User-Generated Geographic Information for Understanding Human Activities in Nature

In this thesis I have investigated how user-generated 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.Tämän väitöskirjan tavoitteena on hankkia uutta tietoa ihmisen ja luonnon vuorovaikutussuhteesta sosiaalisen median ja muiden uusien käyttäjälähtöisten paikkatietoaineistojen pohjalta. Tutkimus keskittyy viheralueille ja kansallispuistoihin. Hyödynnän sosiaalisen median aineistoja, sekä muita mobiililaitteiden käytöstä syntyviä aineistoja viheralueiden ja kansallispuistojen käytön tutkimisessa, ja arvioin näiden aineistojen käytettävyyttä maantieteellisen tiedon lähteenä. Tutkimuksen tavoitteena on tarjota menetelmällistä ymmärrystä käyttäjien tuottamien paikkatietoaineistojen hyödyntämisestä luonnonsuojelututkimuksessa, sekä tuottaa tietoa luontovirkistyksen alueellisesta ja ajallisesta vaihtelusta eri mittakaavatasoilla. Tarkastelen tavoitteita seuraavien kysymysten kautta: Missä ja milloin ihmiset viettävät aikaa luonnossa? Mitä ihmiset tekevät viheralueilla ja kansallispuistoissa, ja mitä he näillä alueilla arvostavat? Ketkä jakavat maantieteellistä tietoa luontovierailuistaan? Väitöskirja koostuu johdanto-osiosta ja neljästä osatyöstä. Artikkeli I luo katsauksen sosiaalisen median aineistojen hyödyntämiseen luonnonsuojelututkimuksessa, ja kuvailee keskeiset aineistolähteet ja analyysimenetelmät. Artikkelissa tunnistetaan lähestymistapoja, joiden mahdollisuuksia ei vielä ole täysin hyödynnetty luonnon ja ihmisen vuorovaikutuksen tutkimisessa. Artikkeli II vertailee sosiaalisen median aineistoja kyselytutkimukseen ja kävijätilastoihin Pallas-Yllästunturin kansallispuistosta. Suosituimmat aktiviteetit ja vierailukohteet toistuvat molemmissa aineistoissa. Artikkeli III vertailee aika- ja paikkatietoon pohjautuvia menetelmiä sosiaalisen median käyttäjien kotimaan tunnistamiseen ja arvioi analyysiin liittyviä rajoitteita. Artikkeli IV vertailee sosiaalista mediaa, matkapuhelinaineistoja, urheilusovellusdataa, ja osallistavan paikkatietokyselyn tuloksia kaupungin viheralueiden käytön tutkimisessa. Aineistot tarjoavat toisiaan täydentävää tietoa viheralueiden käytöstä ja arvostuksesta. Käyttäjälähtöiset paikkatietoaineistot auttavat ymmärtämään missä, milloin ja miten ihmiset käyttävät ja arvostavat kansallispuistoja ja viheralueita, erityisesti alueilla joita on muuten hankala monitoroida. Aineistojen epävarma saatavuus kuitenkin rajoittaa näiden aineistojen käyttöä tutkimuksessa. Lisäksi käyttäjäryhmiin ja aineistojen maantieteelliseen kattavuuteen liittyvät vinoumat sekä yksityisyyden suojaan liittyvät kysymykset rajoittavat käytännön sovelluksia. Rajoitteista huolimatta ihmisten itse tuottamat paikkatietoaineistot tarjoavat arvokasta lisätietoa kansallispuistojen ja viheralueiden suunnittelun ja kestävän hallinnan tueksi. Kansallispuistoista ja viheralueilta tuotetut analyysit ja aineistovertailut tarjoavat uutta tietoa myös muille sovellusaloille joilla hyödynnetään uusia aineistoja ihmisten liikkumisen ja aktiviteettien tutkimiseen

Detecting country of residence from social media data : a comparison of methods

Identifying users' place of residence is an important step in many social media analysis workflows. Various techniques for detecting home locations from social media data have been proposed, but their reliability has rarely been validated using ground truth data. In this article, we compared commonly used spatial and Spatio-temporal methods to determine social media users' country of residence. We applied diverse methods to a global data set of publicly shared geo-located Instagram posts from visitors to the Kruger National Park in South Africa. We evaluated the performance of each method using both individual-level expert assessment for a sample of users and aggregate-level official visitor statistics. Based on the individual-level assessment, a simple Spatio-temporal approach was the best-performed for detecting the country of residence. Results show why aggregate-level official statistics are not the best indicators for evaluating method performance. We also show how social media usage, such as the number of countries visited and posting activity over time, affect the performance of methods. In addition to a methodological contribution, this work contributes to the discussion about spatial and temporal biases in mobile big data.Peer reviewe

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

Tropical stream diatom communities – the importance of headwater streams for regional diversity

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Subjective and objective measures of function and return to work : an observational study with a clinical psychiatric cohort

