Visualizing the Invisible Image of Cities

With the recent advances in technology, we have the opportunity to study the city dynamics at a large scale. A fundamental step is to be able to sense extensive areas. Participatory sensor networks have the potential to become a very fundamental tool to study social behavior at a large scale. Currently, there are some location sharing services, such as Foursquare, that record the user´s location along the time, which is clearly one of dimensions in the city dynamics. In this work, we propose a technique called city image and show its applicability taking as examples eight different cities. The resulting image is a way of summarizing the city dynamics based on transition graphs, which map the movements of individuals in a PSN. This technique is a promising way to better understand the city dynamics, helping us to visualize the invisible images of cities.