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The COVID-19 pandemic provided a unique opportunity to examine how varied environmental and social factors in urban environments affect human wellbeing, which is an important dimension of urban sustainability. Past research has focused on individual dimensions of health and isolated nature interactions, limiting knowledge about how different environmental and social factors affect distinct aspects of residents' wellbeing. Through quantitative analyses of social survey and environmental data in metropolitan Phoenix, Arizona (USA), we explored how distinct nature recreation activities—along with nature satisfaction and social capital—affected residents' subjective, mental, and physical wellbeing across diverse neighborhoods during the COVID-19 pandemic, controlling for socio-demographics. Results reveal how distinct drivers shape different dimensions of wellbeing. Perceived social and environmental attributes of neighborhoods and proximity to nature preserves were associated with subjective wellbeing, while park visitation was linked to physical health. Nature interactions largely were unrelated to mental health. Changes in nature recreation during the COVID-19 pandemic did not significantly impact any dimension of wellbeing. Our research suggests that multiple local environmental and social features should be considered when designing healthy communities for urban sustainability. [ABSTRACT FROM AUTHOR]

Urban parks, integral to city life, have long contributed to the well-being of residents through various ecosystem services. Previous studies consistently highlighted unequal park distribution and access, and the COVID-19 pandemic has exacerbated these disparities. From a spatial justice perspective, this review examines urban parks' roles during the pandemic, the impact on equity and access, and how evolving park usage characteristics inform future management challenges. Analysing 53 peer-reviewed studies and 11 online materials from January 2020 to April 2023, this review reveals a significant increase in park visitors during the pandemic, causing challenges in accommodating the surge due to lockdown measures. The findings underscore physical and social justice dimensions, revealing disparities in park access during COVID-19. These challenges prompt reevaluating urban parks' potential for well-being and ecosystem benefits, advocating for inclusive decision-making to enhance community resilience and socialisation. The COVID-19 crisis highlighted planning and management challenges, emphasising the need for a more sustainable, liveable, and responsive approach to urban park planning. [ABSTRACT FROM AUTHOR]

Urban parks played an important role during the COVID-19 pandemic among urban dwellers. Numerous studies have shown that park visitations increased or decreased during the pandemic depending on the parks' contexts, locations, and populations. However, a lack of research has been conducted regarding the impact of COVID-19 on vulnerable and non-vulnerable communities. Therefore, this study seeks to identify the differences between socioeconomic levels in responses to COVID-19′s impact on urban park visits. To observe park users' movements in real-world scenarios, mobile signaling data were used to capture their movements. Then, using Repeated Measures ANOVA (RM ANOVA), the effectiveness of park visit patterns was statistically verified by considering two variables: "time" and "vulnerability". The results showed that park visits increased during the early stages of the COVID-19 pandemic regardless of the vulnerability. As COVID-19 spread, underserved communities experienced decreased park visits, demonstrating park inequality after the pandemic. The comparisons in this study provide recommendations for park managers and policymakers in terms of reducing park inequality. [ABSTRACT FROM AUTHOR]

Spillover impacts pose challenges for the management of protected areas (PAs). The issue of external threats encroaching on PAs has long been recognized, but a corollary—that PA conservation can increase costs borne by neighboring governments or landowners—is less well appreciated. In some contexts, basic principles of fairness and cooperation suggest that PA users should help pay these costs. Several countries have developed mechanisms for distributing the costs of spillover impacts to PA users, but not the United States. Here, we investigate whether and how US park visitors could help address one type of spillover, the need for wildlife conservation efforts beyond park boundaries, using a case study of the Greater Yellowstone Ecosystem (GYE). We examine a “conservation fee” recently proposed in the Wyoming legislature, along with tax-based alternatives. After exploring some costs of wildlife conservation in GYE, we estimate that a fee of up to $10 per vehicle could generate up to $13 million annually, and tax-based approaches considerably more. We consider legal, political, and governance challenges, and ways to mitigate them. The GYE could serve as a demonstration site for visitor funding of cooperative, large-landscape conservation, for potential future expansion in the US and beyond.

