Handbook of Mobility Data Mining, Volume 1 1st Edition

Grab the future of urban movement with Handbook of Mobility Data Mining, Volume 1, 1st Edition by Haoran Zhang. This authoritative guide immediately draws readers in with a clear promise: practical, research-grade insights for making sense of location-based and trajectory data that power today’s smart cities and transport systems.

Dive into rigorous yet accessible explanations of spatial–temporal analytics, trajectory mining, clustering, predictive modeling, and privacy-aware data handling. Written for data scientists, urban planners, transportation engineers, and graduate students, the book balances theoretical depth with hands-on problem solving—explaining algorithms and workflows while showing how to interpret mobility patterns across urban, regional, and national contexts.

Imagine improving public transit scheduling, optimizing ride-hailing fleets, or designing safer pedestrian networks—this volume gives you the analytical tools and conceptual framework to turn raw GPS traces, cell-tower logs, and sensor feeds into actionable strategy. It highlights best practices for cleaning, aggregating, and visualizing mobility data, along with robust discussion of ethical and legal considerations for location privacy.

Practical, relevant, and globally minded, Handbook of Mobility Data Mining is ideal for professionals and academics working in transport agencies, city governments, GIS firms, and research labs across North America, Europe, Asia, and beyond. Whether you’re developing smart-city solutions or advancing mobility research, Haoran Zhang’s first volume is a foundational resource that elevates both projects and careers.

Add this essential reference to your library today to master the techniques shaping the future of transport and urban mobility.

Note: eBooks do not include supplementary materials such as CDs, access codes, etc.