Abstract

Leveraging Network Analyst and Python to Automate Production of Commodity Flows
Track: Government
Authors: Elise Pietroniro, Ethan Howieson

Network Analyst and Python were leveraged in an automated process to create commodity flows of dangerous goods for Transport Canada. In an effort to efficiently represent movement by rail, thousands of rail data records are interpreted and conditioned through python scripting. Origin-destination pairs are loaded and routing analysis results are generated using Network Analyst. The complete process includes analysis and mapping production, resulting in much increased savings in time and effort.