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. [ABSTRACT FROM AUTHOR]

Objectives: We explored the importance of environmental and mobility strategies during early COVID-19 by age and ethnicity and investigated predictors of park visitations considering the COVID-19 impacts. Background: Parks are safe and accessible venues to stay active and reduce social isolation, which is especially important considering COVID-19 and the associated lockdowns. Methods: We analyzed online survey data from 683 residents (collected July 2020) of El Paso, TX, and objective measures of neighborhood park characteristics. Chi-square tests and mixed-effects logistic regression analyses were performed to examine the environmental/mobility strategies, personal and environmental factors, and park visitations, considering the COVID-19 impacts. Results: The percentage of those who visited (1+ times/week) parks or trails/paths in the neighborhood dropped from 41.7% to 19.5% since the start of COVID-19 (OR = 0.015, p <.001). Before COVID-19, middle-aged and older adults were less likely to visit parks than younger adults, while this difference became insignificant during early COVID-19. Hispanic adults were more likely to visit parks than non-Hispanics both before and during early COVID-19. Positive environmental predictors of park visitations included park availability in the neighborhood, proximity to the closest park, seeing people being physically active in the neighborhood, and neighborhood aesthetics. Conclusions: Proximately located parks, trails, and paths well integrated into residential communities, and high aesthetic quality of the neighborhood are the potential features of pandemic-resilient communities and should be considered an important national priority to maintain and promote the health and well-being of the population, especially during pandemics like COVID-19. [ABSTRACT FROM AUTHOR]

Forecasting tourism volume can provide helpful information support for decision-making in managing tourist attractions. However, existing studies have focused on the long-term and large-scale prediction and scarcely considered high-frequency and micro-scale ones. In addition, the current approaches are limited regarding forecasting the visitor volume of a designated sub-area in a tourist attraction. This sub-area forecast can assist local-scaled managing decisions of tourist attractions, particularly for large-scale tourist attractions. Therefore, to achieve high-frequency forecasts of tourist volume for finer scale areas such as parks and their sub-areas and generate more controllable and flexible forecasts, this study developed a novel method that incorporates a forecasting model composed of multiple deep learning components and a designed control mechanism. The control mechanism produces high-temporal-resolution sequences of tourist volume for designated sub-areas, and the forecasting model is built on an attention-based deep-bidirectional neural network to better capture the long-range dependencies of the sequence and enhance the forecasting accuracy and robustness. The experimental research was performed at Taiyangdao Park and its two designated sub-areas to validate the effectiveness and superiority of the proposed method compared to other widely used deep-learning methods; three types of performance evaluations were adopted including fitting methods, error measures, and Diebold–Mariano tests. The results demonstrated that the proposed method provided outstanding performance in high-frequency forecasts and yielded more desired forecasting outcomes than other widely used forecasting methods. Furthermore, the comparison with the performances of various other deep learning models provide insights concerning their forecasting capacity; for instance, bidirectional RNN models tend to achieve better forecasts than general RNN models in the high-frequency forecasts. The proposed method has significant practical applicability in aiding short-term micro-scale management decisions and can also serve as an alternative approach in the field of tourist volume forecasting. [ABSTRACT FROM AUTHOR]

Park visits are beneficial for people's physical and psychological health, as well as for the development of social relationships. This study investigated the degree of recovery of physical, psychological, and social aspects of residents in different types of parks and the influence of socio-demographic factors, personal factors, residential space attributes, and park characteristics on park visitation. The results show that tourists visiting urban parks have higher physiological and social recovery than those visiting suburban parks and that there are significant differences. Physical exercise, rest and relaxation, and spending time with family and children were the three most prevalent factors influencing park visits, while time constraints were the most important reason why residents failed to use parks. Socio demographics, residential spatial attributes, individual variables, and park characteristics explained 13.6%, 16.7%, 4.6%, and 2.9% of the total variance in park visit frequency, respectively. Residential green space, age, children under age seven, time spent in residential green space, willingness to spend time in nature, greenery, maintenance, and amenities were positively associated with park use. Income, education, home price, and distance from home to the park were negatively associated with park use. These findings have implications for park management and for future research. [ABSTRACT FROM AUTHOR]

Urban planners and urban forestry researchers use various methods to evaluate how well different populations access the benefits of parks, often by assessing park distribution in relation to the social and economic conditions of surrounding neighbourhoods. However, without precise visitation data, it remains unclear whether proximity to parks translates into actual use. This study analyses the social and spatial factors influencing park visitation using real-world data across multiple urban and ecological contexts. We utilised smartphone mobility to capture visitation counts for over 14,000 parks across 10 US metropolitan areas, representing populations from more than 26,000 census block groups (CBGs). By integrating census data with spatial models, we examined the relationships between park visitation, proximity of parks to visitors' home neighbourhoods, and socio-economic variables such as race and ethnicity. Our analysis revealed that park visitation increases with proximity to visitors' home neighbourhoods. We also found positive associations between visitation rates and factors such as population density, median income, and park coverage in visitors' home neighbourhoods. Additionally, we identified significant correlations between park visitation and the racial and ethnic composition of these neighbourhoods. These findings confirm the assumption that closer proximity to parks enhances visitation rates. We recommend that park visitation data be considered alongside distributional analyses when planning for park accessibility. • Visitor's neighbourhood density, park coverage, and park proximity effect park visitation. • MSA Residents living in higher-income neighbourhoods are more likely to visit parks. • Income levels more consistently effect park visitation patterns than racial or ethnic factors. • Visitation should be considered alongside distributional analyses in park planning. [ABSTRACT FROM AUTHOR]

