  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.
