Activiteit: Talk or presentation at a workshop/seminar
Description
Mobility data typically covers both the spatial and temporal domain. The literature lacks methods which fully exploit the richness and at the same time manage the complexity of such data sets. Moreover, mobility data is often characterised by poor quality. In this paper two novel techniques are proposed that facilitate the advanced analysis of (spatiotemporal) mobility data. First, an incremental imputation technique is realised, which reduces substantially the amount of missing data by cleverly exploiting the spatio-temporal properties of historical data. Second, a multi-step non-negative matrix factorisation workflow is conceived allowing to extract spatio-temporal fingerprints of traffic trajectories of interest. The validation of both methods on a data set of vehicle counts from multiple adjacent locations in the Brussels-Capital Region (Belgium) produced already very promising results.
Periode
7 dec 2021
Evenementstitel
16th International Workshop on Spatial and Spatiotemporal Data Mining, 2021