Using Parcel Level Data for an Activity-Based

Tour Model

TRB Transportation Planning Application

Conference

May 8, 2007

Background for Modeling

• Long Range Land Use “Blueprint”– “4 D’s” emphasis– Regionally adopted– In process of developing first

Blueprint transportation plan

• Place3s Land Use Scenario/Analysis Tool– “Parcel” level data– Place type

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

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

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

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

Strategies for Developing Datasets

• Yield Estimation for Land Use Scenario– Qi = acrespt x yieldi

– 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.)

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

Place3sExisting Conditions

Place3s2030 Conditions

Change Parcels

Synthetic (Gridded)Parcels in

Change Ares

Intersection Density Lookup Table

  Intersection Density  

  (Int / Acre x 100) Good Density

Place Type 1-link 3-link 4-link 3's + 4's

Rural Residential 1.8 2.6 0.3 2.9

Single Family Large Lot 8.2 16.7 4.2 20.9

Single Family Small Lot 3.0 18.4 17.7 36.1

Retail 3.1 9.2 1.8 11.0

Industrial 0.3 1.2 0.4 1.6

Office 0.6 1.7 0.3 1.9

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

Existing Transit Stops

Future (Model) Transit Lines

Future Transit Stops

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

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

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)

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)

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