Using crowd-sourced photos to assess seasonal patterns of visitor use in mountain-protected areas

Mobile phone data reveals spatiotemporal recreational patterns in conservation areas during the COVID pandemic

Understanding visitation patterns is crucial in developing effective conservation strategies for protected areas, as it serves as an indicator for operating an ecosystem management plan that balances biodiversity and ecosystem services intertwined with public health and social benefits. However, limited data availability during the COVID-19 pandemic has hindered the comprehensive understanding of temporal changes in realized cultural ecosystem services, particularly in recreational activities within these areas. Our study utilized GPS data from mobile phones to quantify visitor characteristics and their contribution to recreational ecosystem services in protected areas at a national scale during the COVID-19 pandemic. We estimated the pandemic's relative impact on visitor patterns at 98 visitor centers in national parks and Ramsar sites in Japan. The total number of visitors and travel distance in various sizes of protected areas decreased after the outbreak of COVID-19. The number of visitors in the protected areas displayed a quick recovery despite the increasing positive COVID-19 cases during the following summer. Post-pandemic, visitors showed a preference for less densely populated protected areas closer to their home range. Our findings partly suggest that protecting a diverse range of conservation areas along the urban gradient could be an effective strategy for maintaining the resilience of recreational services during a prolonged pandemic.

Using cellular device location data to estimate visitation to public lands: Comparing device location data to U.S. National Park Service's visitor use statistics

Understanding human use of public lands is essential for management of natural and cultural resources. However, compiling consistently reliable visitation data across large spatial and temporal scales and across different land managing entities is challenging. Cellular device locations have been demonstrated as a source to map human activity patterns and may offer a viable solution to overcome some of the challenges that traditional on-the-ground visitation counts face on public lands. Yet, large-scale applicability of human mobility data derived from cell phone device locations for estimating visitation counts to public lands remains unclear. This study aims to address this knowledge gap by examining the efficacy and limitations of using commercially available cellular data to estimate visitation to public lands. We used the United States' National Park Service's (NPS) 2018 and 2019 monthly visitor use counts as a ground-truth and developed visitation models using cellular device location-derived monthly visitor counts as a predictor variable. Other covariates, including park unit type, porousness, and park setting (i.e., urban vs. non-urban, iconic vs. local), were included in the model to examine the impact of park attributes on the relationship between NPS and cell phone-derived counts. We applied Pearson's correlation and generalized linear mixed model with adjustment of month and accounting for potential clustering by the individual park units to evaluate the reliability of using cell data to estimate visitation counts. Of the 38 parks in our study, 20 parks had a correlation of greater than 0.8 between monthly NPS and cell data counts and 8 parks had a correlation of less than 0.5. Regression modeling showed that the cell data could explain a great amount of the variability (conditional R-squared = 0.96) of NPS counts. However, these relationships varied across parks, with better associations generally observed for iconic parks. While our study increased our confidence in using cell phone data to estimate visitation, we also became aware of some of the limitations and challenges which we present in the Discussion.

Spatial analysis of cultural ecosystem services using data from social media: A guide to model selection for research and practice

Experiences gained through in person (in-situ) interactions with ecosystems provide cultural ecosystem services. These services are difficult to assess because they are non-material, vary spatially and have strong perceptual characteristics. Data obtained from social media can provide spatially-explicit information regarding some in-situ cultural ecosystem services by serving as a proxy for visitation. These data can identify environmental characteristics (natural, human and built capital) correlated with visitation and, therefore, the types of places used for in-situ environmental interactions. A range of spatial models can be applied in this way that vary in complexity and can provide information for ecosystem service assessments. We deployed four models (global regression, local regression, maximum entropy and the InVEST recreation model) to the same case-study area, County Galway, Ireland, to compare spatial models. A total of 6,752 photo-user-days (PUD) (a visitation metric) were obtained from Flickr. Data describing natural, human and built capital were collected from national databases. Results showed a blend of capital types correlated with PUD suggesting that local context, including biophysical traits and accessibility, are relevant for in-situ cultural ecosystem service flows. Average trends included distance to the coast and elevation as negatively correlated with PUD, while the presence of major roads and recreational sites, population density and habitat diversity were positively correlated. Evidence of local relationships, especially town distance, were detected using geographic weighted regression. Predicted hotspots for visitation included urban areas in the east of the region and rural, coastal areas with major roads in the west. We conclude by presenting a guide for researchers and practitioners developing cultural ecosystem service spatial models using data from social media that considers data coverage, landscape heterogeneity, computational resources, statistical expertise and environmental context.

