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Commuter-shed Profiling

Commuter-shed Profiling. A higher resolution method without effecting privacy. Previous Origination-Destination studies conducted Coarse grained data TAZ roughly 8,000-12,000 people Santa Clara study in 1999 with zip codes 20% participation 12 employment centers

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Commuter-shed Profiling

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  1. Commuter-shed Profiling A higher resolution method without effecting privacy

  2. Previous Origination-Destination studies conducted • Coarse grained data • TAZ roughly 8,000-12,000 people • Santa Clara study in 1999 with zip codes • 20% participation • 12 employment centers • Still about 10,000 people per zip code (5 digit) • Census ACS by county only with Journey-to-Work • Stanford Research Park initiative • 4 employment centers • Employers volunteered data – no employee names • Addresses geocoded then aggregated to 1/5 mile grid

  3. How to get more detail without: • Compromising privacy • Selective inclusion • Zip-Plus4 ! • Based on street addresses • Easily derived • Side of street or block level detail • No actual address extracted

  4. Raw Zip-Plus4 data to be geocoded

  5. Road Network for geocoding:

  6. Raw Zip+4 geocoded to street midpoints:

  7. Details:

  8. Overlaid on aerials:

  9. Euclidean Proximity polygons:

  10. Parcels selected by Zip+4 overlay:

  11. Proactive Ridesharing Marketing Stanford Model Zip-Plus4 Model Addresses 1/5 Mile Grid Employees Employer PA/VTA Zip-Plus4 Identify promising neighborhoods Zip-Plus4 Request Zip code Employees Employer PA/VTA

  12. Conclusion: • Zip-Plus4 could meet the need • Privacy issues may be overcome • Need a mechanism in place

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