In recent years, the large deployment of mobile devices has led to a massive/nincrease in the volume of records of where people have been and when they were there./nThe analysis of these spatio-temporal data can supply high-level human behavior/ninformation valuable to urban planners, local authorities, and designer of location-based/nservices. In this paper, we describe our approach to collect and analyze the history of/nphysical presence of tourists from the digital footprints they publicly disclose on the web./nOur work takes place in the Province of Florence in Italy, where the insights on the/nvisitors’ flows and on the nationalities of the tourists who do not sleep in town has been/nlimited to information from survey-based hotel and museums frequentation. In fact, most/nlocal authorities in the world must face this dearth of data on tourist dynamics. In this/ncase study, we used a corpus of geographically referenced photos taken in the province/nby 4280 photographers over a period of 2 years. Based on the disclosure of the location/nof the photos, we design geovisualizations to reveal the tourist concentration and spatiotemporal/nflows. Our initial results provide insights on the density of tourists, the points of/ninterests they visit as well as the most common trajectories they follow.