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A Review of the Effects of Climate Change on Visitor Use in US Public Lands and Waters
Figure 1. A conceptual diagram of how climate change is affecting visitor use in public lands and waters, and how changes to visitor use can affect operations of public lands and waters. NPS Climate change is affecting recreational visitor use in U.S. public lands and waters, causing changes to visitation levels, timing of trips, activity participation, and visitor safety. This report reviews the literature on how climate change is influencing visitor use in the United States and how visitor use may be affected in the future. Our goal is to provide the current state of the literature for managers of public lands and waters and provide foundational information for the development of a climate change vulnerability assessment methodology for visitor use within the National Park Service (that may be applicable to other federal lands and waters). Specifically, we investigate how seven different climate change factors may affect visitor use on public lands and waters. These factors consist of increasing temperatures; flooding, drought, and increased variability of precipitation; decreasing snowpack and earlier spring runoff; wildfires, smoke, and air quality; coastal hazards: hurricanes and sea level rise; harmful algal blooms (HABs); and zoonotic and vector-borne disease. The current research indicates that these factors are already affecting visitors to public lands and waters and continued effects in the future are likely as the climate warms. Additionally, we summarize existing research on how visitors to U.S. public lands and waters are adapting to climate change. Throughout the review, we note where there are substantial gaps in the literature and more research would help managers respond to the effects of climate change on visitor use.
Read moreAdapting Visitor Use Management Under a Changing Climate Across the U.S. National Park System Author Links Open Overlay Panel
Research shows that climate change is already affecting both resources and visitors in U.S. National Parks. We sought to better understand if and how park staff across the National Park Service are adapting to climatic changes that affect visitor use, as well as barriers and challenges to adaptation and information needs. We conducted semi-structured qualitative interviews with 63 staff from 31 representative national park units across the United States. We qualitatively coded interviews for themes using deductive and inductive coding approaches. Results indicate that park staff are already taking action to adapt to changes that are affecting visitor use, including efforts to increase resiliency of infrastructure and to support the health and safety of visitors (e.g., increased communication, preventative search and rescue, changes to programming). Common barriers and challenges include institutional factors (such as funding, staffing capacity, and shifting priorities), uncertainty about future conditions, and difficulties with prioritizing climate adaptation. Park staff relayed varied needs for data, tools, and information, but commonly indicated a need for social science data and tools to help synthesize, standardize, and translate climate information. These results provide insights into current actions park staff are taking to adapt to climate change and what resources may be helpful in the future to lower the challenges and barriers to adaptation. Highlights Climate change is affecting visitor use in U.S. National Park Service (NPS) units. NPS staff are taking actions to respond and adapt to the effects on visitor use. Actions are related to visitor infrastructure, safety, and services, among others. Challenges to visitor use adaptation include funding, staffing & future uncertainty. Staff report needing social science data and tools to translate data to action.
Read moreCharacterizing Social and Ecological Values Expressed in US Forest Service Public Comments Using a Computational Approach
Addressing social and ecological values is a central aim of democratic environmental management and policymaking, especially during deliberative and participatory processes. Agencies responsible for managing public lands would benefit from a deepened understanding of how various publics value those lands. Federal land management agencies receive millions of written comments from the public on proposed management actions annually, providing a unique source of insights into how the public assigns value to public lands. To date, little attention has been directed towards methods for analysing the public’s comments to understand their expressed values, in part because the volume of comments often makes manual analysis unworkable. This study introduces and applies a novel computational approach to inferring values in written text by using natural language processing and a method that combines a lexicon with semantic embedding models. We developed embedding models for four types of values that are expressed in public comments. We then fit models to 409,241 public comments on actions proposed by the United States Forest Service from 2011 to 2020 and regulated by the National Environmental Policy Act. The embedding model generally outperformed the lexicon word-count, particularly for value types with shorter lexicons, and, like human evaluators, the embedding models performed better for more evident values and were less reliable for more abstract or latent values. By applying the resulting model, we furthered our understanding of how the public values National Forest lands in the United States. We observed that aesthetic and moral values were expressed more often in comments for projects that received more public interest, as gauged by the number of comments a project received and in comments for projects addressing recreational management. Related Media Plain Language Summary: A computational approach for characterizing values for nature: A case study with US Forest Service public comments. (May 5, 2025)
Read moreLeveraging Digital Mobility Data to Estimate Visitation in National Wildlife Refuges
Figure 6. Predictive power (R2) of nine different visitation models. The first (Mobility + Refuge) is the combined model that uses all the digital mobility data and a fixed effect for refuge. The second (Mobility) uses all the digital mobility data but does not include an effect for refuge. Each bar shows the amount of variability that is explained by each predictor in that model, calculated as the General Dominance. The other columns are the total R2 values of simple linear regression models which regressed a single predictor against observed visits. They are named for the model predictor. The US Fish and Wildlife Service manages over 500 National Wildlife Refuges and dozens of National Fish Hatcheries across the United States. Accurately estimating visitor numbers to these areas is essential for understanding current recreation demand, planning for future use, and ensuring the ongoing protection of the ecosystems that refuges safeguard. However, accurately estimating visitation across the entire refuge system presents significant challenges. Building on previous research conducted on other federal lands, this study evaluates methods to overcome constraints in estimating visitation levels using statistical models and digital mobility data. We develop and test a visitation modeling approach using multiple linear regression, incorporating predictors from eight mobility data sources, including four social media platforms, one community science platform, and three mobile device location datasets from two commercial vendors. We find that the total number of observed visitors to refuges correlates with the volume of data from each mobility data source. However, neither social media nor mobile device location data alone provide reliable proxies for visitation due to inconsistent relationships with observed visitation; these relationships vary by data source, refuge, and time. Our results demonstrate that a visitation model integrating multiple mobility datasets accounts for this variability and outperforms models based on individual mobility datasets. We find that a refuge-level effect is the single most important predictor, suggesting that including site characteristics in future models will make them more generalizable. We conclude that statistical models which incorporate digital mobility data have the potential to improve the accuracy of visitor estimates, standardize data collection methods, and simplify the estimation process for agency staff.
