par David, Rodrigo Sasse;Torp, Kristian;Sakr, Mahmoud 
;Zimanyi, Esteban
Référence Data Engineering for Data Science, Springer Nature, page (337-356)
Publication Publié, 2026-01
;Zimanyi, Esteban Référence Data Engineering for Data Science, Springer Nature, page (337-356)
Publication Publié, 2026-01
Partie d'ouvrage collectif
| Résumé : | Network-constrained trajectory analysis is the study of movement con-strained by an underlying network, such as a road system. Such analysis has become increasingly important in addressing contemporary urban challenges. With the grow-ing availability of Global Navigation Satellite System (GNSS) data, it is now possible to analyze mobility patterns at scale and with high precision. This chapter explores how GNSS data can be leveraged to support urban planning, with a particular focus on two key applications: road traffic management and sustainable mobility. By exam-ining vehicle trajectories, we highlight methods for quantifying congestion, moni-toring traffic dynamics, and promoting environmentally friendly practices such as eco-driving and eco-routing. |
