oyJon Makler, AICP | @plangineering

Portland State UniversityOregon Transportation Research & Education Consortium

jOF WEB-BASED, GEOSPATIAL TRANSIT PERFORMANCE DATA ARCHIVES

Morgan Harvey, ProgrammerDr. Kristin Tufte, Technical Lead

Ryan Peterson, GIS Tech

Steve Callas Service & Performance Analysis Manager

Why?

• More informed decision making through visualization

• Efficient support for user requests for data• Enable innovative performance analysis

portal.its.pdx.edu

What Will We Cook Today?

TransitPerformance

Data

Geospatial Web-based

portal.its.pdx.edu

Ingredientsportal.its.pdx.edu

Menu Planningportal.its.pdx.edu

Prepare the Ingredients!

• Prepare GTFS data and set aside• Collect daily APC and AVL data• Clean the data based on error messages,

mismatched ons and offs, more• Aggregate by quarter for “typical” data• Be prepared for strange values (partial people)• Export data with enough fields to support

GTFS matching

portal.its.pdx.edu

Step 1: Convert GTFS to Feature Classportal.its.pdx.edu

Step 2: ArcPy converts pattern lines to stop segments

Now you can match GTFS and

PAX Data!

portal.its.pdx.edu

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Step 3: Create Minimum Stop Segments

Now you can aggregate across

routes!

portal.its.pdx.edu

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Choices

• Segment- and stop-based measures• Query options (time, day, season, year)• Display options (absolute and relative)

portal.its.pdx.edu

Garnish and Serve!portal.its.pdx.edu

Garnish and Serve!portal.its.pdx.edu

Garnish and Serve!portal.its.pdx.edu

Garnish and Serve!portal.its.pdx.edu

Dessert(aka, next steps)

• Cartographic refinements– Line Offsets– Point symbology

• Integrate data visualizations (pie charts & plots)

• Data download capability• Non-temporal queries

portal.its.pdx.edu

Thank You!

Jon Maklermakler@pdx.edu@plangineeringportal.its.pdx.edu