
Handbook of Mobility Data Mining, Volume 1
Data Preprocessing and Visualization
Haoran Zhang(Editor)
Elsevier (Publisher)
Published on 26. January 2023
Book
Paperback/Softback
222 pages
978-0-443-18428-4 (ISBN)
Description
Handbook of Mobility Data Mining, Volume One: Data Preprocessing and Visualization 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. The book 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. The book contains crucial information for researchers, engineers, operators, administrators, and policymakers seeking greater understanding of current technologies' infra-knowledge structure and limitations.
Further, the book introduces 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 significant challenges faced by the MDM field. This volume focuses on how to efficiently pre-process mobile big data to extract and utilize critical feature information of high-dimensional city people flow. The book first provides a conceptual theory and framework, then discusses data sources, trajectory map-matching, noise filtering, trajectory data segmentation, data quality assessment, and more, concluding with a chapter on privacy protection in mobile big data mining.
Further, the book introduces 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 significant challenges faced by the MDM field. This volume focuses on how to efficiently pre-process mobile big data to extract and utilize critical feature information of high-dimensional city people flow. The book first provides a conceptual theory and framework, then discusses data sources, trajectory map-matching, noise filtering, trajectory data segmentation, data quality assessment, and more, concluding with a chapter on privacy protection in mobile big data mining.
More details
Language
English
Place of publication
Philadelphia
United States
Target group
Professional and scholarly
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
Product notice
Paperback (trade)
Dimensions
Height: 229 mm
Width: 152 mm
Thickness: 12 mm
Weight
304 gr
ISBN-13
978-0-443-18428-4 (9780443184284)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions

E-Book
01/2023
Elsevier
€109.00
Available for download
Person
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 Maelardalen 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.
Editor
Assistant Professor, Center for Spatial Information Science, University of Tokyo, Tokyo, Japan; Researcher, School of Business Society and Engineering, Maelardalen University, Sweden; Senior Scientist, Locationmind Inc., Tokyo, Japan
Content
1. Mobility Data Preprocessing and Visualization: Concept, Theory, and Framework
2. Mobility Data Sources
3. Trajectory Map-Matching
4. Noise Filtering of Mobility Data
5. Trajectory Data Segmentation
6. Stop-Move Detection of Trajectorty Data
7. Travel Mode Detection of Trajectorty Data
8. Mobility Data Quality Assessment
9. Modifiable Areal Unit Problem
10. Mobility Data Management and Visualization
2. Mobility Data Sources
3. Trajectory Map-Matching
4. Noise Filtering of Mobility Data
5. Trajectory Data Segmentation
6. Stop-Move Detection of Trajectorty Data
7. Travel Mode Detection of Trajectorty Data
8. Mobility Data Quality Assessment
9. Modifiable Areal Unit Problem
10. Mobility Data Management and Visualization