Public transport is a major mode of transportation when accessing various health services. Modern public transport data is in the form of GTFS and provides comprehensive data for networks from Perth to London and many cities in-between. The network data comes in a complex highly detailed form and at scale. This project is to develop a Python workflow that will optimise the extraction of GTFS data for researchers to then use to understand health access whilst being generic enough to extract data from any GTFS set in the world. Data extractions for example will include questions such as all routes in a city with a certain frequency between certain hours of the day. The product produced in Python will be of a form where other questions for extractions can be applied. At the end of the day the data will need to be transferable to Geographic Information Systems to integrate with other geographic data - eg Doctors clinics to then complete the analysis. As a test of the project, we will use GNAF data (location of every building in Australia) to look at travel time between homes and hospitals (other health facilities) using the public transport network in 3 capital cities.
Department of Computer Science & Software Engineering The University of Western Australia Last modified: 18 July 2024 Modified By: Michael Wise |
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