Read moreNational Park Service Staff Perspectives on How Climate Change Affects Visitor Use
Three bikers traveling through the Swan Lake area at Yellowstone National Park in the spring. As temperatures increase due to climate impacts, shoulder seasons in parks may allow for more warm-weather activities. Credit: NPS / Jacob W. Frank. Many public lands, including those managed by the U.S. National Park Service (NPS), have the purpose of conserving natural and cultural resources and providing opportunities for visitors to recreate in and enjoy these areas. Achieving this mission becomes more challenging as drought, flooding, increasing temperatures and other climatic change effects are impacting NPS lands and visitors and affecting factors such as visitation, recreation access and health and safety among other aspects of park operations. However, the literature lacks insights from staff dealing with on-the-ground climate impacts to visitor use. To address this gap, we held semi-structured interviews with 63 staff from 31 NPS units across the United States (U.S.) to better understand the effects of climate change on visitor use. We qualitatively analysed the interviews using both deductive and inductive methods to identify key themes. Interview participants consistently noted that climate change is already affecting visitor use at their parks. For instance, increasing temperatures are negatively affecting both staff and visitor safety at parks nationwide, whereas all coastal parks within our sample are already experiencing impacts from sea-level rise or more frequent and severe coastal storms and hurricanes. Other impacts include reduced recreational access, damaged infrastructure and cultural resources and diminished visitor experiences due to fire and smoke. Similarly, concerns about future impacts often revolved around the health and safety of visitors and staff—particularly related to wildfire and smoke, water quality and availability, and increased heat—and climate change forever altering parks. Our research shows staff in parks and protected areas are noticing effects of climate change on visitor use; some of these impacts have not been previously documented in the scientific literature. Study results highlight future visitor use management research needs and key topics to consider for visitor use planning processes.
Read moreA National Model for Estimating US Public Land Visitation
Figure 1. Map of study locations and regions, colored by management agency. Shaded areasshow unit boundaries for units which are larger than the points. Public land management relies on accurate visitor counts in order to understand and mitigate environmental impacts and to quantify the value of ecosystem services provided by natural areas. We built and tested predictive visitation models suitable for publicly-managed parks, open space and other protected lands based on multiple sources of digital mobility data including posts to social media, recreation report platforms, and a cellular device location dataset from a commercial vendor. Using observational visitation data series from the United States’ National Park Service, Forest Service and Fish and Wildlife Service, we quantified the accuracy of statistical models to predict on-the-ground visitation using individual and combined sources of locational data. We found the predictive models performed best in settings where some on-site visitation data can be integrated into the models. On-site visitation data helps to account for meaningful differences in modeled relationships both within and across the three agencies considered. We found variation in the usefulness of the digital mobility data sources, with models combining multiple data sources outperforming those using a single source, including those based solely on cellular device locations. We discuss the practical implications of these findings as well as paths forward to improve visitation estimation on public lands by incorporating digital mobility data.
Read moreThe Influence of Wildfire Risk Reduction Programs and Practices on Recreation Visitation
Figure 1. Area within the Deschutes Skyline Collaborative ForestLandscape Restoration Project (in blue) compared with the area of the remainder of the Deschutes National Forest (in green). Map made in QGIS v 3.30. Background The increasing extent and severity of uncharacteristic wildfire has prompted numerous policies and programs promoting landscape-scale fuels reduction. Aims We used novel data sources to measure how recreation was influenced by fuels reduction efforts under the US Forest Service Collaborative Forest Landscape Restoration (CFLR) Program. Methods We used posts to four social media platforms to estimate the number of social media user-days within CFLR landscapes and asked: (1) did visitation within CFLR Program landscapes between 2012 and 2020 change in a manner consistent with the pattern on nearby lands, and (2) was there a relationship between the magnitudes of specific fuel treatment activities within CFLR landscapes and visitation to that landscape? Key results In aggregate, visitation to the CFLR landscapes changed at a rate mirroring the trend observed elsewhere. Within CFLR landscapes, pre-commercial thinning and pruning had slight positive influences on visitation whereas prescribed burning and managed wildfire had slight negative influences. Conclusions Fuel treatments can have a modest influence on visitation, but we didnot find any wholesale changes in visitation within CFLR landscapes. Implications Social media and other novel data sources offer an opportunity to fill in gaps in empirical data on recreation to better understand social-ecological system linkages.
