1 / 15

Enhancing Commuter Shed Profiling with Zip-Plus4 Data

Learn about a higher resolution method for commuter-shed profiling without compromising privacy. Discover how Zip-Plus4 data can provide more detailed information about commuter patterns while safeguarding individual privacy. Explore case studies, data processing techniques, and proactive ridesharing strategies. This informative guide presents a comprehensive approach to understanding commuter behavior at a granular level.

aurek
Download Presentation

Enhancing Commuter Shed Profiling with Zip-Plus4 Data

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  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

More Related