Using social media to estimate visitor provenance and patterns of recreation in Germany's national parks. (1st June 2020) - Sinclair, Michael; Mayer, Marius; Woltering, Manuel; Ghermandi, Andrea
Abstract: Social media data are increasingly utilised as a low-cost alternative to visitor surveys in characterising nature-based recreation. However, the information available on individual users is limited and typically does not include provenance, restricting the potential applications and impact of the data. Here we investigate a methodology to estimate social media visitors' home locations at various spatial scales and apply it to the entire network of national parks in Germany. We compare predicted visitor provenance to representative onsite survey data and explore group-specific spatial and temporal patterns of recreation as characterised by users' geotagged photographs. Results show that photograph metadata can be used to assign home locations with accuracies between 62 and 89% depending on spatial scale implemented. Said social media-based predictions are reasonably well representative of the surveyed visitor structure in German national parks with Flickr visitor-days composed of 19% local, 62% non-local German and 19% international visits. Highlights: Photographs metadata can be used to assign home locations of Flickr users. Home locations are predicted with accuracies between 62 and 89% depending on scale. Flickr visits are 19% local, 62% non-local German and 19% international. Flickr photographs can characterize seasonal, weekly and daily visitation patterns. International visitors take more photographs per visit than local visitors.