1. Using Parcel Level Data for an Activity-Based Tour Model TRB Transportation Planning Application Conference May 8, 2007

2. Background for Modeling Long Range Land Use “Blueprint” –“4 D’s” emphasis –Regionally adopted –In process of developing first Blueprint transportation plan Place 3 s Land Use Scenario/Analysis Tool –“Parcel” level data –Place type

3. Background for Modeling (cont’d) Limitations of zone-based model –Many 4 D’s factors missed by zone aggregation Developed SACSIM (Activity-Based Tour Model) –Familiar model (similar to SF, others) –Based on parcel-level land use data –Motorized Networks still TAZ-based for assignment –Skims combine TAZ skims and direct parcel/point proximity measures

4. Types of Parcel/Point Data Files Place3s “Parcel” Files –Place Type, Acres –# Dwellings –# Jobs Schools –K12 (all types) –College/University 4+ year colleges Community colleges Paid Off-Street Parking –# Spaces –$ / day, $ / hour

5. Types of Parcel/Point Data Files (cont’d) Street Pattern –Intersection points by type –Types = 1, 3, 4+ legs / node Transit stations/stops –LRT, rail stations –Fixed route bus stops –Park-and-ride facilities

6. Parcel/Point Data Formulations Point values –# of dwellings, jobs, school enrollments, etc. at the parcel/point Buffered point values –# of dwellings, jobs, etc. within ¼ or ½ mile of parcel

7. Strategies for Developing Datasets Yield Estimation for Land Use Scenario –Q i = acres pt x yield i –Used for both “base year” (2005) and future year dataset –Future year land use scenarios developed in Place3s Inventory + Change –Base year points from inventory –Future year change from other source (Place3s, travel model networks, etc.)

8. Examples of Inventory+Change Approach Street Pattern / Intersection Density –Use actual GIS intersection points for 2005 –For future year, use Place3s comparisons between 2005 and future year to identify “change” parcels –Apply lookup rates by place type to change parcels

9. Place 3 s Existing Conditions

10. Place 3 s 2030 Conditions

11. Change Parcels

12. Synthetic (Gridded)Parcels in Change Ares

13. Intersection Density Lookup Table Intersection Density (Int / Acre x 100) Good Density Place Type 1-link3-link4-link 3's + 4's Rural Residential1.82.60.32.9 Single Family Large Lot8.216.74.220.9 Single Family Small Lot3.018.417.736.1 Retail3.19.21.811.0 Industrial0.31.20.41.6 Office0.61.70.31.9

14. Examples of Inventory+Change Approach (cont’d) Transit stops –Use 2005 GIS inventory of stops for base year –Identify new lines by comparing 2005 and future year travel model transit networks (zone- base) –Synthesize transit stops for the new lines –Add new stops to inventory

15. Existing Transit Stops

16. Future (Model) Transit Lines

17. Future Transit Stops

18. Scale of Data Production Place3s land use datasets are the basis –Separate staff to work with local agencies, committees etc. to develop land use scenarios in Place3s –2 persons full-time, 4-5 part time dedicated to this effort –Place3s used for many land use planning, outreach and public relations functions

19. Scale of Data Production (cont’d) Inventory Data –Housing, employment, schools, transit stops –Separate function, 5-6 staff work part time on this –Episodic (updates every 2-3 years or for special projects

20. Scale of Data Production (cont’d) Time required to generate a full SACSIM dataset –Starting point: Complete, regional Place3s dataset –Ending point: Complete, runnable SACSIM dataset –Approximate duration: 1-2 weeks –Approximate staff time: 50 hours, spread between 4 staff –20-30 hours running time for buffering a new file (single thread workstation)

21. Making It Faster Buffering: selective re- buffering Up front QC of files –Re-do’s are painful… Multi-threading / server farm (in budget next year)

22. Acknowledgments ABTM Model (Daysim) Designers, Architects –John Bowman, Ph.D –Mark Bradley Application and Shell Program Developers –John Gibb, DKS Associates Parcel Data Production Process –Steve Hossack, SACOG