Coffee will be available at 9:45 am and lunch will be served following the meeting.
Grant Ervin | Project Manager - GIT | Michael Baker International | [email protected]
Stephen Holt | GIT Associate II |Michael Baker International | [email protected]
Shared Transportation Services Mobile Application Data Support Project - In an effort to provide the traveling public with timely and accurate information about transportation mode choices, particularly “shared-ride” alternatives to driving alone, Michael Baker International, in conjunction with the North Jersey Transportation Planning Authority (NJTPA) developed a data model and workflow for creating, publishing and maintaining a General Transit Feed Specification (GTFS). The NJTPA Shared Pilot Shared Transportation Services Data Model project included information from twenty-three (23) data feeds from fifteen (15) shared-ride agencies. Using a variety of technology including ArcGIS, python, and SQL server, Michael Baker developed an extract, transform and load (ETL) process to collect and validate transit data from the various transit agencies into one unified GTFS feed to be consumed by third party applications like Google and Apple. Additionally, Michael Baker and the NJTPA developed outreach, implementation and maintenance plans to support future development and expansion of the system as need and interest of shared-ride mode choices increase. In this session, attendees will learn about the GTFS format, its utilization for transit information dissemination, and how to leverage Python/ArcPy for automating the data unification process.
Addison Larson | Planning Data Scientist | DVRPC | [email protected]
Mapping with sample error in mind - Survey estimates from the Census Bureau are used to characterize neighborhoods and inform planning and policy decisions. However, as researchers use smaller geographies, the margins of error increase relative to the size of the estimates, making these data less reliable in description and decision-making.
DVRPC has begun to address the issues associated with survey data by developing a Map Reliability Calculator that helps researchers produce reliable maps without compromising an excess of geographic detail.
This presentation will: 1) Demonstrate DVRPC's Map Reliability Calculator, an interactive online tool developed in R Shiny that computes the expected classification error of Census estimates; 2) Discuss trade-offs in categorizing and mapping estimates, including the number of classes, classification schemes, and geographies; and 3) Outline DVRPC's proposed procedure to satisfy reliability criteria for smaller geographies by aggregating adjacent observations.
Andrew Thompson | Solutions Engineer | CARTO | [email protected]
CARTO- Andrew Thompson (Carto) will show us what insightful new features and enhancements have been made to the Carto (https://carto.com/) platform, an open source web mapping and data platform for location data. CARTO VL and Airship will be highlighted.