Modelling daily mobility using mobile data traffic at fine
  spatiotemporal scale
Panayotis Christidis Maria Vega Gonzalo Miklos Radics
We applied a data-driven approach that explores the usability of the NetMob
2023 dataset in modelling mobility patterns within an urban context. We
combined the data with a highly suitable external source, the ENACT dataset,
which provides a 1 km x 1km grid with estimates of the day and night population
across Europe. We developed three sets of XGBoost models that predict the
population in each 100m x 100m grid cell used in NetMob2023 based on the mobile
data traffic of the 68 online services covered in the dataset, using the ENACT
values as ground truth. The results suggest that the NetMob 2023 data can be
useful for the estimation of the day and night population and grid cell level
and can explain part of the dynamics of urban mobility.