Handbook of Mobility Data Mining, Volume 1

Handbook of Mobility Data Mining, Volume 1

Data Preprocessing and Visualization

1st Edition - January 1, 2023

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  • Editor: Haoran Zhang
  • Paperback ISBN: 9780443184284

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The Handbook of Mobility Data Mining introduces the fundamental technologies of mobile big data mining (MDM), advanced AI methods, and upper-level applications, helping readers comprehensively understand MDM with a bottom-up approach. It explains how to preprocess mobile big data, visualize urban mobility, simulate and predict human travel behavior, and assess urban mobility characteristics and their matching performance as conditions and constraints in transport, emergency management, and sustainability development systems. Further, it focuses on introducing how to design MDM platforms that adapt to the evolving mobility environment, new types of transportation, and users based on an integrated solution that utilizes sensing and communication capabilities to tackle the significant challenges that the MDM field faces. 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. The information in this work is crucial for researchers, engineers, operators, company administrators, and policymakers in related fields, to comprehensively understand current technologies' infra-knowledge structure and limitations.

Key Features

  • Introduces the characteristics of different Mobility Data sources, like GPS, CDR, and sensor-based Mobility Data
  • Summarizes existing visualization technologies of the current transportation system into a multi-view frame, covering the perspective of the three leading actors, then provides recommendations for practical open-source tools and libraries for system visualization
  • Stems from the editor’s strong network of global transport authorities and transport companies, providing a solid knowledge structure and data foundation as well as geographical and stakeholder coverage


Researchers, engineers, operators, company administrators, and policymakers on transportation, environment, urban planning, data mining, and sustainability; Transport-mobility planners, the road and vehicle industry, urban management authorities, transportation institutes, traffic police, public and goods transport operators; masters and Ph.D. students pursuing research in the area of mobility and transportation

Table of Contents

  • 1. Mobility Data Preprocessing and Visualization: Concept, Theory, and Framework

    2. Mobility Data Sources
    2.1 GPS Mobility Data Mining
    2.2 CDR Mobility Data Mining
    2.3 Sensor-based Mobility Data Analytics

    3. Trajectory Map-Matching
    3.1 Geometric Map-matching Algorithm
    3.2 Topological Algorithm
    3.3 Probabilistic Algorithm
    3.4 Machine Learning- based Map-matching Algorithm

    4. Noise Filtering of Mobility Data
    4.1 Cluster-based Filter Method
    4.2 Kalman Filter Method
    4.3 Heuristic-based Outlier Detection Method

    5. Trajectory Data Segmentation
    5.1 Attribute-Driven Segmentation
    5.2 Pattern-Driven Segmentation

    6. Stop-Move Detection of Trajectorty Data
    6.1 Cluster-based Detection
    6.2 Physical Model-based Detection
    6.3 Heuristic-based Detection
    6.4 Machine Learning-based Detection

    7. Travel Mode Detection of Trajectorty Data
    7.1 Physical Model-based Detection
    7.2 Machine Learning-based Detection
    7.3 Deep Learning-based Detection

    8. Mobility Data Quality Assessment
    8.1 Six Dimensions in Data Quality
    8.2 Monte Carlo Data Grading Framework

    9. Modifiable Areal Unit Problem
    9.1 Mobility Data Aggregation
    9.2 Error Analysis
    9.3 Grid Shape Impacts

    10. Mobility Data Management and Visualization
    10.1 Mobility Data Management Tools
    10.2 Key Visualization Technologies
    10.3 Monitoring
    10.4 Analysis and Optimization
    10.5 Evaluation strategies involved in evaluating visual interfaces
    10.6 Privacy Protection in Mobile Big Data Mining

Product details

  • No. of pages: 300
  • Language: English
  • Copyright: © Elsevier 2023
  • Published: January 1, 2023
  • Imprint: Elsevier
  • Paperback ISBN: 9780443184284

About the Editor

Haoran Zhang

Haoran (Ronan) Zhang is Assistant Professor in the Center for Spatial Information Science at the University of Tokyo, a Researcher at the School of Business Society and Engineering at Mälardalen University in Sweden, and Senior Scientist at Locationmind Inc. in Japan. His research includes smart supply chain technologies, GPS data in shared transportation, urban sustainable performance, GIS technologies in renewable energy systems, and smart cities. He is author of numerous journal articles and Editorial Board Member of several international academic journals. He has Ph.D.’s in both Engineering and Sociocultural Environment and was awarded Excellent Young Researcher by Japan’s Ministry of Education, Culture, Sports, Science and Technology.

Affiliations and Expertise

Assistant Professor, Center for Spatial Information Science, University of Tokyo, Tokyo, Japan; Researcher, School of Business Society and Engineering, Mälardalen University, Sweden; Senior Scientist, Locationmind Inc., Tokyo, Japan

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