🗺️ Street Network Analysis
Analyze the walkability of the street network surrounding transit stations. This tool measures block lengths, intersection density, and connectivity patterns to assess how easily pedestrians can navigate to and from stations through the existing street grid. In order to speed up image processing, the maps on this page show the street network within a 1/4 mile radius of the station. The data and analysis represent the street network within a 1/2 mile radius of the station.
Street Network Analysis
About Street Network Analysis
This tool analyzes the pedestrian environment around transit stations by examining street network connectivity, density, and walkability. The analysis measures how easy it is to walk to and from a station based on the structure of the surrounding street grid.
What We Measure
The analysis examines the street network within an 800-meter (½ mile) walking radius and calculates several key metrics:
Block Length
- Measures the average distance between intersections along street segments
- Shorter blocks create more direct walking routes with more route choices
Intersection Density
- Counts the number of true intersections (3+ connecting streets) per square mile
- More intersections = more connectivity and route flexibility
Street Network Connectivity
- Evaluates how well the street grid connects different areas
- Identifies dead-ends and cul-de-sacs that reduce walkability
- Measures the overall density of the street network
How the Analysis Works
This analysis uses OpenStreetMap data to build a complete model of the street network:
- Network Retrieval: The system queries OpenStreetMap's database for all streets and pathways within 800 meters of the station, including:
- All street types (residential, arterial, etc.)
- Pedestrian paths and sidewalks
- The connections between streets (topology)
- Intersection Detection: True intersections are identified as locations where 3 or more streets meet
- Simple connections between two streets (not intersections) are excluded
- This ensures we're measuring genuine route choice points
- Block Length Calculation: The distance between each pair of consecutive intersections is measured
- The average across all segments gives the overall block length
- Connectivity Analysis: The network structure is analyzed to identify:
- Dead-ends and cul-de-sacs
- Overall network density
- How well different parts of the area connect to each other
Why This Matters
Street network connectivity plays an important role in creating walkable areas:
Direct Impact on Walking
- Shorter blocks mean more direct routes to destinations
- More intersections provide route flexibility and choice
- Well-connected grids reduce walking distances by 20-40% compared to suburban patterns
Transit Accessibility
- A walkable street grid expands the effective catchment area of the station
- Good connectivity means more people can easily walk to transit
- Poor connectivity can make nearby destinations unreachable by foot
Safety and Comfort
- Connected grids distribute traffic across multiple routes
- More intersections create "eyes on the street" for safety
- Grid patterns typically have slower vehicle speeds
Development Potential
- Walkable grids support mixed-use development
- Better connectivity increases property values near transit
- Grid patterns enable efficient land use around stations
Equity Considerations
- Disconnected networks disproportionately affect those without cars
- Good street connectivity is essential for transit-dependent populations
- Walkable neighborhoods provide access to opportunities without vehicle ownership
Important Notes
Data Quality: OpenStreetMap data quality varies by location. Areas with active mapping communities have more complete and accurate data.
Scope: This analysis focuses on the physical street network structure, not on the quality of pedestrian infrastructure (sidewalks, crossings, etc.).
Context Matters: A lower score doesn't always mean poor walkability in practice. Some areas may have excellent pedestrian paths or greenways not captured in street network analysis. Similarly, a high score for the street grid doesn't guarantee good sidewalks or safe crossings.
Comparison Tool: Scores are most useful for comparing different stations or identifying which station areas might benefit most from connectivity improvements.