Parks have evolved into essential urban sanctuaries, especially amid the COVID-19 pandemic. While previous studies have investigated the impact of lockdown measures on park visitation, limited attention has been given to the impacts of sudden easing of containment measures, especially the "unfencing" of parks in densely populated cities. Employing a regression discontinuity design (RDD), this study analyzes changes in park visitation behaviors among Shanghai residents (N=563) following the policy relaxation. We focus on three key aspects: visitation behavior, choice of park types, and activities undertaken within public parks compared to gated community greenspaces. The results reveal a short-term decrease in visits to nearby parks, reduced public transit use, and shorter travel times. This trend was accompanied by a reduction in visitation to various park types, especially larger ones, with waterfront greenspaces being an exception. However, visit frequency and duration remained unchanged. A significant decrease in exercise and enjoying weather was observed in both parks and community greenspaces. Additionally, there was a noticeable reduction in activities like playing with children, nature appreciation, specifically within community greenspaces. These findings extend our understanding of urban residents' engagement with greenspaces in a transitioning post-pandemic context, providing valuable insights in managing greenspaces during and after public health crises. [ABSTRACT FROM AUTHOR]

Identifying key factors affecting park visitation is critical for promoting park visitation and maximizing parks' health and social benefits. Little research has comprehensively revealed the effects of UGC on park visitation within a large regional context, despite its pervasive influence in modern society. Furthermore, although existing research indicated that factors influencing park visitation may vary across different cities, few studies have linked such heterogeneity to different city levels, i.e., cities with different economic status, population size and urbanization level. In this study, we performed comparative research to reveal the effect of UGC on park visitation in nine cities with different urban contexts and economic levels within the Pearl River Delta (PRD), China based on 1,771,093 UGC and mobility data of sample parks. Our results demonstrated that UGC exposure, sentiment, and rating had significant effects on park visitation across all PRD cities; the effect of UGC rating was higher than that of most other variables. Furthermore, most high-value clusters of UGC were concentrated in first-tier cities, while low-value clusters were in non-first-tier cities. Moreover, the effects of UGC variables showed a decreasing trend with lower city levels, while the effect of certain built environment variables exhibited an increasing trend with lower city levels. Our study sheds light on the key factors in park usage, providing effective pathways for policymakers and urban designers to maximize the utilization of urban parks across various city types in modern society. • User-generated content (UGC) could affect park visitation across all city levels. • The rating, sentiment, and exposure of UGC attributes were significant. • Spatial heterogeneity in UGC attributes was identified. • UGC effects on park visitation increased with city levels. [ABSTRACT FROM AUTHOR]

In this study, we pilot a novel use of location quotient and proportional comparison methodology paired with mobile device location data. Specifically, we sought to understand visitation patterns in an urban park context based on visitor home locale socio-demographics, using an example from Fairmount Park in Philadelphia, PA, USA. We examined visitors' home locale demographics (i.e., percent African American and median household income) across a variety of park amenities (e.g., playgrounds, ball fields, splashpads), using location quotients and proportional analyses to compare the home locale demographics of visitors to specific amenities to park visitors as a whole. Findings illustrate amenities with over- or underrepresentation of visitors from certain socio-demographic groups, with bivariate analyses documenting intersectionality between race and income. Results of such analyses can aid park managers in understanding use of particular amenities and service gaps among historically underserved populations, and in turn, support more equitable resource allocation. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has limited people's visitation to public places because of social distancing and shelter-in-place orders. According to Google's community mobility reports, some countries showed a decrease in park visitation during the pandemic, while others showed an increase. Although government responses played a significant role in this variation, little is known about park visitation changes and the park attributes that are associated with these changes. Therefore, we aimed to examine the associations between park characteristics and percent changes in park visitation in Harris County, TX, for three time periods: before, during, and after the shelter-in-place order of Harris County. We utilized SafeGraph's point-of-interest data to extract weekly park visitation counts for the Harris County area. This dataset included the size of each park and its weekly number of visits from 2 March to 31 May 2020. In addition, we measured park characteristics, including greenness density, using the normalized difference vegetation index; park type (mini, neighborhood, community, regional/metropolitan); presence of sidewalks and bikeways; sidewalk and bikeway quantity; and bikeway quality. Results showed that park visitation decreased after issuing the shelter-in-place order and increased after this order was lifted. Results from linear regression models indicated that the higher the greenness density of the park, the smaller the decrease in park visitation during the shelter-in-place period compared to before the shelter-in-place order. This relationship also appeared after the shelter-in-place order. The presence of more sidewalks was related to less visitation increase after the shelter-in-place order. These findings can guide planners and designers to implement parks that promote public visitation during pandemics and potentially benefit people's physical and mental health. [ABSTRACT FROM AUTHOR]

