Exploring human–nature interactions in national parks with social media photographs and computer vision

Understanding the activities and preferences of visitors is crucial for managing protected areas and planning conservation strategies. Conservation culturomics promotes the use of user-generated online content in conservation science. Geotagged social media content is a unique source of in situ information on human presence and activities in nature. Photographs posted on social media platforms are a promising source of information, but analyzing large volumes of photographs manually remains laborious. We examined the application of state-of-the-art computer-vision methods to studying human-nature interactions. We used semantic clustering, scene classification, and object detection to automatically analyze photographs taken in Finnish national parks by domestic and international visitors. Our results showed that human-nature interactions can be extracted from user-generated photographs with computer vision. The different methods complemented each other by revealing broad visual themes related to level of the data set, landscape photogeneity, and human activities. Geotagged photographs revealed distinct regional profiles for national parks (e.g., preferences in landscapes and activities), which are potentially useful in park management. Photographic content differed between domestic and international visitors, which indicates differences in activities and preferences. Information extracted automatically from photographs can help identify preferences among diverse visitor groups, which can be used to create profiles of national parks for conservation marketing and to support conservation strategies that rely on public acceptance. The application of computer-vision methods to automatic content analysis of photographs should be explored further in conservation culturomics, particularly in combination with rich metadata available on social media platforms.Peer reviewe

Understanding the use of urban green spaces from user-generated geographic information

Parks and other green spaces are an important part of sustainable, healthy and socially equal urban environment. Urban planning and green space management benefit from information about green space use and values, but such data are often scarce and laborious to collect. Temporally dynamic geographic information generated by different mobile devices and social media platforms are a promising source of data for studying green spaces. User-generated data have, however, platform specific characteristics that limit their potential use. In this article, we compare the ability of different user-generated data sets to provide information on where, when and how people use and value urban green spaces. We compare four types of data: social media, sports tracking, mobile phone operator and public participation geographic information systems (PPGIS) data in a case study from Helsinki, Finland. Our results show that user-generated geographic information sources provide useful insights about being in, moving through and perceiving urban green spaces, as long as evident limitations and sample biases are acknowledged. Social media data highlight patterns of leisure time activities and allow further content analysis. Sports tracking data and mobile phone data capture green space use at different times of the day, including commuting through the parks. PPGIS studies allow asking specific questions from active participants, but might be limited in spatial and temporal extent. Combining information from multiple user-generated data sets complements traditional data sources and provides a more comprehensive understanding of green space use and preferences.Peer reviewe

Assessing global popularity and threats to Important Bird and Biodiversity Areas using social media data

Understanding worldwide patterns of human use of sites of international significance for biodiversity conservation is crucial for meeting global conservation targets. However, robust global datasets are scarce. In this study, we used social media data, mined from Flickr and Twitter, geolocated in Important Bird and Biodiversity Areas (IBAs) to assess i) patterns of popularity; ii) relationships of this popularitywith geographical and biological variables; and iii) identify sites under high pressure fromvisitors. IBAs located in Europe and Asia, and in temperate biomes, had the highest density of users. Sites of importance for congregatory species, which were also more accessible, more densely populated and provided more tourism facilities, received higher visitation than did sites richer in bird species. Wefound 17% of all IBAs assessed to be under very high threat also received high visitation. Our results showinwhich IBAs enhancedmonitoring should be implemented to reduce potential visitation risks to sites of conservation concern for birds, and to harness the potential benefits of tourism for conservation. (C) 2019 The Authors. Published by Elsevier B.V.Peer reviewe

Green environment and incident depression in South Africa : a geospatial analysis and mental health implications in a resource-limited setting

Our results imply the importance of green environments for mental wellbeing in sub-Saharan African settings experiencing rapid urbanisation, economic and epidemiological transition, reaffirming the need to incorporate environmental services and benefits for sustainable socioeconomic development.Peer reviewe