User-Generated Geographic Information for Visitor Monitoring in a National Park: A Comparison of Social Media Data and Visitor Survey

Abstract

Abstract:Protected area management and marketing require real-time information on visitors' behavior and preferences. Thus far, visitor information has been collected mostly with repeated visitor surveys. A wealth of content-rich geographic data is produced by users of different social media platforms. These data could potentially provide continuous information about people's activities and interactions with the environment at different spatial and temporal scales. In this paper, we compare social media data with traditional survey data in order to map people's activities and preferences using the most popular national park in Finland, Pallas-Yllästunturi National Park, as a case study. We compare systematically collected survey data and the content of geotagged social media data and analyze: (i) where do people go within the park; (ii) what are their activities; (iii) when do people visit the park and if there are temporal patterns in their activities; (iv) who the visitors are; (v) why people visit the national park; and (vi) what complementary information from social media can provide in addition to the results from traditional surveys. The comparison of survey and social media data demonstrated that geotagged social media content provides relevant information about visitors' use of the national park. As social media platforms are a dynamic source of data, they could complement and enrich traditional forms of visitor monitoring by providing more insight on emerging activities, temporal patterns of shared content, and mobility patterns of visitors. Potentially, geotagged social media data could also provide an overview of the spatio-temporal activity patterns in other areas where systematic visitor monitoring is not taking place.

Using Volunteered Geographic Information and Nighttime Light Remote Sensing Data to Identify Tourism Areas of Interest

“…It contains rich spatiotemporal information generated by the human sensors and provides a way to explore and understand the socio-economic conditions of a place [26,27]. Though there have been concerns regarding information bias and lack of standard quality control, several studies have empirically revealed that VGI is of equally good quality as authoritative data [8,28,29]. Several researchers have used VGI resources including geo-tagged contents (e.g., tweets and photos) [16][17][18]30], check-in data [18,30], OSM [31] and so on.…”

“…As a boon from the current "Information Age", a massive amount of data is now available via digital technologies and novel data sources [7]. Recent studies have demonstrated that new data sources such as social media can provide more insights in addition to the results from traditional surveys [8]. Paid and free data from online social media sources and remote sensing cater near-real-time data.…”

Identifying Temporal Patterns of Visitors to National Parks through Geotagged Photographs

“…Research has mainly focused on geotagged data from photo-sharing websites such as Flickr and Instagram (no longer available for download). Such data had been used to quantify recreation at natural and cultural sites at a global scale [12], model visitation rates in national parks [20], measure parks' popularity [21], map visitor flows [22,23], identify factors contributing to distribution patterns [11,24], and measure visitor use and spatial patterns [25]. Furthermore, data from web-share services, such as Wikiloc and GPSies, had been used to measure the intensity of use for mountain biking in natural environments [26] and to compare data sources for assessing visitation to parks [27].…”

“…Furthermore, data from web-share services, such as Wikiloc and GPSies, had been used to measure the intensity of use for mountain biking in natural environments [26] and to compare data sources for assessing visitation to parks [27]. Nevertheless, further research on the applicability and validity of social media data as a source of information for visitor monitoring is needed [25].We contribute to the literature by providing an exploratory analysis of the time-based component of geotagged data with three different time measurements; monthly, weekly, and daily, and how well this new source of data matched official visitor data. Several papers in the literature have demonstrated the usefulness of crowdsourced data for behavioral study purposes.…”

Factors Affecting the Number of Visitors in National Parks in the Czech Republic, Germany and Austria

“…Furthermore, Zhang et al [23] analyse a theme park's tourism-carrying capacity (TCC) and devise a conceptual framework that categorizes determinants of TCC on three levels as fundamental, mediating, and direct determinants. To conduct the research, data was collected from questionnaires, social media [24] or publicly accessible databases. The authors in other studies used regressions models [13,25] of visitor numbers.…”