Read moreA Text-Messaging Chatbot to Support Outdoor Recreation Monitoring Through Community Science
Figure 1. Volunteer participation rates at sites grouped by parking lot size (small, medium, and large). Participation rates were statistically significantly higher at sites with small parking lots (a) compared to medium and large lots (b). There was no significant difference in participation rates between sites with large- and medium-sized parking lots (b). Public land managers depend on reliable and readily available data about outdoor recreation in parks and greenspaces. However, traditional recreation monitoring techniques including visitor surveying and counting cannot be implemented over large spatial and temporal scales, especially in remote and undeveloped settings where monitoring is costly. To fill these data gaps, and thereby inform decision-making, this study develops and tests the efficacy of a novel recreation monitoring technique that engages visitors in data collection using a chatbot and text-messages. Drawing on knowledge and methods from community science and crowdsourcing, we present a relatively low-cost and low-barrier approach to counting and characterizing recreational visits on public lands. In an 18-month pilot implementation on a national forest in Washington, USA, we found that crowdsourced data collected using the chatbot were consistent with results of controlled counts and in-person surveys. Furthermore, some sites received relatively high participation rates, up to 12% of recreating parties, regardless of cellular connectivity at the site. This study, which is the first to engage public land usersin community science using a text-messaging chatbot for the purposes of studying outdoor recreation, demonstrates the potential for technology to support new community science approaches that involve visitors in land stewardship and the development of recreation monitoring systems.
Read moreModeling and Forecasting Percent Changes in National Park Visitation Using Social Media
Figure 1. Yellowstone National Park time series decomposition of National Park Service (NPS) counts. National parks have tremendous cultural, ecological, and economic value to societies. In order to manage and maintain these public spaces, decision-makers rely on detailed information about park use and park condition. Many parks, however, lack precise visitor counts because of challenges associated with monitoring large and inaccessible areas with porous boundaries. To facilitate better management, we propose a method to estimate percentage changes in park visitation without using any on-site visitor counts. Specifically, using 20 national parks in the United States, we develop a time series model for forecasting future monthly changes in visitation based on the volume of social media images shared by visitors to parks. Forecasts are generated from historic park-level and national-level photo-user-days (PUD) of images posted to Flickr, using singular spectrum analysis (SSA). We further propose an approach for augmenting existing on-site visitation data collected by the US National Park Service. Our model evaluations indicate that the proposed model that only uses social media data achieves competitive performance to the models which partially or fully utilizes on-site visitor counts.
Read moreSocial Media Data for Environmental Sustainability: A Critical Review of Opportunities, Threats, and Ethical Use
Figure 1. A virtuous cycle for social media (SM) data andsustainability through transparency, inclusivity, and responsibledata use Social media data are transforming sustainability science. However, challenges from restrictions in data accessibility and ethical concerns regarding potential data misuse have threatened this nascent field. Here, we review the literature on the use of social media data in environmental and sustainability research. We find that they can play a novel and irreplaceable role in achieving the UN Sustainable Development Goals by allowing a nuanced understanding of human-nature interactions at scale, observing the dynamics of social-ecological change, and investigating the co-construction of nature values. We reveal threats to data access and highlight scientific responsibility to address trade-offs between research transparency and privacy protection, while promoting inclusivity. This contributes to a wider societal debate of social media data for sustainability science and for the common good.
Read moreWhere Wilderness is Found: Evidence From 70,000 Trip Reports
Figure 1. The study area, showing the boundaries of the Mt. Baker-Snoqualmie National Forest, wilderness areas within it and the trailheads for the 470 hikes in the Washington Trails Association hiking guide that we included in the sample. Map created with the R programming language using the sf, ggspatial and cowplot packages (Dunnington, 2022; Pebesma & Bivand, 2023; R Core Team, 2022; Wilke, 2019). Data from USDA Forest Service, Washington Trails Association, Washington Department of Transportation, Environmental Systems Research Institute map service and Natural Earth, facilitated by the basemaps and rnaturalearth packages for R (ESRI, 2009; Massicotte & South, 2023; Schwalb-Willmann, 2022; USDA Forest Service, 2019; WSDOT, 2023; WTA, 2023c). 1. Outdoor recreation is an essential way many people engage with nature. The provision of public spaces for recreation intersects with conservation practices motivated by intertwined social and ecological values, such as strict practices associated with the concept of ‘wilderness’. Debates persist about how such concepts and management practices influence people’s recreation experiences. 2. Many US public land management agencies facilitate opportunities for outdoor recreation, relying on management frameworks and tools intended to foster specific experiential qualities. But these frameworks and tools assume simplistic relationships between settings and people’s experiences, and managers rarely assess these relationships. 3. This study uses a data set of nearly 70,000 crowdsourced trip reports from a hiking website to understand the qualities of visitors’ experiences on trails. We study the geographic distribution of experiential qualities commonly associated with US wilderness areas: aesthetics, awe, challenge, pristineness, quietness, solitude and timelessness. Using analytical methods that rely on machine learning and natural language processing, we identify these experiential qualities in trip reports from hundreds of routes, and use generalized linear models to analyse relationships between the frequency of each experiential quality and the route’s administrative, built, biophysical, geographic and social settings. 4. We find that four of the seven experiential qualities (aesthetics, awe, challenge and solitude) are commonly described in trip reports, each appearing in 15%–55% of manually coded reports. The extent to which setting characteristics explained variability in experiences differed, ranging from 34% of the variability in the proportion of trip reports describing aesthetics to 55% for awe. The setting characteristics associated with each experiential quality also differed, with characteristics such as trail mileage and summit destinations having stronger influences on experiential qualities than characteristics such as wilderness designation. 5. Synthesis and applications. Our findings suggest the need to consider more diverse variables in experience–setting relationships, develop more robust models to characterize those relationships and create new data sources to represent understudied variables. These advances would help empirically inform and improve frameworks and tools used for recreation and wilderness planning and monitoring, and potentially promote more responsive management to evolving social– ecological values.
