Pedestrian Count Data
Buy and sell pedestrian count data data. Hourly pedestrian volumes on sidewalks, crosswalks, and public spaces. City planning and retail site selection AI uses this.
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Find Me This Data →Overview
What Is Pedestrian Count Data?
Pedestrian count data measures hourly foot traffic volumes on sidewalks, crosswalks, and public spaces in urban environments. The data is generated through multiple technologies including computer vision, CCTV systems, cellular networks, and manual counting by trained observers. This real-time and historical pedestrian flow information is essential for understanding urban mobility patterns and economic activity at the neighborhood level. City planners, retail businesses, and infrastructure developers rely on pedestrian count data to make evidence-based decisions about site selection, urban design, and transportation planning. The data captures not just raw pedestrian volumes but also movement patterns across different times of day, street widths, and locations relative to tourist hotspots and commercial districts. Because official economic data like GDP and retail spending are released infrequently and at high spatial aggregation levels, pedestrian counts serve as a timely proxy for local economic vitality.
Market Data
41% of city-wide trips made on foot
NYC Pedestrian Trip Share
Source: MIT News
Computer vision, CCTV, sensors, and manual counting
Data Collection Method
Source: ResearchGate
Up to 1,000 sidewalk segments on weekdays; ~450 on weekends
NYC DOT Coverage
Source: MIT News
42 locations and 78 sidewalk segments with trained human counters
Somerville Annual Survey
Source: SAGE Journals
Who Uses This Data
What AI models do with it.do with it.
Retail Site Selection
Retailers evaluate potential locations by analyzing pedestrian volumes and congestion patterns to assess foot traffic potential and customer accessibility.
City Planning & Infrastructure
Urban planners use pedestrian counts to calibrate models for new development, transit planning, and infrastructure proposals to understand foot-traffic impacts.
Local Economic Analysis
Economists and policymakers use pedestrian counts as a timely proxy for local economic activity when official GDP and retail spending data is unavailable or delayed.
Post-Occupancy Evaluation
Architects and urban designers compare pedestrian counts before and after interventions to assess whether designs achieved intended movement and activation outcomes.
What Can You Earn?
What it's worth.worth.
Raw Hourly Counts
Varies
Single sidewalk or crosswalk segment; basic volume data
Segmented Analysis
Varies
Data enriched with direction, time-of-day, and congestion metrics
Multi-Location Datasets
Varies
Aggregated counts across multiple city blocks or districts; higher value for planning applications
Validated Historical Series
Varies
Years of verified counts with seasonal and event-based patterns; premium for economic modeling
What Buyers Expect
What makes it valuable.valuable.
Temporal Granularity
Hourly or sub-hourly counts across weekdays and weekends, with coverage during AM and PM peak travel periods for accurate flow representation.
Spatial Precision
Clear identification of segment location, street width, direction of movement, and proximity to landmarks or commercial zones for context and comparability.
Methodology Transparency
Documentation of collection method (camera-based, manual, sensor), validation procedures, and any quality assurance steps taken to verify accuracy.
Consistency & Verification
Repeated counts at same locations across multiple time periods to enable trend analysis, with cross-validation between automated systems and manual counting.
Companies Active Here
Who's buying.buying.
Conduct annual pedestrian surveys and calibrate foot-traffic models for infrastructure planning and development review
Harvests pedestrian count data using computer vision technology from city streets; produces automated reports tracking pedestrian volumes for customers
Use pedestrian counts for post-occupancy evaluation of public spaces (Trafalgar Square, Central St Giles, Bloomberg HQ) to validate design outcomes
Build predictive models and calibrate pedestrian flow algorithms using observed count data to forecast movement patterns and economic activity
FAQ
Common questions.questions.
How is pedestrian count data collected?
Pedestrian count data is collected using multiple methods: computer vision technology (automated camera systems that process video to count pedestrians), CCTV systems, cellular network data, weather station integration, and trained human observers who manually count using screen-line methods across designated street segments. Most modern systems process video in real-time and discard raw footage after extraction for privacy protection.
What makes pedestrian count data valuable for economic analysis?
Pedestrian counts serve as a timely proxy for local economic activity in neighborhoods and central business districts. Unlike official economic data like GDP and retail spending, which are released infrequently and only at high spatial aggregation levels, pedestrian counts provide granular, real-time insights into local economic vitality and can help policymakers and businesses make faster, more informed decisions.
How accurate are automated computer vision systems for counting pedestrians?
Automated systems using computer vision have shown good results when verified against manual counts. Research teams typically cross-validate camera-based counts with trained human counters at the same locations to ensure accuracy. Repeated counts at identical locations across multiple time periods allow for verification and trend validation.
What are the privacy concerns with pedestrian counting technologies?
Sensor, cellular phone network, and CCTV technologies used for pedestrian counting raise personal data protection concerns. However, companies like Placemeter address this by discarding video footage after processing (except for small quality assurance samples) and converting raw data into anonymized pedestrian count reports rather than retaining identifiable information.
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