User-Generated Geographic Information for Understanding Human Activities in Nature

In this thesis I have investigated how usergenerated data can be applied to studying human-nature interactions on different spatial and temporal scales. User-generated geographic information refers to spatial data sets generated by and about people, such as social media data, sports tracking data, mobile phone data and participatory geographic information. Users of various digital platforms and mobile devices generate considerable amounts of data about their observations, activities and preferences in different environments. These data can potentially be used to fill information gaps about spatial and temporal patterns of human activities in nature. The aim with this thesis is to gain improved understanding of human-nature interactions based on user-generated geographic information with a focus on social media data from national parks and green spaces. The main objectives are to gain 1) a novel understanding about user-generated data, and 2) insights about human activities in nature on different scales through these questions: Where and when are people visiting nature? What are people doing and valuing in nature? Which users have shared their data from national parks and green spaces? This thesis consists of four articles and an introductory section. Article I provides an overview of social media data sources and analysis methods relevant for nature conservation, and highlights that most of the analytical opportunities are still unexplored in the growing body of literature using social media data in conservation science. Article II compares social media data with national park visitor survey and finds similar trends in both data sources regarding popular activities and visited places. Article III compares methods for detecting national park visitors’ place of residence from geotagged social media and assesses biases that affect the analysis. Article IV compares the use of social media data, sports application data, mobile phone data and participatory geographic information for understanding the use of urban green spaces and suggests that combining information from several sources provides a more comprehensive understanding of green space use and preferences. Overall, user-generated geographic information offers valuable insights about where, when and how people use and value nature, especially from areas that are otherwise difficult to monitor. There are several issues related to data access, bias and privacy in these data. Despite evident limitations, these data contribute to a better understanding of human activities in nature and complement traditional data sources with new and dynamic perspectives. In some areas, user-generated data might be the best available information about human activities. Data comparisons from national parks and green areas presented in this thesis also feed into other fields of research using social media and other user-generated data for studying human spatial behaviour.