Read moreAn Open‐Source Image Classifier for Characterizing Recreational Activities Across Landscapes
Environmental management increasingly relies on information about ecosystem services for decision-making. Compared with regulating and provisioning services, cultural ecosystem services (CES) are particularly challenging to characterize and measure at management-relevant spatial scales, which has hindered their consideration in practice. Social media are one source of spatially explicit data on where environments support various types of CES, including physical activity. As tools for automating social media content analysis with artificial intelligence (AI) become more commonplace, studies are promoting the potential for AI and social media to provide new insights into CES. Few studies, however, have evaluated what biases are inherent to this approach and whether it is truly reproducible. This study introduces and applies a novel and open-source convolutional neural network model that uses computer vision to recognize recreational activities in the content of photographs shared as social media. We train a model to recognize 12 common recreational activities to map one aspect of recreation in a national forest in Washington, USA, based on images uploaded to Flickr. The image classifier performs well, overall, but varies by activity type. The model, which is trained with data from one region, performs nearly as well in a novel region of the same national forest, suggesting that it is broadly applicable across similar public lands. By comparing the results from our CNN model with an on-site survey, we find that there are apparent biases in which activities visitors choose to photograph and post to social media. After considering potential issues with underlying data and models, we map activity diversity and find that natural features (such as rivers, lakes and higher elevations) and some built infrastructure (campgrounds, trails, roads) support a greater diversity of activities in this region. We make our model and training weights available in open-source software, to facilitate reproducibility and further model development by researchers who seek to understand recreational values at management-relevant scales—and more broadly provide an example of how to build, test and apply AI to understand recreation and other types of CESs.
Read moreBiodiversity and Infrastructure Interact to Drive Tourism to and Within Costa Rica
Costa Rica. Credit: Domenico Convertini, flickr Nature-based tourism has potential to sustain biodiversity and economic development, yet the degree to which biodiversity drives tourism patterns, especially relative to infrastructure, is poorly understood. Here, we examine relationships between different types of biodiversity and different types of tourism in Costa Rica to address three questions. First, what is the contribution of species richness in explaining patterns of tourism in protected areas and country-wide in Costa Rica? Second, how similar are the patterns for birdwatching tourism compared to those of overall tourism? Third, where in the country is biodiversity contributing more than other factors to birdwatching tourism and to overall tourism? We integrated environmental data and species occurrence records to build species distribution models for 66 species of amphibians, reptiles, and mammals, and for 699 bird species. We used built infrastructure variables (hotel density and distance to roads), protected area size, distance to protected areas, and distance to water as covariates to evaluate the relative importance of biodiversity in predicting birdwatching tourism (via eBird checklists) and overall tourism (via Flickr photographs) within Costa Rica. We found that while the role of infrastructure is larger than any other variable, it alone is not sufficient to explain birdwatching and tourism patterns. Including biodiversity adds predictive power and alters spatial patterns of predicted tourism. Our results suggest that investments in infrastructure must be paired with successful biodiversity conservation for tourism to generate the economic revenue that countries like Costa Rica derive from it, now and into the future.
Read moreThe Relationship Between Natural Environments and Subjective Well-Being as Measured by Sentiment Expressed on Twitter
Fig. 1. (A) The spatial distribution of tweets in the sample. (B) Land cover in Seattle. (C) Tree canopy coverage in Seattle. (D) Parks in Seattle. Land-cover and tree-canopy data were taken from the 2016 National Land Cover Database (NLCD) (Dewitz, 2019). Polygons representing urban parks within Seattle were downloaded from Seattle GeoData portal (Seattle Parks, 2012). There is growing evidence that time spent in nature can affect well-being. Nonetheless, assessing this relationship can be difficult. We used 1,971,045 geolocated tweets sent by 81,140 users from Seattle, Washington, USA to advance our understanding of the relationship between subjective well-being and natural environments. Specifically, we quantified the relationships between sentiment (negative/neutral/positive) expressed in geolocated tweets and their surrounding environments, focusing on three environmental indicators: land-cover type, tree-canopy density, and urban parks. We allowed the relationships to vary according to the broader type of environment (i.e., land-use zoning). We estimated three random-intercept partial proportional odds models corresponding to the three environmental indicators while controlling for multiple covariates. Our results suggested that for a given land-use type, tweets sent from some natural land-cover types were less likely to be negative compared to tweets sent from the urban built land-cover type. For tweets sent in industrial zones, an increase in tree-canopy cover was associated with a lower probability of having negative sentiments and with a higher probability of having positive sentiments; but for tweets sent in commercial/mixed zones, the association was reversed. Also, urban parks were generally associated with a lower probability of having negative sentiments, but tweets sent from large natural parks in residential zones were less likely to be positive. Our results suggest that the relationship between subjective well-being and natural environments depends on where people are situated in the built environment and may be more complex than previously thought. The more nuanced understanding provided by analyzing geolocated social media has potential to inform urban planning and land management.
