This research sheds light on the relationship between the presence of location-based social network (LBSN) data and other economic and demographic variables in the city of Valencia (Spain). For that purpose, a comparison is made between location patterns of geolocated data from various social networks (i.e., Google Places, Foursquare, Twitter, Airbnb and Idealista) and statistical information such as land value, average gross income, and population distribution by age range. The main findings show that there is no direct relationship between land value or age of registered population and the amount of social network data generated in a given area. However, a noteworthy coincidence was observed between Google Places data-clustering patterns, which represent the offer of economic activities, and the spatial concentration of the other LBSNs analyzed, suggesting that data from these sources are mostly generated in areas with a high density of economic activities.

Social media data has frequently sourced research on topics such as traveller planning or the factors that influence travel decisions. The literature on the location of tourist activities, however, is scarce. The studies in this line that do exist focus mainly on identifying points of interest and rarely on the urban areas that attract tourists. Specifically, as acknowledged in the literature, tourist attractions produce major imbalances with respect to adjacent urban areas. The present study aims to fill this research gap by addressing a twofold objective. The first was to design a methodology allowing to identify the preferred tourist areas based on concentrations of places and activities. The tourist area was delimited using Instasights heatmaps information and the areas of interest were identified by linking data from the location-based social network Foursquare to TripAdvisor’s database. The second objective was to delimit areas of interest based on users’ existing urban dynamics. The method provides a thorough understanding of functional diversity and the location of a city’s different functions. In this way, it contributes to a better understanding of the spatial distribution imbalances of tourist activities. Tourist areas of interest were revealed via the identification of users’ preferences and experiences. A novel methodology was thus created that can be used in the design of future tourism strategies or, indeed, in urban planning. The city of Bucharest, Romania, was taken as a case study to develop this exploratory research.

Accessibility to cultural heritage is crucial for fostering inclusive urban environments and preserving historical and cultural identities. This study addresses the gap between heritage conservation and urban accessibility with two objectives: (1) to identify tangible and intangible cultural heritage elements based on user preferences from the social media platform Foursquare, and (2) to assess the impact of accessibility on public engagement using Space Syntax analysis. The historic centres of Valencia and Alicante, Spain, were chosen as case studies for their rich cultural heritage and dynamic urban contexts. A novel urban cultural heritage (UCH) taxonomy was developed to categorise heritage elements into buildings, public spaces, elements, and events/festivities. Findings indicated that social media data offer valuable insights that complement official heritage catalogues, providing a richer understanding of cultural assets and public engagement. The results showed that higher public engagement was concentrated (1) in and around key heritage sites, (2) in heritage sites that combine cultural significance with multifunctional public use, (3) in public spaces and urban nodes that are highly accessible and well connected to the urban structure, (4) in areas where clusters of heritage elements are located close together, and (5) around sites of architectural prominence and cultural significance. This emphasised that accessibility is as important as historical significance for attracting public interest. The study suggested that improving accessibility and integrating social media data with traditional methods can enhance heritage conservation strategies and support sustainable urban development by fostering stronger identity values within cities.

The reuse of Spain’s obsolete railway infrastructure as greenways, namely vías verdes, reflects a Europe-wide territorial strategy, which has resulted in the refurbishment of more than 2500 km of abandoned Spanish railway lines. The potential of these vías verdes as strategical green infrastructure linkers between settlements and their peripheral natural environments is assessed in two Spanish case studies of Girona and Alicante. The territorial elements that affect vías verdes (natural landscape areas, urban settlements and population) are obtained from public administration sources. Additionally, users’ activity through the Wikilock social network is considered. The spatial analysis shows the role of vías verdes in terms of landscape value, accessibility and planning strategy: the itineraries of the vías verdes connect different valuable natural areas with diverse landscape patterns in near proximity to urban nuclei; more than 65% of the population can access a vía verde in less than 200 metres. Moreover, it offers the opportunity to complete a network which could link urban nuclei and their natural periphery through the refurbishment of the remaining stretches. Despite the fact that the full potential of these vías verdes as strategical greenways has not been fully considered in the green infrastructure planning, these corridors could meet environmental, cultural and social sustainable goals.

Metropolitan road axes are spaces of urban centrality and opportunity to promote a greater connectivity between different parts of the urban continuum. In this sense, the functional characterization of six representative axes in Madrid, Barcelona, Paris, London, New York and Mexico City allows obtaining a current analysis of the density and diversity of economic and urban activities to identify key aspects over which to influence to improve their functional and social structure. For this, a method is proposed that adopts the geolocation data from Google Places social network as a main source of information. From the research, important similarities in the functional character of the axes are deduced, among other the predominance of activities related to services and shopping or the greater diversity of economic and urban activities in more central spaces. But differences are also identified, such as the specialization of certain activities characteristic in each metropolitan axis or the differential relationship between population density and the number of activities both in terms of density and linear quantification. All in all, the method proposed opens new possibilities for the strategic planning of economic and urban activities in metropolitan areas.