowed them to categorize areas into actionable groups:

1. High bikeability, high crashes—areas where infrastructure exists but safety improvements may be needed
2. Low bikeability, high crashes—priority zones for infrastructure investment
3. High bikeability, low crashes—potential models for replication
4. Low bikeability, low crashes—areas that may benefit from increased usage

Stronger Results Through Teamwork

A defining aspect of the project was the collaboration among GIS specialists and data scientists—two groups that don’t always work closely together.

STV’s GIS team focused on spatial relationships and mapping, while the digital solutions group brought expertise in analytics, automation and modeling. That combination allowed the team to go further than either group typically would on its own.

“I think a lot of GIS groups tend to focus specifically on GIS,” says McGlone. “But whenever you team up with other groups and can solve the problem together, you have different, elevated results.”

Lessons for Engineers

While the project focused on Brooklyn, McGlone emphasizes that the methods are widely applicable—to other cities, transit systems and even different types of infrastructure.

“These issues start at the community level,” he explains. “What is your community saying? What are their concerns? Then look at the data, find the disconnects, find the relationships. Let’s help our community directly.”

From there, engineers can move beyond static analysis and toward iterative solutions. By tracking data through time, teams can evaluate whether design changes or pilot projects are actually improving outcomes.

“Don’t just look at your data as a snapshot,” advises McGlone. “Look at it as detailed increments of data to understand the patterns. And don’t have one person wear all the hats. Bring your teams together. That’s how you really understand the full challenge and reach your goal.”

Finally, he encourages engineers to fully leverage the analytical tools available to them. “Take your analysis to the next level,” he says. “Don’t leave your data hanging.”