# Estimation of Static and Dynamic Urban Populations with Mobile Network Metadata

arXiv: https://arxiv.org/abs/1810.12909 · HTML: https://mlsanity.com/paper/1810.12909/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 30 Oct 2018.

## Built on by (most cited first, 1 of 1)

- [Zen: LSTM-based generation of individual spatiotemporal cellular traffic with interactions](https://mlsanity.com/paper/2301.02059/) (2023)

## Abstract (arXiv)

Communication-enabled devices routinely carried by individuals have become pervasive, opening 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. Our approach suits the estimation of static population densities, i.e., of the distribution of dwelling units per urban area contained in traditional censuses. More importantly, it enables the estimation of dynamic population densities, i.e., the time-varying distributions of people in a conurbation. By leveraging substantial real-world mobile network metadata and ground-truth information, we demonstrate that the accuracy of our solution is superior to that granted by state-of-the-art methods in practical heterogeneous urban scenarios.