Read moreAdvancing Sustainable Development and Protected Area Management with Social Media-Based Tourism Data
Figure 1. The Bahamian archipelago, including the network of marine protected areas (orange boundaries), geotagged Flickr photos (purple points), and Andros, the largest island in The Bahamas. Politically considered a single island, Andros is in fact comprised of three major landmasses, North Andros (which contains the districts of North Andros and Central Andros), Mangrove Cay, and South Andros. Sustainable tourism involves increasingly attracting visitors while preserving the natural capital of a destination for future generations. To foster tourism while protecting sensitive environments, coastal managers, tourism operators, and other decision-makers benefit from information about where tourists go and which aspects of the natural and built environment draw them to particular locations. Yet this information is often lacking at management-relevant scales and in remote places. We tested and applied methods using social media as data on tourism in The Bahamas. We found that visitation, as measured by numbers of geolocated photographs, is well correlated with counts of visitors from entrance surveys for islands and parks. Using this relationship, we predicted nearly 4 K visitor-days to the network of Bahamian marine protected areas annually, with visitation varying more than 20-fold between the most and least visited parks. Next, to understand spatial patterns of tourism for sustainable development, we combined social media-based data with entrance surveys for Andros, the largest island in The Bahamas. We estimated that tourists spend 125 K visitor-nights and more than US$45 M in the most highly visited district, five times that of the least visited district. We also found that tourists prefer accessible, natural landscapes—such as reefs near lodges—that can be reached by air, roads, and ferries. The results of our study are being used to inform development and conservation decisions, such as where to invest in infrastructure for visitor access and accommodation, siting new marine protected areas, and management of established protected areas. Our work provides an important example of how to leverage social media as a source of data to inform strategies that encourage tourism, while conserving the environments that draw visitors to a destination in the first place.
Read moreAn Ecosystem Service Perspective on Urban Nature, Physical Activity, and Health
Figure 1. Conceptual model of the relationships among urban nature (as part of the urban system), PA (quantity and quality), and health, alignedwith an ecosystem service approach. Numbers correspond with The Current State of Knowledge points 1 and 2. Nature underpins human well-being in critical ways, especially in health. Nature provides pollination of nutritious crops, purification of drinking water, protection from floods, and climate security, among other well-studied health benefits. A crucial, yet challenging, research frontier is clarifying how nature promotes physical activity for its many mental and physical health benefits, particularly in densely populated cities with scarce and dwindling access to nature. Here we frame this frontier by conceptually developing a spatial decision-support tool that shows where, how, and for whom urban nature promotes physical activity, to inform urban greening efforts and broader health assessments. We synthesize what is known, present a model framework, and detail the model steps and data needs that can yield generalizable spatial models and an effective tool for assessing the urban nature–physical activity relationship. Current knowledge supports an initial model that can distinguish broad trends and enrich urban planning, spatial policy, and public health decisions. New, iterative research and application will reveal the importance of different types of urban nature, the different subpopulations who will benefit from it, and nature’s potential contribution to creating more equitable, green, livable cities with active inhabitants.
Read moreEffects of the COVID-19 Pandemic on Park Visitation Measured by Social Media
Figure 1. Time series of weekly PUD from 2019–2020, in four US cities. Major COVID-related policies are denoted as vertical lines. The COVID-19 pandemic and the resulting economic recession have negatively affected many people’s physical, social, and psychological health. Parks and green-spaces may have ameliorated the negative effects of the pandemic by creating opportunities for outdoor recreation and nature exposure, while other public activities and gatherings were restricted due to risk of disease transmissions. Using park visitation estimates derived from 140K Instagram images shared in four US metropolitan areas, this study investigates trends in park use over the span of the COVID-19 pandemic. We find that while COVID-related stay-at-home orders are associated with shifts in park visitation, the cities that we analysed do not follow uniform trends. Our analyses suggest that future research may be able to explain variability in park visitation based on local factors such as park location and the socio-demographics of visitors. However, the research community does not currently have access to the volume and resolution of data that is necessary to study the issue. There is an urgent need for the CSCW community and social computing researchers to address this data gap if we are to understand the impacts of the pandemic, plan for urban resiliency, and ensure equitable access to parks and other shared resources.
Read moreNo Walk in the Park: the Viability and Fairness of Social Media Analysis for Parks and Recreational Policy Making
Figure 1. Social Vulnerability Index classes by census tract in Seattle (WA). The yellow regions depict the selected parks. Recent years have seen an increase in the use of social media for various decision-making purposes in the context of urban computing and smart cities, including management of public parks. However, as such decision-making tasks are becoming more autonomous, a critical concern that arises is the extent to which such analysis are fair and inclusive. In this article, we examine the biases that exist in social media analysis pipelines that focus on researching recreational visits to urban parks. More precisely, we demonstrate the potential biases that exist in different data sources for estimating the number and demographics of visitors through a comparison of image content shared on Instagram and Flickr from 10 urban parks in Seattle, Washington. We draw a comparison against a traditional intercept survey of park visitors and a multi-modal city-wide survey of residents. We evaluate the viability of using more complex AI facial recognition algorithms and its capabilities for removing some of the presented biases. We evaluate the AI algorithm through the lens of algorithmic fairness and its impact on sensitive demographic groups. We show that despite the promising results, there are new sets of concerns regarding equity that arise when we use AI algorithms.
