Volume 1: Data Preprocessing and Visualization focuses on how to efficiently pre-process mobile big data to extract and utilize critical feature information of high-dimensional city people flow. It first provides a conceptual theory and framework, then goes on to discuss data sources, trajectory map-matching, noise filtering, trajectory data segmentation, data quality assessment and more. It concludes with a chapter on privacy protection in mobile big data mining.

Volume 2: Mobility Analytics and Prediction provides a basis for how to simulate and predict mobility data. After an introductory theory chapter, it then covers crucial topics such as long-term mobility pattern analytics, mobility data generators, user information inference, Grid-based population density prediction, and more. It concludes with a chapter on graph-based mobility data analytics.

Volume 3: Mobility Data-driven Applications looks at various cases studies to illustrate and explore the methods introduced in the first two volumes. It begins with a set of chapters on Intelligent Transportation Management, using cases of dynamic road pricing, P2P bidding systems, bicycle-sharing systems, ride-sharing simulation, and customized bus systems. Part 2 then discusses Smart Emergency Management, detailing cases such as the Fukushima Earthquake, Hurricane Katrina, and COVID-19. Part 3 concludes with a set of chapters on Urban Sustainability Development, covering bicycle travel behavior, railway travel behavior, mobility inequality, and both road and light pollution inequality.