Measuring access to opportunities in a transportation system requires two key ingredients: Travel times (typically in the form of travel time matrices) and opportunity locations. In this workshop, we will use a brand-new Python module called r5py to quickly generate realistic travel time matrices for public transit and other modes. The workshop will outline the basic approach used to generate the matrices, and explore some of the ways it can be used to calculate travel time measures to hospitals. To get the most out of the workshop, participants should have a familiarity with Python notebooks and the Pandas library, as well as basic geospatial mapping software experience to visualize and quality-check the results. This workshop will use Python notebooks and a provided dataset from CANUE and supplemental open datasets. Previous experience with python is required.
These workshops are presented in collaboration by GeoHealth Network, The Canadian Urban Environmental Health Research Consortium (CANUE), Population Data BC, University of Victoria Continuing Studies and sponsored by the University of Toronto Tri-Campus Graduate Program in Geography and Planning, School of Cities, and University of Toronto - Mississauga (The Angela B. Lange and Ian Orchard Graduate Student Initiatives Fund).