Read moreNext-Generation Visitation Models using Social Media to Estimate Recreation on Public Lands
Figure 1. Locations of geotagged social media posts made by visitors to public lands in WWA and NNM. Points represent the latitude and longitude where a Flickr photograph (purple) or tweet (green) was created. For Instagram, points represent places to which images were assigned by users (blue). Larger points represent a greater number of Instagram images from the location. Study sites are contained within the management units (shaded grey). Figure created using R48 version 3.5.3. Outdoor and nature-based recreation provides countless social benefits, yet public land managers often lack information on the spatial and temporal extent of recreation activities. Social media is a promising source of data to fill information gaps because the amount of recreational use is positively correlated with social media activity. However, despite the implication that these correlations could be employed to accurately estimate visitation, there are no known transferable models parameterized for use with multiple social media data sources. This study tackles these issues by examining the relative value of multiple sources of social media in models that estimate visitation at unmonitored sites and times across multiple destinations. Using a novel dataset of over 30,000 social media posts and 286,000 observed visits from two regions in the United States, we compare multiple competing statistical models for estimating visitation. We find social media data substantially improve visitor estimates at unmonitored sites, even when a model is parameterized with data from another region. Visitation estimates are further improved when models are parameterized with on-site counts. These findings indicate that while social media do not fully substitute for on-site data, they are a powerful component of recreation research and visitor management.
Read moreUses and Limitations of Social Media to Inform Visitor Use Management in Parks and Protected Areas: A Systematic Review
Figure 1. Papers published by year (n = 58). These are papers published through April 2020, so the number of papers in 2020 only represents 4 months 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.
Read moreSocial-Ecological and Technological Factors Moderate the Value of Urban Nature
Figure 1. Actions lead to changes in the value of urban ecosystem services, defined by a change in human well-being, which may be different for different groups of people, hence the importance of considering equity. The relationships between actions and value are moderated by social, ecological or technological factors. For each action that leads to a change in value, there may also be co-benefits (for example, positive impacts on other sustainability goals) and disservices (for example, unintended negative consequences). Finally, decision-makers require the ability to compare the net value of urban ecosystem services relative to substitutes or alternative interventions designed to meet the same goals. Urban nature has the potential to improve air and water quality, mitigate flooding, enhance physical and mental health, and promote social and cultural well-being. However, the value of urban ecosystem services remains highly uncertain, especially across the diverse social, ecological and technological contexts represented in cities around the world. We review and synthesize research on the contextual factors that moderate the value and equitable distribution of ten of the most commonly cited urban ecosystem services. Our work helps to identify strategies to more efficiently, effectively and equitably implement nature-based solutions.
Read moreGeolocated Social Media as a Rapid Indicator of Park Visitation and Equitable Park Access
Figure 1. Alignment of Census block group, park and park buffer boundaries. The block group boundary in which Central Park is contained includes residential areas bordering the park. When population density within the 400m buffer is averaged over Census block groups, density of the residential areas bordering the park are underestimated due to the inclusion of the park’s area. Understanding why some parks are used more regularly or intensely than others can inform ways in which urban parkland is developed and managed to meet the needs of a rapidly expanding urban population. Although geolocated social media (GSM) indicators have been used to examine park visitation rates, studies applying this approach are generally limited to flagship parks, national parks, or a small subset of urban parks. Here, we use geolocated Flickr and Twitter data to explore variation in use across New York City’s 2143 diverse parks and model visitation based on spatially-explicit park characteristics and facilities, neighborhood-level accessibility features and neighborhood-level demographics. Findings indicate that social media activity in parks is positively correlated with proximity to public transportation and bike routes, as well as particular park characteristics such as water bodies, athletic facilities, and impervious surfaces, but negatively associated with green space and increased proportion of minority ethnicity and minority race in neighborhoods in which parks are located. Contrary to previous studies which describe park visitation as a form of nature-based recreation, our findings indicate that the kinds of green spaces present in many parks may not motivate visitation. From a social equity perspective, our findings may imply that parks in high-minority neighborhoods are not as accessible, do not accommodate as many visitors, and/or are of lower quality than those in low-minority neighborhoods. These implications are consistent with previous studies showing that minority populations disproportionately experience barriers to park access. In applying GSM data to questions of park access, we demonstrate a rapid, big data approach for providing information crucial for park management in a way that is less resource-intensive than field surveys.
Read moreInequality in Access to Cultural Ecosystem Services From Protected Areas in the Chilean Biodiversity Hotspot
Figure 1. Conceptual framework linking ecosystems as service providing areas, cultural ecosystem services and human benefits as supply and demand sides in human–environmental systems (adapted from (Burkhard et al., 2012; Cord et al., 2017). The green and red arrows represent the potential forms of access of the population in the region to the protected areas that we predict will vary according to their socioeconomic characteristics (the thick of the arrow represent population size and the length of the arrow represent the distance travelled along the road network). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.) Experiences with nature through visits to protected areas provide important cultural ecosystem services that have the potential to strengthen pro-environmental attitudes and behavior. Understanding accessibility to protected areas and likely preferences for enjoying the benefits of nature visits are key factors in identifying ways to reduce inequality in access and inform the planning and management for future protected areas. We develop, at a regional scale, a novel social media database of visits to public protected areas in part of the Chilean biodiversity hotspot using geotagged photographs and assess the inequality of access using the home locations of the visitors and socio-economic data. We find that 20% of the population of the region make 87% of the visits to protected areas. The larger, more biodiverse protected areas were the most visited and provided most cultural ecosystem services. Wealthier people tend to travel further to visit protected areas while people with lower incomes tend to visit protected areas that are closer to home. By providing information on the current spatial flows of people to protected areas, we demonstrate the need to expand the protected area network, especially in lower income areas, to reduce inequality in access to the benefits from cultural ecosystem services provided by nature to people.
