A temporal-contextual analysis of urban dynamics using location-based data

Abstract

The dynamics of urban activities in Jerusalem were studied by analyzing a large-scale semantically rich movement dataset. The semantic enrichment process was based on coupling movement trajectories sampled by GPS loggers with contextual data derived from trajectory-based digital activity dairies. Although the utility of such procedures in generating trajectory-specific semantic data was noted before, their application stays limited. In this paper, we promote the utilization of these procedures by demonstrating that they are not only feasible but also important for mobility studies. We discuss the characteristics of the semantic enrichment process and the manner by which it was applied within the large-scale analysis of urban dynamics. This application uncovered a time- and context-dependent array of centers in Jerusalem, resulting in a semantically rich characterization of urban dynamics. Such characterization provides otherwise unobtainable insights crucial for urban analysis. Wider implications for movement studies may be derived, as this application demonstrates how diary-based enrichment approaches hold the potential to advance bridging the semantic gap in mobility research.