Traditionally, urban traveling patterns have been obtained through origin-destination surveys. This method presents drawbacks such as high costs, limited representativeness of the surveyed population, and low spatial and temporal resolution of the results obtained. This study proposes deploying historical data on mobile device geolocalization to depict population displacement patterns with high spatial and temporal resolution levels. As an illustrative example, the traveling patterns were derived for a megacity in Latin America (the metropolitan area of Monterrey, Mexico) with a database of 0.7 million users being monitored during three months. The solutions formulated to tackle the challenges posed by this proposed method are described, as well as the use of the information gathered to obtain dynamic origin-destination matrices, quantify the average number of daily trips and kilometers traveled per inhabitant, attain population density per hour, and to identify the destinations attractor of most trips. We also suggest using this information to assess the impact of massive events such as concerts and sports gatherings on city mobility and air pollution.