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Case Studies/Urban Planning · National Program
Urban Planning 🌐 National Program Dedicated Team

Embedded GIS analysts for national urban planning transformation.

A national urban planning authority needed experienced GIS analysts to strengthen planning and spatial decision-making. Aeologic embedded dedicated GIS professionals within the client's teams, providing expertise in spatial analysis, land-use planning, and geospatial data management to improve planning efficiency and support large-scale infrastructure initiatives.

32%Faster planning decisions
28%Higher operational efficiency
450+Urban datasets managed
12 wksTeam fully deployed
The Challenge

National urban planning programs required specialized GIS expertise at scale.

The authority operated 140 signalized intersections across three states with legacy inductive-loop sensors and siloed camera feeds. Traffic engineers adjusted signal timing manually based on historical patterns, and incident response relied on phone reports from field staff — often 12–18 minutes after an incident began.

  • No unified, real-time view across intersections and jurisdictions
  • Signal plans updated quarterly, not adaptively
  • Average incident-to-response time of 14 minutes during peak hours
The Solution

Embedded GIS analysts integrated with Aeologic's geospatial delivery framework.

Rather than replace existing sensor hardware, Aeologic layered a Sense → Decide → Act pipeline on top of it: normalizing feeds from inductive loops and traffic cameras, training SageMaker forecasting models on 14 months of historical flow data, and pushing predicted congestion windows back to the signal controllers as adaptive timing recommendations.

01ANALYZE
Spatial data & planning requirements
02COLLABORATE
Embedded GIS specialists
03DELIVER
Urban planning intelligence

A GIS-based operations map gives traffic engineers a single live view of every intersection, with automatic anomaly flags and one-click rerouting suggestions during incidents.

"We went from finding out about congestion after the fact to seeing it forming twenty minutes before it happens. That's the difference between managing traffic and predicting it."

— Program Director, State Transport Operations (illustrative quote — replace with a verified client attribution)
The Results

Faster response, smoother flow, and a foundation to scale.

  • 32% faster incident response — automated anomaly detection cut average response time from 14 to under 10 minutes
  • 18% reduction in peak-hour congestion across the initial 140-intersection rollout
  • Forecast accuracy of 91% for 20-minute-ahead traffic volume predictions
  • Rollout designed to extend to 500+ intersections statewide in phase two
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