To evaluate the association between two measurement tools (Social and Occupational Functioning Assessment Scale, SOFAS and Sheehan Disability Scale, SDS), returning to work (RTW) and their inter-correlation. 132 psychiatric patients referred to assessment of work ability participated. The association between SOFAS and SDS Work to RTW were assessed by logistic regression. Inter-correlations between SOFAS and SDS were assessed with the Spearman's rho correlation coefficient. SOFAS and SDS Work scores were associated with a 1-year RTW and SOFAS and SDS were inter-correlated. When assigning the ability to work, both subjective and objective measures of function predict RTW.Peer reviewe

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

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.Peer reviewe

Social media reveal that charismatic species are not the main attractor of ecotourists to sub-Saharan protected areas

Charismatic megafauna are arguably considered the primary attractor of ecotourists to sub-Saharan African protected areas. However, the lack of visitation data across the whole continent has thus far prevented the investigation of whether charismatic species are indeed a key attractor of ecotourists to protected areas. Social media data can now be used for this purpose. We mined data from Instagram, and used generalized linear models with site- and country-level deviations to explore which socio-economic, geographical and biological factors explain social media use in sub-Saharan African protected areas. We found that charismatic species richness did not explain social media usage. On the other hand, protected areas that were more accessible, had sparser vegetation, where human population density was higher, and that were located in wealthier countries, had higher social media use. Interestingly, protected areas with lower richness in non-charismatic species had more users. Overall, our results suggest that more factors than simply charismatic species might explain attractiveness of protected areas, and call for more in-depth content analysis of the posts. With African countries projected to develop further in the near-future, more social media data will become available, and could be used to inform protected area management and marketing.Peer reviewe

ES GreenBelt – A preliminary study on spatial data and analysis methods for assessing the ecosystem services and connectivity of the protected areas network of the Green Belt of Fennoscandia

The Green Belt of Fennoscandia forms an ecological network that spans from the Barents Sea all the way to the Baltic Sea. It is a part of the European Green Belt which runs through Europe, starting from the Barents Region and ending in the Balkans. The main body of the Green Belt of Fennoscandia consists of existing and planned protected areas near the shared borders of Finland, Russia and Norway. The green structure between these protected areas also plays a crucial role in the conservation of biodiversity. In addition to environmental values, the environment of the Green Belt of Fennoscandia provides a variety of ecosystem services which are notable on a local, regional and Europe-wide scale. Supplementing the current scientific knowledge base with information on the region’s connectivity and ecosystem services would facilitate the inclusion of these perspectives in the development of the Green Belt of Fennoscandia into a model area for international cross-border nature conservation cooperation. This preliminary study reviews a number of existing spatial data materials and analysis methods for assessing the Green Belt from the perspectives of the connectivity of the protected areas network and the supply and demand of ecosystem services. In addition to this, the study provides recommendations regarding the use of materials and methods, and outlines the contents and structure of a potential study spanning the entire region, as well as an assessment of its realisation schedule. There are a variety of methods for assessing connectivity and ecosystem services. Based on this study, we recommend that the Green Belt should be approached on two different scales: assessments of the general characteristics of the entire Belt should be supplemented with more specific regional assessments. The different parts of the Green Belt differ from one another as regards, for example, vegetation, ecosystems, living environments, population, accessibility, infrastructure and operators. As such, there are also regional differences in the most significant local ecosystem services, their demand and the pressures for change that affect them. We also recommend the use of several different and complementary analysis methods, as none of the analysis methods reviewed alone covers all of the important perspectives related to connectivity and ecosystem services. A great deal of spatial data suitable for use in assessments has been produced about the Green Belt area, but there are problems regarding the accessibility, uniformity, accuracy and regional coverage of these materials. Because of this, the collection and standardisation of materials requires a great deal of work before an overall assessment of the Green Belt can be carried out. It is particularly difficult to find uniform materials that cover all three nations’ areas of the entire Green Belt. The limited regional coverage of the materials also calls for complementary assessments carried out on different scales. An overall assessment of the Green Belt of Fennoscandia area would require a diverse union of different project partners. Access to some materials requires formal agreements and/or actual project cooperation. For cross-border cooperation, we recommend the utilisation of existing personal relationships and contacts between researchers and authorities. In addition to researchers and authorities, there are a large number of private and public operators who possess valuable expertise on the ecosystems, species and biodiversity of the Green Belt, spanning either the entire Green Belt or specific parts thereof

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

Instagram, Flickr, or Twitter : Assessing the usability of social media data for visitor monitoring in protected areas

Social media data is increasingly used as a proxy for human activity in diferent environments, including protected areas, where collecting visitor information is often laborious and expensive, but important for management and marketing. Here, we compared data from Instagram, Twitter and Flickr, and assessed systematically how park popularity and temporal visitor counts derived from social media data perform against high-precision visitor statistics in 56 national parks in Finland and South Africa in 2014. We show that social media activity is highly associated with park popularity, and social media based monthly visitation patterns match relatively well with the ofcial visitor counts. However, there were considerable diferences between platforms as Instagram clearly outperformed Twitter and Flickr. Furthermore, we show that social media data tend to perform better in more visited parks, and should always be used with caution. Based on stakeholder discussions we identifed potential reasons why social media data and visitor statistics might not match: the geography and profle of the park, the visitor profle, and sudden events. Overall the results are encouraging in broader terms: Over 60% of the national parks globally have Twitter or Instagram activity, which could potentially inform global nature conservation.Peer reviewe