Read moreRecreational Use in Dispersed Public Lands Measured Using Social Media Data and On-Site Counts
Figure 1. MBSNF (boundary in gray) in western WA. Left: The 15 trail areas observed in this study are dispersed across 4 ranger districts (MTB: Mt. Baker, DAR: Darrington, SKY: Skykomish, SNO: Snoqualmie). Right: Geotagged Flickr photos (purple points) taken in and around the MBSNF. Sources: USFS and Flickr. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.) Outdoor recreation is one of many important benefits provided by public lands. Data on recreational use are critical for informing management of recreation resources, however, managers often lack actionable information on visitor use for large protected areas that lack controlled access points. The purpose of this study is to explore the potential for social media data (e.g., geotagged images shared on Flickr and trip reports shared on a hiking forum) to provide land managers with useful measures of recreational use to dispersed areas, and to provide lessons learned from comparing several more traditional counting methods. First, we measure daily and monthly visitation rates to individual trails within the Mount Baker-Snoqualmie National Forest (MBSNF) in western Washington. At 15 trailheads, we compare counts of hikers from infrared sensors, timelapse cameras, and manual on-site counts, to counts based on the number of shared geotagged images and trip reports from those locations. Second, we measure visitation rates to each National Forest System (NFS) unit across the US and compare annual measurements derived from the number of geotagged images to estimates from the US Forest Service National Visitor Use Monitoring Program. At both the NFS unit and the individual-trail scales, we found strong correlations between traditional measures of recreational use and measures based on user-generated content shared on the internet. For national forests in every region of the country, correlations between official Forest Service statistics and geotagged images ranged between 55% and 95%. For individual trails within the MBSNF, monthly visitor counts from on-site measurements were strongly correlated with counts from geotagged images (79%) and trip reports (91%). The convenient, cost-efficient and timely nature of collecting and analyzing user-generated data could allow land managers to monitor use over different seasons of the year and at sites and scales never previously monitored, contributing to a more comprehensive understanding of recreational use patterns and values. Related News Univ. of Washington program Nature and Health studies link between environment and well-being (December 30, 2021)
Read moreUsing Social Media to Understand Drivers of Urban Park Visitation in the Twin Cities, MN
Figure 1. Distribution of urban park and green space polygons in the Twin Cities Metropolitan Area, MN, USA. Green space and parks in urban environments provide a range of ecosystem services and public benefits. However, planners and park managers can lack tools and resources to gather local information on how parks are used and what makes them desirable places for recreation and a wide variety of uses. Traditional survey methods to monitor park use and user preferences can be costly, time consuming, and challenging to apply at scale. Here, we overcome this limitation by using geotagged social media data to assess patterns of visitation to urban and peri-urban green space across park systems in the metropolitan area of the Twin Cities, Minnesota, USA. We find that parks with nearby water features, more amenities, greater accessibility from the presence of trails, and that are located within neighborhoods with higher population density, are associated with higher rates of visitation. As cities grow and shifts in demographics occur, more responsive management of public green space will become increasingly important to ensure urban parks provide ecosystem services and meet users’ needs. Using social media data to rapidly assess park use at a lower cost than traditional surveys has the potential to inform public green space management with targeted information on user behavior and values of urban residents.
Read moreNature Contact and Human Health: A Research Agenda
Figure 1. A spectrum of forms of nature contact. Background At a time of increasing disconnectedness from nature, scientific interest in the potential health benefits of nature contact has grown. Research in recent decades has yielded substantial evidence, but large gaps remain in our understanding. Objectives We propose a research agenda on nature contact and health, identifying principal domains of research and key questions that, if answered, would provide the basis for evidence-based public health interventions. Discussion We identify research questions in seven domains: a) mechanistic biomedical studies; b) exposure science; c) epidemiology of health benefits; d) diversity and equity considerations; e) technological nature; f) economic and policy studies; and g) implementation science. Conclusions Nature contact may offer a range of human health benefits. Although much evidence is already available, much remains unknown. A robust research effort, guided by a focus on key unanswered questions, has the potential to yield high-impact, consequential public health insights.
Read morePhotos, Tweets, and Trails: Are Social Media Proxies for Urban Trail Use?
Figure 1: Maps of annual average daily trail traffic (AADTT), annual average photo-user days (AAPUD), and annual averageTwitter-user days (AATUD) Decision makers need information on the use of, and demand for, public recreation and transportation facilities. Innovations in monitoring technologies and diffusion of social media enable new approaches to estimation of demand. We assess the feasibility of using geo-tagged photographs uploaded to the image-sharing website Flickr and tweets from Twitter as proxy measures for urban trail use. We summarize geo-tagged Flickr uploads and tweets along 80 one-mile segments of the multiuse trail network in Minneapolis, Minnesota, and correlate results with previously published estimates of annual average daily trail traffic derived from infrared trail monitors. Although heat maps of Flickr images and tweets show some similarities with maps of variation in trail traffic, the correlation between photographs and trail traffic is moderately weak (0.43), and there is no meaningful statistical correlation between tweets and trail traffic. Use of a simple log-log bivariate regression to estimate trail traffic from photographs results in relatively high error. The predictor variables included in published demand models for the same trails explain roughly the same amount of variation in photo-derived use, but some of the neighborhood socio-demographic and built-environment independent variables have different effects. Taken together, these findings show that both Flickr images and tweets have limitations as proxies for demand for urban trails, and that neither can be used to develop valid, reliable estimates of trail use. These results differ from previously published results that indicate social media may be useful in assessing relative demand for recreational destinations. This difference may be because urban trails are used for multiple purposes, including routine commuting and shopping, and that trail users are less inclined to use social media on trips for these purposes.
