Consiglio Nazionale delle Ricerche

Tipo di prodottoContributo in atti di convegno
TitoloFusing GPS probe and mobile phone data for enhanced land-use detection
Anno di pubblicazione2017
Autore/iFurno A.; Faouzi N.-E.E.; Fiore M.; Stanica R.
Affiliazioni autoriUniv Lyon, ENTPE, IFSTTAR, LICIT UMR-T 9401, Lyon, F-69518, France; CNR-IEIIT, Corso Duca degli Abruzzi 24, Torino, 10129, Italy; Univ Lyon, INSA-Lyon, INRIA, CITI, Villeurbanne, F-69621, France
Autori CNR e affiliazioni
  • inglese
AbstractProfiling the diversity of land use in modern cities by mining data related to human mobility represents a challenging problem in urban planning, transportation and smart city management. Previous work on mobile phone data (i.e., Call Detail Records) has shown the existence of strong correlations between the urban tissue and the associated mobile communication demand. Similarly, GPS traces of vehicles convey information on transportation demand and human activities that can be related to the land use of the neighborhood where they take place. In this paper, we investigate the land use patterns that emerge when studying simultaneously GPS traces of probe vehicles and mobile phone data collected by network providers. To this end, we extend previous definitions of mobile phone traffic signatures for land use detection, so as to incorporate additional information on human presence and mobility conveyed by GPS traces of vehicles. Leveraging these extended signatures, we exploit an unsupervised learning technique to identify classes of signatures that are distinctive of different land use. We apply our technique to real-world data collected in French and Italian cities. Results unveil the existence of signatures that are common to all studied areas and specific to particular land uses. The combined use of mobile phone data and GPS traces outperforms previous approaches when confronted to ground-truth information, and allows characterizing land use in greater detail than in the literature to date.
Lingua abstractinglese
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Pagine da696
Pagine a698
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  • IEEE, New York (Stati Uniti d'America)
Verificato da refereeSì: Internazionale
Stato della pubblicazionePublished version
Indicizzazione (in banche dati controllate)
  • Scopus (Codice:2-s2.0-85030218876)
Parole chiaveLand use detection, Exploratory Factor Analysis, Data fusion
Link (URL, URI)-
Titolo convegno/congressoIEEE International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS)
Luogo convegno/congressoNaples, Italy
Data/e convegno/congresso26-28/06/2017
Titolo parallelo-
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Strutture CNR
  • IEIIT — Istituto di elettronica e di ingegneria dell'informazione e delle telecomunicazioni
Moduli CNR-
Progetti Europei