Integration of flows and signals data from mobile phone network for statistical analyses of traffic in a flooding risk area

Perazzini, Selene; Metulini, Rodolfo; Carpita, Maurizio

doi:10.1016/j.seps.2023.101747

Socio-Economic Planning Sciences

2023

DOI: 10.1016/j.seps.2023.101747

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Integration of flows and signals data from mobile phone network for statistical analyses of traffic in a flooding risk area

Selene Perazzini,

Rodolfo Metulini,

Maurizio Carpita

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2024

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Cited by 1 publication

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Traffic flows time series in a flood-prone area: modeling and clustering on extreme values with a spatial constraint

Carpita,

De Luca,

Metulini

et al. 2024

Stoch Environ Res Risk Assess

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Time series of traffic flows, extracted from mobile phone origin–destination data, are employed for monitoring people crowding and mobility in areas subject to flooding risk. By applying a vector autoregressive model with exogenous covariates combined with dynamic harmonic regression to such time series, we detected the presence of many extreme events in the residuals, which exhibit heavy-tailed distribution. For this reason, we propose a time series clustering procedure based on tail dependence which is suitable for data characterized by a spatial dimension, since objects’ geographical proximity is taken into account. The final aim is to obtain clusters of areas characterized by the common tendency to the manifestation of extreme events, that in this case study are represented by extremely high incoming traffic flows. The proposed method is applied to the Mandolossa, a strongly urbanized area located on the western outskirts of Brescia (northern Italy) which is subject to frequent flooding.

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Traffic flows time series in a flood-prone area: modeling and clustering on extreme values with a spatial constraint

Carpita,

De Luca,

Metulini

et al. 2024

Stoch Environ Res Risk Assess

Self Cite

View full text Add to dashboard Cite

show abstract

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Integration of flows and signals data from mobile phone network for statistical analyses of traffic in a flooding risk area

Cited by 1 publication

References 11 publications

Traffic flows time series in a flood-prone area: modeling and clustering on extreme values with a spatial constraint

Traffic flows time series in a flood-prone area: modeling and clustering on extreme values with a spatial constraint

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