Volunteered Geographical Information and Recreational Uses within Metropolitan and Rural Contexts

Data obtained through Volunteered Geographical Information (VGI) have gradually been used to monitor and support planning mainly in urban contexts. Regarding recreational activities in peri-urban green and natural areas, VGI has been used to map, measure use intensity, profile users, and evaluate their preferences and motivations. Given their extensive use, it is now worthwhile to assess the value of VGI data to (1) compare recreational uses, profile users and map recreational activities in different contexts (metropolitan vs. rural areas), and (2) evaluate outdoor and adventure tourist products such as Grand Routes (GR). Data from former GPSies (AllTrails nowadays), one of the most popular web-share services, were used to assess recreational uses in Lisbon Metropolitan Area (LMA) and southwest Portugal (SWPT). A set of 22,031 tracks of “on foot” and “on wheels” activities, submitted by 3297 national and foreign users, covering 12 years, was analysed within a GIS modelling environment. Results indicate that, although there are many more submissions in the LMA, the influence of foreigners in the SWPT is higher (11% vs. 19%). The existing GR in SWPT concentrates the foreign use for hiking (71% of foreign vs. 28% of national users), demonstrating its attractiveness. For the favourite activity in both areas—Mountain biking—results show a higher spatial dispersion, yet part of the activity in SWPT still conforms to the GR (16% of foreign and 20% of national use). This study proves other applications for VGI, showing its usefulness for assessing recreational uses in both metropolitan and rural areas. Spatial knowledge about recreational uses is a valuable tool to evaluate and monitor such activities, and to know what users like to do, and where, and is also useful information when designing recreational products considering their tourist potential, thus adding value to these offers.

Outdoor cycling activity affected by COVID-19 related epidemic-control-decisions

Aim

The lockdown of sports infrastructure due to the COVID-19 pandemic has substantially shifted people’s physical activity towards public green spaces. With Germany’s lockdown as one of the more severe governmentally imposed epidemic-control-decisions, we tested to what extent the frequency of outdoor cycling activities changed from March to June 2020.

Methods

User behaviour and frequency in 15 urban and 7 rural German public green spaces was quantified using cycling data from the fitness application Strava. Changes in cycling activities were analysed with four different generalised linear models, correcting for factors like weather conditions and temporal changes in the user base of the fitness application.

Results

We found a clear increase in outdoor cycling sport activities in urban public green spaces in response to epidemic-control decisions (e.g. increase by 81% in April relative to the expected value (95% CI [48%, 110%])). In contrast, biking in rural areas showed no significant change with epidemic-control-decisions in place.

Conclusion

Fitness App data, e.g. from Strava, can be used to monitor visitor behaviour and frequency. The increase in outdoor cycling activities during epidemic control decisions likely reflects a shift of sport activities from indoor and team sports to outdoor and individual sports. This highlights the importance of accessible green space for maintaining physical fitness and health. Beyond this shift, it is likely that outdoor activities may be of particularly importance for stress relief in times of crisis such as the current COVID-19 pandemic.

Exploring the disparities in park accessibility through mobile phone data: Evidence from Fuzhou of China

Parks are a major public service infrastructure for urban residents. Due to the unbalance geographic distribution of public parks within an urban, residents may have uneven access to this service. Despite there has been an efflorescent literature references, there is no consensus on how to properly measure the accessibility of park. The traditional place-based or infrastructure-based approach is often criticized for inappropriately defining spatial units or threshold distances. Taking a fast urbanization region-Fuzhou City, China as a case, this study overcomes this deficiency by employing the method of two-step floating catchment area (2SFCA) to evaluate the park accessibility using mobile phone data (during December 10, 2018 to December 16, 2018), which is people-based information with actual park users' origin-destination trajectory of park users. The results indicate that the threshold distance is 2 km from the visitors' home to park regardless of level, and the total number of visitors is relative fewer in weekend than that in workdays. The spatial distribution of park effective area presents a notably decreasing trend from the urban center to its periphery; however, the spatial distribution of park accessibility is more scattered and irregular. Finally, different key factors of park accessibility are identified for different locations using Geographically weighted regression (GWR) technique. Our study has a good implication for urban park planner and manager to implement differentiated planning policies for parks with full consideration of holistic factors.

