In this Working Paper we analyse computational strategies for using aggregated spatio-temporal population data acquired from telecommunications networks to infer travel and movement patterns between geographical regions. Specifically, we focus on hour-by-hour cellphone counts for the SA-2 geographical regions covering the whole of New Zealand. This Working Paper describes the implementation of the inference algorithms, their ability to produce models of travel patterns during the day, and lays out opportunities for future development.
@article{arxiv.2303.17758,
title = {Commuter Count: Inferring Travel Patterns from Location Data},
author = {Nathan Musoke and Emily Kendall and Mateja Gosenca and Lillian Guo and Lerh Feng Low and Angela Xue and Richard Easther},
journal= {arXiv preprint arXiv:2303.17758},
year = {2023}
}