Modelling Urban Flows, Spatial Effects in Origin-Destination data


This paper is an introduction of preliminary research for Ph.D. thesis ‘Machine Learning methods for Urban Flows, spatial effects in Origin-Destinations’. It examines the biggest challenges in the theory of Gravity models and Spatial Interaction models for urban flow prediction, including the nature of the human spatial decision-making. It also outlines the biggest concerns with the methodological approaches for predicting urban flows and presents the future steps of this research

In GISRUK 2020