Social media reveal ecoregional variation in how weather influences visitor behavior in U.S. National Park Service units

Daily weather affects total visitation to parks and protected areas, as well as visitors’ experiences. However, it is unknown if and how visitors change their spatial behavior within a park due to daily weather conditions. We investigated the impact of daily maximum temperature and precipitation on summer visitation patterns within 110 U.S. National Park Service units. We connected 489,061 geotagged Flickr photos to daily weather, as well as visitors’ elevation and distance to amenities (i.e., roads, waterbodies, parking areas, and buildings). We compared visitor behavior on cold, average, and hot days, and on days with precipitation compared to days without precipitation, across fourteen ecoregions within the continental U.S. Our results suggest daily weather impacts where visitors go within parks, and the effect of weather differs substantially by ecoregion. In most ecoregions, visitors stayed closer to infrastructure on rainy days. Temperature also affects visitors’ spatial behavior within parks, but there was not a consistent trend across ecoregions. Importantly, parks in some ecoregions contain more microclimates than others, which may allow visitors to adapt to unfavorable conditions. These findings suggest visitors’ spatial behavior in parks may change in the future due to the increasing frequency of hot summer days.

Chinese tourists in Nordic countries: An analysis of spatio-temporal behavior using geo-located travel blog data

Geo-located travel blogs, a new data source, enable to achieve more detailed analysis of tourists' spatio-temporal behavior. Taking Chinese tourists in Nordic countries as the research object, this paper focuses on their behavior, seasonal patterns and complex network effects by using geo-located travel blog data collected from Qunar.com. The results show that: (1) Chinese tourists visiting Nordic countries are often experienced in traveling. The local climate during the cold season does not prevent them from pursuing the aurora scenery. (2) The travel behavior of Chinese tourists is spatially heterogeneous. The network analysis reveals that Iceland showcases stronger, compared to the other Nordic countries, community independence and small world effect. (3) During the warm season, Chinese tourists choose a variety of destinations, while in cold season, they tend to choose destinations with higher chances for spotting the northern lights. These results provide helpful information for the tourism management departments of Nordic countries to improve their marketing and development efforts directed for Chinese tourists.

Chinese tourists in Nordic countries: An analysis of spatio-temporal behavior using geo-located travel blog data

Geo-located travel blogs, a new data source, enable to achieve more detailed analysis of tourists' spatio-temporal behavior. Taking Chinese tourists in Nordic countries as the research object, this paper focuses on their behavior, seasonal patterns and complex network effects by using geo-located travel blog data collected from Qunar.com. The results show that: (1) Chinese tourists visiting Nordic countries are often experienced in traveling. The local climate during the cold season does not prevent them from pursuing the aurora scenery. (2) The travel behavior of Chinese tourists is spatially heterogeneous. The network analysis reveals that Iceland showcases stronger, compared to the other Nordic countries, community independence and small world effect. (3) During the warm season, Chinese tourists choose a variety of destinations, while in cold season, they tend to choose destinations with higher chances for spotting the northern lights. These results provide helpful information for the tourism management departments of Nordic countries to improve their marketing and development efforts directed for Chinese tourists.

Chinese tourists in Nordic countries: An analysis of spatio-temporal behavior using geo-located travel blog data

Geo-located travel blogs, a new data source, enable to achieve more detailed analysis of tourists' spatio-temporal behavior. Taking Chinese tourists in Nordic countries as the research object, this paper focuses on their behavior, seasonal patterns and complex network effects by using geo-located travel blog data collected from Qunar.com. The results show that: (1) Chinese tourists visiting Nordic countries are often experienced in traveling. The local climate during the cold season does not prevent them from pursuing the aurora scenery. (2) The travel behavior of Chinese tourists is spatially heterogeneous. The network analysis reveals that Iceland showcases stronger, compared to the other Nordic countries, community independence and small world effect. (3) During the warm season, Chinese tourists choose a variety of destinations, while in cold season, they tend to choose destinations with higher chances for spotting the northern lights. These results provide helpful information for the tourism management departments of Nordic countries to improve their marketing and development efforts directed for Chinese tourists.