Forecasting tourism volume can provide helpful information support for decision-making in managing tourist attractions. However, existing studies have focused on the long-term and large-scale prediction and scarcely considered high-frequency and micro-scale ones. In addition, the current approaches are limited regarding forecasting the visitor volume of a designated sub-area in a tourist attraction. This sub-area forecast can assist local-scaled managing decisions of tourist attractions, particularly for large-scale tourist attractions. Therefore, to achieve high-frequency forecasts of tourist volume for finer scale areas such as parks and their sub-areas and generate more controllable and flexible forecasts, this study developed a novel method that incorporates a forecasting model composed of multiple deep learning components and a designed control mechanism. The control mechanism produces high-temporal-resolution sequences of tourist volume for designated sub-areas, and the forecasting model is built on an attention-based deep-bidirectional neural network to better capture the long-range dependencies of the sequence and enhance the forecasting accuracy and robustness. The experimental research was performed at Taiyangdao Park and its two designated sub-areas to validate the effectiveness and superiority of the proposed method compared to other widely used deep-learning methods; three types of performance evaluations were adopted including fitting methods, error measures, and Diebold–Mariano tests. The results demonstrated that the proposed method provided outstanding performance in high-frequency forecasts and yielded more desired forecasting outcomes than other widely used forecasting methods. Furthermore, the comparison with the performances of various other deep learning models provide insights concerning their forecasting capacity; for instance, bidirectional RNN models tend to achieve better forecasts than general RNN models in the high-frequency forecasts. The proposed method has significant practical applicability in aiding short-term micro-scale management decisions and can also serve as an alternative approach in the field of tourist volume forecasting.

In 2020, people's health suffered a great crisis under the dual effects of the COVID‐19 pandemic and the extensive, severe wildfires in the western and central United States. Parks, including city, national, and cultural parks, offer a unique opportunity for people to maintain their recreation behaviors following the social distancing protocols during the pandemic. However, massive forest wildfires in western and central US, producing harmful toxic gases and smoke, pose significant threats to human health and affect their recreation behaviors and mobility to parks. In this study, we employed the geographically and temporally weighted regression (GTWR) Models to investigate how COVID‐19 and wildfires jointly shaped human mobility to parks, regarding the number of visits per capita, dwell time, and travel distance to parks, during June ‐ September 2020. We detected strong correlations between visitations and COVID‐19 incidence in southern Montana, western Wyoming, Colorado, and Utah before August. However, the pattern was weakened over time, indicating the decreasing trend of the degree of concern regarding the pandemic. Moreover, more park visits and lower dwell time were found in parks further away from wildfires and less air pollution in Washington, Oregon, California, Colorado, and New Mexico, during the wildfire season, suggesting the potential avoidance of wildfires when visiting parks. This study provides important insights on people's responses in recreation and social behaviors when facing multiple severe crises that impact their health and wellbeing, which could support the preparation and mitigation of the health impacts from future pandemics and natural hazards. Plain Language Summary: This study investigates the variations of human mobility patterns to parks in space and time during the COVID‐19 pandemic and wildfire seasons in 2020 across the western and central United States. We estimate how the COVID‐19 outbreaks, wildfire occurrence, and wildfire‐induced air pollutions affect the number of visits per capita to the parks, the minimum dwell time people spent at parks, and the travel distances to parks. People tended to travel closer to parks and spent less time at parks where there were more COVID‐19 cases reported likely due to the infection protection behavior and risk altitude. However, the pattern was weakened over time due to the decrease in the concerns of the pandemic. Also, during the major wildfire season (August–September), more people traveled further to visit the parks away from the wildfires and stayed longer there. This study explored patterns in physical activity and human mobility to parks under multiple crises that pose threats to human health and wellbeing, which might provide some insights in the preparation for future pandemics and natural hazards. Key Points: We investigated human mobility patterns to parks under COVID‐19 pandemic and wildfire season in western and central United StatesWe found a general trend of avoidance to the parks with fewer visits and dwell time in the places with high COVID‐19 casesWith special demand of physical activities in pandemic, people travel further and spend longer time at the parks away from the wildfires [ABSTRACT FROM AUTHOR]

