1 / 17

Jon Makler, AICP | @ plangineering Portland State University

j. oy. Jon Makler, AICP | @ plangineering Portland State University Oregon Transportation Research & Education Consortium. OF WEB-BASED, GEOSPATIAL TRANSIT PERFORMANCE DATA ARCHIVES. Morgan Harvey, Programmer. Dr. Kristin Tufte, Technical Lead. Ryan Peterson, GIS Tech.

marci
Télécharger la présentation

Jon Makler, AICP | @ plangineering Portland State University

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. j oy Jon Makler, AICP | @plangineering Portland State University Oregon Transportation Research & Education Consortium OF WEB-BASED, GEOSPATIAL TRANSIT PERFORMANCE DATA ARCHIVES

  2. Morgan Harvey, Programmer Dr. Kristin Tufte, Technical Lead Ryan Peterson, GIS Tech Steve Callas Service & Performance Analysis Manager

  3. portal.its.pdx.edu Why? • More informed decision making through visualization • Efficient support for user requests for data • Enable innovative performance analysis

  4. portal.its.pdx.edu What Will We Cook Today? Transit Performance Data Web-based Geospatial

  5. portal.its.pdx.edu Ingredients

  6. portal.its.pdx.edu Menu Planning

  7. portal.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

  8. portal.its.pdx.edu Step 1: Convert GTFS to Feature Class

  9. portal.its.pdx.edu Step 2: ArcPy converts pattern lines to stop segments 6 14 33 Now you can match GTFS and PAX Data!

  10. portal.its.pdx.edu Step 3: Create Minimum Stop Segments 6 14 33 Now you can aggregate across routes!

  11. portal.its.pdx.edu Choices • Segment- and stop-based measures • Query options (time, day, season, year) • Display options (absolute and relative)

  12. portal.its.pdx.edu Garnish and Serve!

  13. portal.its.pdx.edu Garnish and Serve!

  14. portal.its.pdx.edu Garnish and Serve!

  15. portal.its.pdx.edu Garnish and Serve!

  16. 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

  17. Jon Makler makler@pdx.edu @plangineering portal.its.pdx.edu Thank You!

More Related