Population estimation from mobile network traffic metadata
- 1. Telecom SudParis, CNRS SAMOVAR, University Paris Saclay
- 2. CNR
Description
Please cite our paper if you publish material based on those datasets:
G. Khodabandelou, V. Gauthier, M. El-Yacoubi, M. Fiore, "Estimation of Static and Dynamic Urban Populations with Mobile Network Metadata", in IEEE Trans. on Mobile Computing, 2018 (in Press). 10.1109/TMC.2018.2871156
Abstract
Communication-enabled devices that are physically carried by individuals are today pervasive,
which opens unprecedented opportunities for collecting digital metadata about the mobility of large populations. In this paper, we propose a novel methodology for the estimation of people density at metropolitan scales, using subscriber presence metadata collected by a mobile operator. We show that our approach suits the estimation of static population densities, i.e., of the distribution of dwelling units per urban area contained in traditional censuses. Specifically, it achieves higher accuracy than that granted by previous equivalent solutions. In addition, our approach enables the estimation of dynamic population densities, i.e., the time-varying distributions of people in a conurbation. Our results build on significant real-world mobile network metadata and relevant ground-truth information in multiple urban scenarios.
Dataset Columns
- grid id: the coordinate of the grid can be retrieved with the shapefile of a given city
- timestamp: format Y-M-D H:M:S
- landuse label: the land use label has been computed by through method described in [2]
- population: Census population of a given grid block as defined by the Istituto nazionale di statistica [ISTAT](https://www.istat.it/en/censuses) in 2011
- estimation: Dynamics population estimation as the result of the method described in [1]
The repository
├── datasets
│ ├── Milan_estimation.csv
│ ├── Rome_estimation.csv
│ └── Turin_estimation.csv
└── grid
├── Milan
│ ├── Milan_EPS3003.dbf
│ ├── Milan_EPS3003.prj
│ ├── Milan_EPS3003.qpj
│ ├── Milan_EPS3003.shp
│ └── Milan_EPS3003.shx
├── Rome
│ ├── Rome_EPSG3003.dbf
│ ├── Rome_EPSG3003.prj
│ ├── Rome_EPSG3003.qpj
│ ├── Rome_EPSG3003.shp
│ └── Rome_EPSG3003.shx
└── Turin
├── Turin_EPSG3003.dbf
├── Turin_EPSG3003.prj
├── Turin_EPSG3003.qpj
├── Turin_EPSG3003.shp
└── Turin_EPSG3003.shx
References
[1] G. Khodabandelou, V. Gauthier, M. El-Yacoubi, M. Fiore, "Population estimation from mobile network traffic metadata", in proc of the 17th International Symposium on A World of Wireless, Mobile and Multimedia Networks (WoWMoM), pp. 1 - 9, 2016.
[2] A. Furno, M. Fiore, R. Stanica, C. Ziemlicki, and Z. Smoreda, “A tale of ten cities: Characterizing signatures of mobile traffic in urban areas,” IEEE Transactions on Mobile Computing, Volume: 16, Issue: 10, 2017.
Files
ComplexNetTSP/DynamicPopEst-v1.0.zip
Files
(122.2 kB)
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Additional details
Related works
- Is supplement to
- https://github.com/ComplexNetTSP/DynamicPopEst/tree/v1.0 (URL)
- 10.1109/TMC.2018.2871156 (DOI)
References
- G. Khodabandelou, V. Gauthier, M. El-Yacoubi, M. Fiore, Population estimation from mobile network traffic metadata , in proc of 17th International Symposium on A World of Wireless, Mobile and Multimedia Networks (WoWMoM), pp. 1 - 9, 2016. http://ieeexplore.ieee.org/document/7523554/