commuter-shed profiling

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

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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 - PowerPoint PPT Presentation

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Page 1: Commuter-shed Profiling

Commuter-shed Commuter-shed ProfilingProfiling

A higher resolution method A higher resolution method without effecting privacywithout effecting privacy

Page 2: Commuter-shed Profiling

• Previous Origination-Destination studies conductedPrevious Origination-Destination studies conducted• Coarse grained dataCoarse grained data• TAZ roughly 8,000-12,000 peopleTAZ roughly 8,000-12,000 people• Santa Clara study in 1999 with zip codesSanta Clara study in 1999 with zip codes

– 20% participation20% participation– 12 employment centers12 employment centers– Still about 10,000 people per zip code (5 digit)Still about 10,000 people per zip code (5 digit)

• Census ACS by county only with Journey-to-WorkCensus ACS by county only with Journey-to-Work• Stanford Research Park initiativeStanford Research Park initiative

– 4 employment centers4 employment centers– Employers volunteered data – no employee namesEmployers volunteered data – no employee names– Addresses geocoded then aggregated to 1/5 mile gridAddresses geocoded then aggregated to 1/5 mile grid

Page 3: Commuter-shed Profiling
Page 4: Commuter-shed Profiling

• How to get more detail without:How to get more detail without:– Compromising privacyCompromising privacy– Selective inclusionSelective inclusion

• Zip-Plus4 !Zip-Plus4 !– Based on street addressesBased on street addresses– Easily derivedEasily derived– Side of street or block level detailSide of street or block level detail– No actual address extractedNo actual address extracted

Page 5: Commuter-shed Profiling
Page 6: Commuter-shed Profiling

Raw Zip-Plus4 data to be geocodedRaw Zip-Plus4 data to be geocoded

Page 7: Commuter-shed Profiling

Road Network for geocoding:Road Network for geocoding:

Page 8: Commuter-shed Profiling

Raw Zip+4 geocoded to street midpoints:Raw Zip+4 geocoded to street midpoints:

Page 9: Commuter-shed Profiling

Details:Details:

Page 10: Commuter-shed Profiling

Overlaid on aerials:Overlaid on aerials:

Page 11: Commuter-shed Profiling

Euclidean Proximity polygons:Euclidean Proximity polygons:

Page 12: Commuter-shed Profiling
Page 13: Commuter-shed Profiling

Parcels selected by Zip+4 overlay:Parcels selected by Zip+4 overlay:

Page 14: Commuter-shed Profiling

Proactive Ridesharing Marketing

Employees Employer PA/VTA

EmployerEmployees PA/VTA

Addresses 1/5 Mile Grid

Request Zip code

Identify promising

neighborhoods

Stanford Model

Zip-Plus4Zip-Plus4

Zip-Plus4 Model

Page 15: Commuter-shed Profiling

• Zip-Plus4 could meet the need

• Privacy issues may be overcome

• Need a mechanism in place

Conclusion:Conclusion: