Filter Publications
Adapting 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 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 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 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 moreCoding Manual for “The Nature Voices of People Who Visit Discovery Park: An Interaction Pattern Approach”
Chris TarnawskiDiscovery Park Lighthouse. Credit: Chris Tarnawski. Interaction with nature is vital for human physical health and mental well-being, yet urban development continues to put pressures on natural areas that allow for essential forms of human-nature interaction. Discovery Park, the largest park within Seattle—with over 500 acres and almost 12 miles of walking trails—is a case in point insofar as some Seattle constituents would like to develop some of its open space. The goal of this research is to give voice to how visitors of Discovery Park interact with nature at the park. To accomplish this, we applied an Interaction Pattern Approach, where “interaction patterns” are defined as fundamental ways of interacting with nature that are characterized abstractly enough such that many different instantiations of each pattern can be engendered. After their visit to Discovery Park, participants were asked to access our website (what we called “the Nature Language Website”) to write a few sentences or paragraphs that described a meaningful experience they had interacting with nature in the park. Participants were also asked a few demographic questions. This technical report provides our coding manual—our systematic method to code the qualitative data—of people who visited Discovery Park, and who wrote of how they interacted with nature in the park. This technical report thereby provides open access to our core intellectual qualitative work on this project. It can be used by others to conduct related research on how people interact with nature, and especially natural landscapes.
Read more
Recreational 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 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 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)
Read more