Uses and Limitations of Social Media to Inform Visitor Use Management in Parks and Protected Areas: A Systematic Review

Social media are being increasingly used to inform visitor use management in parks and protected areas. We review the state of the scientific literature to understand the ways social media has been, and can be, used to measure visitation, spatial patterns of use, and visitors' experiences in parks and protected areas. Geotagged social media are a good proxy for actual visitation; however, the correlations observed by previous studies between social media and other sources of visitation data vary substantially. Most studies using social media to measure visitation aggregate data across many years, with very few testing the use of social media as a visitation proxy at smaller temporal scales. No studies have tested the use of social media to estimate visitation in near real-time. Studies have used geotags and GPS tracks to understand spatial patterns of where visitors travel within parks, and how that may relate to other variables (e.g., infrastructure), or differ by visitor type. Researchers have also found the text content, photograph content, and geotags from social media posts useful to understand aspects of visitors' experiences, such as behaviors, preferences, and sentiment. The most cited concern with using social media is that this data may not be representative of all park users. Collectively, this body of research demonstrates a broad range of applications for social media. We synthesize our findings by identifying gaps and opportunities for future research and presenting a set of best practices for using social media in parks and protected areas.

Assessing conflicts between winter recreational activities and grouse species

Mountain environments provide habitats for many wild animal species and are of great importance to recreational activities. In the European Alps, winter recreation activities such as ski mountaineering are becoming increasingly popular, which may lead more often to disturbance of Alpine wildlife. Assessment of ski mountaineering activities and related potential conflict zones is needed to implement protection measures and to guide skiers towards nature-friendly behaviour in sensitive locations. Yet basic data regarding frequencies of ski mountaineers is still missing at regional scale. For the Region of the Tyrol (Austria), this study therefore aimed to advance methods of assessing ski mountaineering activities for use in the spatial analysis of conflict zones with grouse species. We overlaid high-resolution information on the spatial and temporal distribution of ski mountaineers from crowd-sourced data (Strava) with distribution maps of capercaillie (Tetrao urogallus L.) and black grouse (Tetrao tetrix L.). Our results indicate that ski mountaineering activities affected 10.3% of the distribution area of black grouse and 8.6% of the distribution area of capercaillie. The raw crowd-sourced data was pre-processed with local information on skiing resorts, cross-country trails and infrastructure and use of the tested method was validated, with good spatial resolution (0.076 km² per minimum mapping unit) for large study areas. We identified four intensity classes of ski mountaineering activity, which were randomly distributed in the study area. The spatial distribution of ski mountaineering activities showed an accumulation of activities in the south of the Inn valley. Our results could provide a valuable basis for developing mitigation measures and strategies in order to reduce the disturbance of Alpine wildlife by ski mountaineering.

Assessing discourses about controversial environmental management issues on social media: Tweeting about wild horses in a national park

Public participation is critical for planning and management of protected areas. With people increasingly using social media, including Twitter, to obtain news and express opinions, park agencies should recognize the utility of monitoring and engaging with this public discourse. We used a conservation culturomics approach to analyse Tweets during a period of controversy about the management of large mammals (horses) in a park (Kosciuszko National Park in Australia), including examining who talked about what, when and what emotions were expressed. An automated programming interface was used to collect metadata for Tweets about the Park, with keywords coded while sentiments and emotions were analysed using a standard lexicon of terms. The debate over introduced wild/feral horses in the Park dominated the discourse, accounting for 56% of the 2085 Tweets referring by name to the Park over 275 days. Many Tweets referred to horses (44.8%) and/or used the alternative term, brumbies (15%). They were more likely to be Retweets, be sent by Australians, with a potential reach of over 5 million followers. Peaks in Tweets related to specific events in the news, with Tweets sent by journalists and others in a professional capacity or specific organisations engaged in the debate more likely to be retweeted. Despite considerable polarisation in the broader debate, including in the traditional media and on other social media platforms, the discourse on Twitter focused mainly on the environmental impacts of horses, and ways to reduce their numbers, rather than wanting to keep horses in the Park. There are important issues with the use of Twitter data including challenges in identifying relevant Tweets, biases in who Tweets and what is retweeted, limited text in Tweets, and increasing focus of the rights to privacy online. Twitter, however, remains a relatively fast, timely and often free way to listen into public debate with a large potential audience, is simple to analyse and hence provides valuable insights into public reactions to park management decisions complementing other data sources.

