THE USE OF CROWDSOURCED GEOGRAPHIC INFORMATION FOR SPATIAL EVALUATION OF CULTURAL ECOSYSTEM SERVICES IN THE AGRICULTURAL LANDSCAPE: THE CASE OF CHIANTI CLASSICO (ITALY)

The use of geo-tagged photographs seems to be a promising alternative to assess Cultural Ecosystem Services CESs in respect to the traditional investigation when focusing on the study of the aesthetic appreciation of a protected area or natural landscape. The aim of this study is integrating the cumulative viewshed calculated from geotagged photo metadata publicly shared on Flickr with raster data on infrastructure, historical sites, and the natural environment, using landscape ecology metrics and RandomForest modelling. Crowdsourced data provided empirical assessments of the covariates associated with visitor distribution, highlighting how changes in infrastructure, crops and environmental factors can affect visitor’s use. These data can help researchers, managers, and public planners to develop projects, and guidelines in the rural landscape for incresing the supply for CESs.

Strategic Sustainable Development Through the Lenses of Tourists’ Preferences: A Geotagged Photo Approach

Knowing tourists’ preferences and experiences with respect to their national park visits is of great importance to implementing strategically sustainable development of national parks. Flickr geotagged photos are utilized and analyzed as our main data source. We included 7090 photos from 626 people in the Great Smoky Mountains National Park to investigate visitors’ behaviors through the presentations of photo spatial and temporal patterns. The results indicated that tourist behaviors that reflect on what they like and enjoy during their park visits can be extracted from geotagged social media data in terms of frequency and length of enjoyment as visitors’ preferred spots.

Personalized Tour Recommender through Geotagged Photo Mining and LSTM Neural Networks

In this study, a tour recommendation system based on social media photos is proposed. The proposed recommendation system can generate trip tours considering both the user’s current location and interests. First, we exploited the geotagged photo dataset from social media websites, which includes photo related information such as user ID numbers, timestamps, hashtags, and GPS coordinates. With this information, the second step is to group photos and identify those places that could be considered relevant for travellers using clustering algorithms. The third step characterizes the resulting clusters by grouping them into different categories using latent dirichlet allocation (LDA) topic modelling approach. The last step is the generation of tours using a long-short term memory neural network (LSTM). The experiments show that the proposed system can be efficient to advise future travellers about the places they would be more likely to visit and arrange trips for them.

Utilizing User Generated Content in the Creation of Land Ownership Boundaries for the Crofters of Scotland

Land registration is important in land tenure security and often resolves land-related issues. Volunteered geographic information is a cheap and quick alternative to formal and traditional approaches to land registration. This research investigates the extent to which this tool is meaningful for land registration, with the Scottish crofting com- munity as a case study. CroftCappture was developed to record points along boundaries and save geotagged photo- graphs and descriptions. The project raised interesting questions over usability, functionality and accuracy, as well issues of privacy, crofting practices, digital competency, and highlighted the fractal nature of the digital divide.