Abstract In 2020, people's health suffered a great crisis under the dual effects of the COVID‐19 pandemic and the extensive, severe wildfires in the western and central United States. Parks, including city, national, and cultural parks, offer a unique opportunity for people to maintain their recreation behaviors following the social distancing protocols during the pandemic. However, massive forest wildfires in western and central US, producing harmful toxic gases and smoke, pose significant threats to human health and affect their recreation behaviors and mobility to parks. In this study, we employed the geographically and temporally weighted regression (GTWR) Models to investigate how COVID‐19 and wildfires jointly shaped human mobility to parks, regarding the number of visits per capita, dwell time, and travel distance to parks, during June ‐ September 2020. We detected strong correlations between visitations and COVID‐19 incidence in southern Montana, western Wyoming, Colorado, and Utah before August. However, the pattern was weakened over time, indicating the decreasing trend of the degree of concern regarding the pandemic. Moreover, more park visits and lower dwell time were found in parks further away from wildfires and less air pollution in Washington, Oregon, California, Colorado, and New Mexico, during the wildfire season, suggesting the potential avoidance of wildfires when visiting parks. This study provides important insights on people's responses in recreation and social behaviors when facing multiple severe crises that impact their health and wellbeing, which could support the preparation and mitigation of the health impacts from future pandemics and natural hazards.

Abstract Spillover impacts pose challenges for the management of protected areas (PAs). The issue of external threats encroaching on PAs has long been recognized, but a corollary—that PA conservation can increase costs borne by neighboring governments or landowners—is less well appreciated. In some contexts, basic principles of fairness and cooperation suggest that PA users should help pay these costs. Several countries have developed mechanisms for distributing the costs of spillover impacts to PA users, but not the United States. Here, we investigate whether and how US park visitors could help address one type of spillover, the need for wildlife conservation efforts beyond park boundaries, using a case study of the Greater Yellowstone Ecosystem (GYE). We examine a “conservation fee” recently proposed in the Wyoming legislature, along with tax‐based alternatives. After exploring some costs of wildlife conservation in GYE, we estimate that a fee of up to $10 per vehicle could generate up to $13 million annually, and tax‐based approaches considerably more. We consider legal, political, and governance challenges, and ways to mitigate them. The GYE could serve as a demonstration site for visitor funding of cooperative, large‐landscape conservation, for potential future expansion in the US and beyond.

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. [ABSTRACT FROM AUTHOR]

Abstract Background Designing parks that optimise visitation and support visitors to be active is important for public health. Yet there is very little evidence about whether playground refurbishment achieves these objectives. This study examined the impact of the installation of a play-scape in a large metropolitan park in Melbourne, Australia. Methods Natural experiment study (intervention vs control). At both parks, park visitation and physical activity were assessed before (T1, 2013) and after the intervention at 12 (T2, 2014) and 24 months (T3, 2015). At each time point, measures included: observations of park visitors using the System for Observing Play and Recreation in Communities on four weekdays and four weekend days, objective monitors to record usage of the walking paths and the number of cars entering the park; and intercept surveys with adult park visitors. Cross-sectional surveys were conducted with local residents at T1 and T3. Results The observational data showed a 176% increase in park visitor counts from T1 to T2 (Incidence Rate Ratio (IRR) = 2.76, 95% CI = 1.04–7.33), at the intervention park relative to the control park. The intervention park had a 119% increase in counts of visitors observed engaging in MVPA from T1 to T2 (IRR = 2.19, 95% CI = 1.14–4.20), and a 128% increase from T1 to T3 (IRR = 2.28, 95% CI = 1.19–4.38), relative to the control park. The relative increases in visitation at the intervention park play-scape compared with the control park playground were highly statistically significant from both T1 to T2 (IRR = 18.12, 95% CI = 5.51–59.59) and T1 to T3 (IRR = 15.05, 95% CI = 4.61–49.16). Similarly, there was a significant interaction between time and park with regard to the number of visitors observed engaging in MVPA in the play-scape/playground areas. The intercept survey data showed an increased odds of children’s regular visitation to the intervention park at T2 (OR = 2.67, 95% CI = 1.08, 6.64), compared with T1, relative to the control park. The remaining results from the intercept survey, objective monitors and resident surveys showed no significant differences in visitation between the two parks. Conclusions These findings confirm that a well-designed play-scape installation has the potential to increase park visitation and encourage visitors to be physically active. Trial registration Current controlled trial ISRCTN50745547 .

• City-wide park use was assessed before and after the COVID-19 shutdown. • Analysis included mobility data and fixed effects regression analysis. • Pandemic shutdown increased the likelihood of park visits from local block groups. • Time spent in parks and distance traveled to them decreased post pandemic. • Higher median household income was associated with stronger pandemic effects. Access to parks is important for a population's mental, physical, and social health. The importance of parks became even more apparent during the COVID-19 pandemic when publicly accessible outdoor spaces were needed to relax, exercise, and socialize. Using metropolitan Atlanta, Georgia as a case study, this study employs 207,785 rows of park visitation data to assess the spatial distribution of park users within 109 Atlanta parks for the year before and after the initial COVID-19 shutdown, focusing on the length of time spent in parks, distance of travel to get there, and quantity of visits. These facets are compared to the socio-demographic information of the park users to assess how different populations benefited from greenspace use. Furthermore, we compared site usage to park typologies to understand changes in park use. Results reveal that after the COVID-19 declaration, parks were more likely to be used among local block group populations, and the time spent in parks slightly decreased. Yet, the impact of COVID-19 on park use was less strong for lower income groups. Findings reveal the important role of parks during the pandemic and may guide future efforts to develop these public greenspace facilities. [ABSTRACT FROM AUTHOR]

Urban parks are essential for physical activity and health enhancement of local residents. Although previous research has explored the utilization of the urban parks, seasonal oscillations in visitation to small and medium-size urban parks have received scant attention. Utilizing long-time smartphone mobile data, this study investigated park visitation patterns in 84 Atlanta parks. In this article, seasonal variations in park visitation and the correlation between park visiting patterns and park attributes were evaluated. Using fixed-effect regression, we modeled the effects of socioeconomic, climatic, and park attributes on park visiting patterns. The results indicated that park visitor volume and park service areas were significantly influenced by seasonal variations. Facilities, pavements, and scale facilitated visitor volume, while water bodies and landscapes enhanced the park's accessibility from a distance. The landscape design of the park was a significant factor during the summer season, rather than autumn and winter, which were mostly influenced by the availability of playgrounds and recreational facilities. Seasonal patterns of resident visitation varied among parks and interacted with park qualities. This study is expected to inform future design and research of urban parks by addressing specific characteristics of parks and to provide resources in response to dynamic patterns of park access that surpass generic norms. • Smartphone data was utilized to examine seasonal changes in urban parks' long-term visitor patterns. • There are substantial seasonal variations in park visitor volume and service areas. • Fixed effect regression models were developed with confounding variables controlled. • Landscape design facilitated park usage in the summertime, while the playground was crucial in the fall and winter. • This study combined big data analysis and manual auditing to expand our understanding of seasonal variations in park visits. [ABSTRACT FROM AUTHOR]

In recent years, visitation to U.S. National Parks has been increasing, with the majority of this increase occurring in a subset of parks. As a result, managers in these parks must respond quickly to increasing visitor-related challenges. Improved visitation forecasting would allow managers to more proactively plan for such increases. In this study, we leverage internet search data that is freely available through Google Trends to create a forecasting model. We compare this Google Trends model to a traditional autoregressive forecasting model. Overall, our Google Trends model accurately predicted 97% of the total visitation variation to all parks one year in advance from 2013 to 2017 and outperformed the autoregressive model by all metrics. While our Google Trends model performs better overall, this was not the case for each park unit individually; the accuracy of this model varied significantly from park to park. We hypothesized that park attributes related to trip planning would correlate with the accuracy of our Google Trends model, but none of the variables tested produced overly compelling results. Future research can continue exploring the utility of Google Trends to forecast visitor use in protected areas, or use methods demonstrated in this paper to explore alternative data sources to improve visitation forecasting in U.S. National Parks. • Search engine data is useful for predicting visitation to park units the next year. • Overall, using Google Trends performs better than an autoregressive model. • Using Google Trends to forecast visitation is useful for some, but not all, parks. • Utility of Google Trends is weakly correlated with higher surrounding populations. [ABSTRACT FROM AUTHOR]

Understanding park visitation patterns and factors that correlate with park use is conducive to urban green space management and planning. Although a growing number of studies have indicated geolocated social media can be used as a proxy for recreational use analysis, most of them relied on a single or similar social media platform(s). In this study, we used geolocated social media data among four popular platforms in China to estimate park visitation and explore the influence of 13 potential factors on park usage in Shenzhen by the geographical detector model. A park visitation index was introduced to estimate park usage, and it indicated large parks, such as natural and city parks, have a higher park visitation index than community parks in Shenzhen. In contrast to the check-in data, the real-time user data has a higher potential to describe park visitation citywide. Our findings demonstrate park size, sports and recreation amenities, the length of trails, and the nearby building density of a given park are likely to influence park visitation. The enhanced interactive relationship of 13 potential determinants of park usage can provide implications for urban park management and planning. ● A park visitation index is introduced to estimate park usage using geolocated social media data among four popular platforms in China. ● A geographical detector model is applied to explore the influence of potential influence factors and their interactive relationship on park usage. ● By comparison, the real-time user dataset (RTUD) is better than the check-in dataset in describing the park visitation. ● Park size, sport and recreation amenities, trails, and neighborhood building density are more likely to influence park visitation. ● The interactive relationship among potential driving factors on park visitation is mainly bivariate enhanced or nonlinear enhanced. [ABSTRACT FROM AUTHOR]

National parks are an important manifestation of the United States’ democratic ideal and attract more than 300 million visits annually. However, racial/ethnic minorities are substantially underrepresented among visitors, and this has led to three hypotheses—marginality, subculture, and discrimination—designed to help explain this pattern of visitation. Moreover, research suggests that the awareness of and visitation to national parks may relate to several variables, including race/ethnicity, socio-economic characteristics, and childhood visitation history. To investigate these issues, an online general population survey of New York City residents was conducted. Study findings suggest that (1) racial/ethnic minorities are underrepresented at some types of parks but not others, (2) Hispanics and Blacks generally have lower rates of awareness about national parks than Whites, and (3) awareness and childhood visitation history significantly affect visitation to national parks. These findings suggest potential approaches to enable and encourage diverse racial/ethnic groups to engage with national parks. [ABSTRACT FROM AUTHOR]

Changes in temperature and precipitation can affect tourist experiences. This study examines how summer park visitation has changed in response to temperature and precipitation extremes. The study goals were two-fold. The first is to introduce a framework and the second is to test it in a pilot region with four mountainous National Parks. The framework is designed to compare the vulnerability of seasonal park visitation to shifts in a combined indicator of temperature and precipitation. It uniquely considers needed measurements, and the data required to conduct an analysis. The second goal is to test it in four destinations in the U.S. Northern Rockies, including Glacier, Yellowstone, Grand Teton, and Rocky Mountain National Parks. The preliminary test reveals outlier cases of visitation under wet and dry extremes. The analysis connects time series climate and visitation data for the peak summer season from 1991-2012. Outlier analysis illustrates more change in extremely dry conditions, with four out of the six dry-year outliers resulting in a visitation decline. Whether this decline in park tourism is attributable to climate features, economic factors, or conscious management decisions, these drops have significant economic impacts: estimates of changes in visitor spending during dry years are between roughly 9 and 90 million USD. These differences may be connected to the popular activities in each park, and the extent they are dependent on weather conditions. This framework can be used to test the relationship between climate and tourism visitation in other regions, in various seasons and time frames. The work may inform the tourist sector in adjusting and planning for a range of conditions. We discuss opportunities and conclude with additional needs for understanding the mechanisms behind risk in mountain park tourism under climate extremes. [ABSTRACT FROM AUTHOR]

Background: Designing parks that optimise visitation and support visitors to be active is important for public health. Yet there is very little evidence about whether playground refurbishment achieves these objectives. This study examined the impact of the installation of a play-scape in a large metropolitan park in Melbourne, Australia. Methods: Natural experiment study (intervention vs control). At both parks, park visitation and physical activity were assessed before (T1, 2013) and after the intervention at 12 (T2, 2014) and 24 months (T3, 2015). At each time point, measures included: observations of park visitors using the System for Observing Play and Recreation in Communities on four weekdays and four weekend days, objective monitors to record usage of the walking paths and the number of cars entering the park; and intercept surveys with adult park visitors. Cross-sectional surveys were conducted with local residents at T1 and T3. Results: The observational data showed a 176% increase in park visitor counts from T1 to T2 (Incidence Rate Ratio (IRR) = 2.76, 95% CI = 1.04-7.33), at the intervention park relative to the control park. The intervention park had a 119% increase in counts of visitors observed engaging in MVPA from T1 to T2 (IRR = 2.19, 95% CI = 1.14-4.20), and a 128% increase from T1 to T3 (IRR = 2.28, 95% CI = 1.19-4.38), relative to the control park. The relative increases in visitation at the intervention park play-scape compared with the control park playground were highly statistically significant from both T1 to T2 (IRR = 18.12, 95% CI = 5.51-59.59) and T1 to T3 (IRR = 15.05, 95% CI =4.61-49.16). Similarly, there was a significant interaction between time and park with regard to the number of visitors observed engaging in MVPA in the play-scape/playground areas. The intercept survey data showed an increased odds of children's regular visitation to the intervention park at T2 (OR = 2.67, 95% CI = 1.08, 6.64), compared with T1, relative to the control park. The remaining results from the intercept survey, objective monitors and resident surveys showed no significant differences in visitation between the two parks. Conclusions: These findings confirm that a well-designed play-scape installation has the potential to increase park visitation and encourage visitors to be physically active. Trial registration: Current controlled trial ISRCTN50745547. [ABSTRACT FROM AUTHOR]

