Do geographic features impact pictures location shared on the Web? Modeling photographic suitability in the Swiss Alps

Nowadays, millions of landscape images are uploaded on photosharing platforms such as Flickr or Panoramio. More and more of these images are also accurately geotagged via GPS devices mounted on personal cameras. Each image results from a twofold spatial choice: the choice of the location and the choice of the picture subject. In this study, our focus is on landscape images in large touristic areas. Firstly, our goal is to learn which geographic features play a role in the choice of the location of shared images. For our analysis, we extract a series of geographic features from a Digital Elevation Model (DEM) and a Topographic Landscape Model (TLM) and model the photographic suitability as a density estimation problem in the space of the geographic features. Secondly, each combination of geographic features of a region is associated with a probability to be a location suitable for a photography. The resulting map is useful to promote tourism, to evaluate the landscape attractiveness or with a more technical objective as a prior in close-range photogrammetry. This study shows that databases of geotagged pictures can be used to understand tourists behaviour also in rural areas, even if most of current researches are adressed to cities. The application to a touristic region in the Swiss Alps shows that the proposed method suits well this Geographic OneClass Data problem and is more accurate than both standard KPCA and One-Class SVM to model the suitability for touristic photography at locations unseen during training. As expected, picture locations are mostly correlated with geographic features extracted from the digital elevation model, as well as with those related to accessibility (distance to roads, paths). However, the force of this study is the combination of the geographic features via a kernel method to model more accurately suitable picture locations.