Future directions in human mobility science

L Pappalardo, E Manley, V Sekara… - Nature computational …, 2023 - nature.com
We provide a brief review of human mobility science and present three key areas where we
expect to see substantial advancements. We start from the mind and discuss the need to …

A survey on deep learning for human mobility

M Luca, G Barlacchi, B Lepri… - ACM Computing Surveys …, 2021 - dl.acm.org
The study of human mobility is crucial due to its impact on several aspects of our society,
such as disease spreading, urban planning, well-being, pollution, and more. The …

A deep gravity model for mobility flows generation

F Simini, G Barlacchi, M Luca, L Pappalardo - Nature communications, 2021 - nature.com
The movements of individuals within and among cities influence critical aspects of our
society, such as well-being, the spreading of epidemics, and the quality of the environment …

Scikit-mobility: A Python library for the analysis, generation, and risk assessment of mobility data

L Pappalardo, F Simini, G Barlacchi… - Journal of Statistical …, 2022 - jstatsoft.org
The last decade has witnessed the emergence of massive mobility datasets, such as tracks
generated by GPS devices, call detail records, and geo-tagged posts from social media …

Exposure density and neighborhood disparities in COVID-19 infection risk

B Hong, BJ Bonczak, A Gupta… - Proceedings of the …, 2021 - National Acad Sciences
Although there is increasing awareness of disparities in COVID-19 infection risk among
vulnerable communities, the effect of behavioral interventions at the scale of individual …

Mobility trajectory generation: a survey

X Kong, Q Chen, M Hou, H Wang, F **a - Artificial Intelligence Review, 2023 - Springer
Mobility trajectory data is of great significance for mobility pattern study, urban computing,
and city science. Self-driving, traffic prediction, environment estimation, and many other …

Zooming into mobility to understand cities: A review of mobility-driven urban studies

R Wang, X Zhang, N Li - Cities, 2022 - Elsevier
Emerging big datasets about human mobility provide new and powerful ways of studying
cities and addressing various urban issues. However, human mobility has usually been …

Mobility prediction using a weighted Markov model based on mobile user classification

M Yan, S Li, CA Chan, Y Shen, Y Yu - Sensors, 2021 - mdpi.com
The vast amounts of mobile communication data collected by mobile operators can provide
important insights regarding epidemic transmission or traffic patterns. By analyzing historical …

Understanding population movement and the evolution of urban spatial patterns: An empirical study on social network fusion data

Y Cao, Z Hua, T Chen, X Li, H Li, D Tao - Land Use Policy, 2023 - Elsevier
Population movement has become one of the main vehicles for information transfer, factor
flow, and resource allocation between cities. It is also considered as the main way to form …

Spatio-temporal graph learning for epidemic prediction

S Yu, F **a, S Li, M Hou, QZ Sheng - ACM Transactions on Intelligent …, 2023 - dl.acm.org
The COVID-19 pandemic has posed great challenges to public health services, government
agencies, and policymakers, raising huge social conflicts between public health and …