The DOI matches its Crossref record; 105 of the 105 references it cites were found in a registry or an index.
The promises of big data and small data for travel behavior (aka human mobility) analysis
Open accessAbstract
The last decade has witnessed very active development in two broad, but separate fields, both involving understanding and modeling of how individuals move in time and space (hereafter called "travel behavior analysis" or "human mobility analysis"). One field comprises transportation researchers who have been working in the field for decades and the other involves new comers from a wide range of disciplines, but primarily computer scientists and physicists. Researchers in these two fields work with different datasets, apply different methodologies, and answer different but overlapping questions. It is our view that there is much, hidden synergy between the two fields that needs to be brought out. It is thus the purpose of this paper to introduce datasets, concepts, knowledge and methods used in these two fields, and most importantly raise cross-discipline ideas for conversations and collaborations between the two. It is our hope that this paper will stimulate many future cross-cutting studies that involve researchers from both fields.
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Cited by
Tu, W., Cao, J., Yue, Y., Shaw, S.-L., Zhou, M., Wang, Z., Chang, X., Xu, Y., & Li, Q. (2017) · International Journal of Geographical Information Science · doi:10.1080/13658816.2017.1356464 · Cited by 298
Iliopoulou, C., & Kepaptsoglou, K. (2019) · European Transport Research Review · doi:10.1186/s12544-019-0365-5 · Cited by 59
Trackintel: An open-source Python library for human mobility analysis
Martin, H., Hong, Y., Wiedemann, N., Bucher, D., & Raubal, M. (2023) · Computers, Environment and Urban Systems · doi:10.1016/j.compenvurbsys.2023.101938 · Cited by 58
Metadata
- Authors
- Chen, C., Ma, J., Susilo, Y., Liu, Y., & Wang, M.
- Venue
- Transportation Research Part C: Emerging Technologies
- Publisher
- Elsevier BV
- Published
- 2016-07
- Volume
- 68
- Pages
- 285-299
- ISSN
- 0968-090X (ISSN-L)
- OpenAlex
- W2345172924
- Cited by
- 580
- References
- 105
- FWCI
- 75.98
- Type
- journal article
- Language
- en
- Open access
- hybrid
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