Evaluating tourist profiles and nature-based experiences in Biosphere Reserves using Flickr: Matches and mismatches between online social surveys and photo content analysis

Monitoring visitor dynamics and their nature-based experiences is an important dimension in the conservation management of protected areas. In the current digital age, the content analysis of social media information is being increasingly used in such a context. However, research testing whether social media content analysis provides similar information to that obtained from stated preference methods is lacking. We aimed to identify differences in the classification of tourist profiles and nature-based experiences, both from online social surveys and photo content analysis. Our approach targeted Flickr's social media users visiting two Biosphere Reserves in Southern Europe: Doñana and Sierra Nevada. We manually classified the main content of Flickr photos considering different categories of tourist profiles and nature-based experiences. Concurrently, we distributed online surveys to Flickr users responsible for those photos and gathered their self-stated classification of tourist profiles and experiences. Finally, we compared the classification results from both content analysis and online surveys using multiple congruence metrics and tests. Overall, we found both matches and mismatches between the results from content analysis and online surveys depending on the categories of tourist profiles and their experiences. "Landscape and species" was the only category with consistent matches between content analysis and online surveys for both tourist profiles and nature-based experiences. We suggest that conclusions based on content analysis or online surveys alone can lead to incomplete information. Instead, the adoption of both content analysis and online surveys should provide complementary perspectives for the monitoring of nature's cultural capital.

Using social media images to assess ecosystem services in a remote protected area in the Argentinean Andes

Social media images are a novel source of data to assess how people view and value the environment. Access to these images is often free, the volume and spread of images is expanding rapidly and hence they are an increasingly valuable source of data complementing and expanding on other data. Recently, coding images has been used to assess sociocultural values relating to ecosystem services including those provided by national parks. To further explore the use of social media images, including for remote environments, we analysed the content of images posted to Flickr by people visiting a national park that contains the highest mountain in the southern hemisphere, Mt. Aconcagua, in Argentina, South America. The saliency of aesthetic landscapes, recreation, social relations and fresh-water provisioning was high across the 334 images posted to Flickr by 104 visitors to the Park, but location mattered. Images from visitors in easily accessible day-use areas were significantly more likely to include content that reflects biodiversity-existence, geology, culture and education services, while the content of images from remote areas was more likely to reflect social relations and fresh-water provision services. Comparisons of the content of images from Mt. Aconcagua with other studies in Europe, South America, Asia, Africa and Australia highlight similarities and differences in people's views of the diversity of locations, but also the benefits and limitations of user-generated social media content when assessing environmental and management issues.

Quantifying tourism booms and the increasing footprint in the Arctic with social media data

Arctic tourism has rapidly increased in the past two decades. We used social media data to examine localized tourism booms and quantify the spatial expansion of the Arctic tourism footprint. We extracted geotagged locations from over 800,000 photos on Flickr and mapped these across space and time. We critically examine the use of social media as a data source in data-poor regions, and find that while social media data is not suitable as an early warning system of tourism growth in less visited parts of the world, it can be used to map changes at large spatial scales. Our results show that the footprint of summer tourism quadrupled and winter tourism increased by over 600% between 2006 and 2016, although large areas of the Arctic remain untouched by tourism. This rapid increase in the tourism footprint raises concerns about the impacts and sustainability of tourism on Arctic ecosystems and communities. This boom is set to continue, as new parts of the Arctic are being opened to tourism by melting sea ice, new airports and continued promotion of the Arctic as a ‘last chance to see’ destination. Arctic societies face complex decisions about whether this ongoing growth is socially and environmentally sustainable.

The State of Mapillary: An Exploratory Analysis

As the world’s largest crowdsourcing-based street view platform, Mapillary has received considerable attention in both research and practical applications. By February 2019, more than 20,000 users worldwide contributed approximately 6.3 million kilometers of streetscape sequences. In this study, we attempted to get a deep insight into the Mapillary project through an exploratory analysis from the perspective of contributors, including the development of users, the spatiotemporal analysis of active users, the contribution modes (walking, cycling, and driving), and the devices used to contribute. It shows that inequality exists in the distribution of contributed users, similar to that in other volunteered geographic information (VGI) projects. However, the inequality in Mapillary contribution is less than in OpenStreetMap (OSM). Compared to OSM, the other main difference is that the data collection demonstrated obvious seasonal variation because contributions to OSM can be accomplished on a computer, whereas images have to be captured on the streets for Mapillary, and this is considerably affected by seasonal weather.