Read moreMeasuring Recreational Visitation at US National Parks with Crowd-Sourced Photographs
Figure 1. Average monthly visitation in each park, from 2007 to 2012, expressed as the percent of total visits measured by NPS and Flickr PUD. Land managers rely on visitation data to inform policy and management decisions. However, visitation data is often costly and burdensome to obtain, and provides a limited depth of information. In this paper, we assess the validity of using crowd-sourced, online photographs to infer information about the habits and preferences of recreational visitors by comparing empirical data from the National Park Service to photograph data from the online platform Flickr for 38 National Parks in the western United States. Using multiple regression analysis, we find that the number of photos posted monthly in a park can reliably indicate the number of visitors to a park in a given month. Through additional statistical testing we also find that the home locations of photo-takers, provided voluntarily on an online profile, accurately show the home origins of park visitors. Together, these findings validate a new method for measuring recreational visitation, opening an opportunity for land managers worldwide to track and understand visitation by augmenting current data collection methods with crowd-sourced, online data that is easy and inexpensive to obtain. In addition, it enables future research on how visitation rates change with changes in access, management or infrastructure, weather events, or ecosystem health, and facilitates valuation research, such as travel cost studies.
Read moreSpatial and Temporal Dynamics and Value of Nature-Based Recreation, Estimated via Social Media
Figure 1. Conserved lands in Vermont. Conserved lands provide multiple ecosystem services, including opportunities for nature-based recreation. Managing this service requires understanding the landscape attributes underpinning its provision, and how changes in land management affect its contribution to human wellbeing over time. However, evidence from both spatially explicit and temporally dynamic analyses is scarce, often due to data limitations. In this study, we investigated nature-based recreation within conserved lands in Vermont, USA. We used geotagged photographs uploaded to the photo-sharing website Flickr to quantify visits by in-state and out-of-state visitors, and we multiplied visits by mean trip expenditures to show that conserved lands contributed US $1.8 billion (US $0.18–20.2 at 95% confidence) to Vermont’s tourism industry between 2007 and 2014. We found eight landscape attributes explained the pattern of visits to conserved lands; visits were higher in larger conserved lands, with less forest cover, greater trail density and more opportunities for snow sports. Some of these attributes differed from those found in other locations, but all aligned with our understanding of recreation in Vermont. We also found that using temporally static models to inform conservation decisions may have perverse outcomes for nature-based recreation. For example, static models suggest conserved land with less forest cover receive more visits, but temporally dynamic models suggest clearing forests decreases, rather than increases, visits to these sites. Our results illustrate the importance of understanding both the spatial and temporal dynamics of ecosystem services for conservation decision-making.
Read moreApplying Novel Visitation Models using Diverse Social Media to Understand Recreation Change after Wildfire and Site Closure
Figure 1. Location of study sites in the Columbia River Gorge, USA. The area burned in the Eagle Creek Fire is shown in red. Sites are numbered from west to east. Names and closure and reopening dates are in Table S1. The purple star on the reference map shows the location of the study area in the USA. The Columbia River forms the border between Washington (to the north) and Oregon (to the south) in this region. Natural disturbances such as wildfires are increasing in severity and frequency. Although the ecological impacts of disturbance are well documented, we have limited understanding of how disturbances and associated management responses influence recreation use patterns. This reflects, in part, difficulty in quantifying recreation use across different land ownerships with inconsistent, or non-existent, recreation monitoring practices. In this study, we use visitation models based on social media to examine how recreation use changed after a wildfire and site closures in a large, mixed-ownership landscape. We find that wildfire and associated closures resulted in visitation loss to the recreation system as a whole and little site-to-site displacement within the system in the two years following the wildfire. Our study highlights the importance, when considering how wildfire and management may alter recreation use patterns, of considering the many factors that influence substitution behavior, including the relative locations of visitor origins, disturbances, and substitute sites.
Read moreMonitoring Recreation on Federally Managed Lands and Waters—Visitation Estimation
Federally managed public lands and waters attract millions of visitors each year, generating significant economic benefits for surrounding communities. Accurate visitation data are crucial for guiding policy decisions and managing resources effectively. This report explores the methods employed by agencies to collect and use data on recreational visitation to Federal lands and waters. Visitation estimation practices across seven agencies are reviewed, revealing similarities such as the use of automated counters for on-site data collection, alongside differences in reporting frequencies, visit definitions, and public access to data. Emerging technologies, including social media, mobile device activity, and community science, are also evaluated for their potential to improve visitation estimation. Although these technologies offer promising opportunities, they come with challenges such as data biases, the need for calibration, costs, and privacy concerns. The report concludes with opportunities to enhance data collection, coordination, and accessibility, ensuring more efficient resource management and informed decision making. Related Media How Busy are National Parks and other Public Lands? Researchers Hone Methods for Estimating Visitation (June 2025)
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