Quantifying residents' utilization of parks and understanding the driving factors behind it are essential for optimizing parks and promoting human well-being. However, previous literature has generally neglected the systematic investigation of visit flows, duration, and their spatiotemporal disparities along with the differential influence of park environmental factors on such measures. We addressed the gaps by combining visit flows and duration analysis based on mobile phone signaling data from 152 urban parks in Chengdu, China. We classified the parks into four categories based on the disparity between visit flows and duration. Through the Spearman rank correlation and spatial regression models, we identified the critical factors influencing park visit flows and duration. The findings reveal that: (1) There is a significant spatiotemporal disparity between visit flows and duration. (2) The main factors affecting park visit behavior included park area, types of facilities, distance to the city center, and the number of surrounding residents. (3) The regression models better explained visit flows than visit duration. (4) Environmental factors had a greater impact on park visit behaviors during weekends and peak hours. Selecting multi-dimensional indicators to quantify the use of urban parks provides valuable references for urban planners to optimize the urban park system. • Visit flows and duration of different parks have spatiotemporal disparities. • Low- and high-quality parks are identified by combining the two visit behaviors. • Park area, amenities, location, and nearby residents mainly affect park visits. • Regression models explain park visit flows better than park visit duration. • Influencing factors increasingly impact on visit behaviors at weekends and peaks. [ABSTRACT FROM AUTHOR]

While various observation techniques have been developed to measure park use or park-based physical activity, no study has used unmanned aerial vehicles (UAVs) to do so. Thus, this study develops a new observation method that uses UAVs to survey park-based physical activity. This study tests the inter-rater reliability and criterion validity of the UAV-using observation method in comparison to an existing on-the-ground observation tool in five diverse urban parks in Salt Lake City, Utah. With a systematic observation tool, SOPARC (System for Observing Play and Recreation in Communities), this study finds that the UAV observations show a high level of inter-rater reliability (ICC = 0.99 for a total number of users). In addition, compared to the results of on-the-ground observations using SOPARC, those of UAV observations demonstrate validity (ICC = 0.98 for a total number of users). Compared to existing methods, the UAV observation tool, covering larger target areas, is suitable for counting park users in a more reliable and efficient way and mapping their use patterns; however, the tool is weaker at collecting detailed user information and surveying under poor weather conditions. Thus, the UAV method could complement existing tools. Finally, this study suggests practical implications of the UAV observation method. [ABSTRACT FROM AUTHOR]

Current “second generation” approaches to visitation in higher order protected areas are based on biocentric management and monitoring that positions visitors as an inherent threat. The result is suboptimal sustainability outcomes of coexistence and possibly increased conflict in an era of escalating demand, reduced public funding and growing threats to global and local biodiversity. A “third generation” model is therefore required that repositions visitors as an inherent opportunity, and augments management and monitoring accordingly with visitor motivation and mobilisation for mass participation in on-site park enhancement activities. Strategies and issues for implementation - including the model's dialectical underpinnings and its relationship to a broader context of people-focused park management -are considered, toward achieving optimal sustainability outcomes of park/visitation symbiosis. [ABSTRACT FROM AUTHOR]

Urban parks are among the most important urban public services. Quantifying their visitation intensity and understanding the driving forces behind their popularity is of great relevance to urban planning. We analyze the behavior of park visitors in Beijing based on phenological information extracted from social media data. Specifically, we built a dataset utilizing natural language processing techniques and co-word analysis methods to explore the connection between flowers and park visitation. Our findings revealed that: (1) According to the changing trend of visitor volumes and their peak times, urban parks can be divided into "single-peak" (visitor volumes show a single peak, with significant seasonal characteristics) and "multi-peak" (visitor volumes show multiple peaks with no obvious seasonal characteristics) parks; (2) There is an association between flowers and visitor volumes to urban parks, with a noticeable increase in the frequency of visits to parks especially in spring (i.e., during flowering); (3) Different types of flowers have varying appeal to attract visitors. Further, parks with one or few "dominant flowers" appeal to more visitors than parks without a clear dominating flower (or flowers). Our results provide implications for urban park design and management for improving their scenic qualities. • Microblog data is utilized as an indicator of park visitation. • Chinese word segmentation techniques are used to extract phenological information. • Co-word analysis is introduced to study the flowers–visitation connection in parks. • Significant visitor peaks are observed during flowering periods. • The results verify that flowers contribute to urban parks' total attractiveness. [ABSTRACT FROM AUTHOR]

Increasing number of people is becoming more active in park visitation and ecotourism. It is therefore important for park managers to understand future trends in visitor use of parks. This research paper is designed to understand the motivational factors or the psychological reasons why people visit parks in order to create the suitable marketing campaign to target them. As well as that, it discovers the facilities and attractions of parks that are most important to the visitors, so that the management of parts can disburse its resources in the best areas to achieve maximum output and return. Furthermore, the research aims to find the best communication channels for tourism destinations to reach its target audience so that its marketing expenditure can yield the maximum return. A survey with 228 participants who have visited Saigon Zoo and Botanical Gardens in the last 12 months was conducted. The research result will be critical for the adaptive management of parks and for building the capacity to manage changes and shifts in visitation patterns and park usage. Saigon Zoo and Botanical Gardens would take advantage of this trend and secure a substantial proportion of the new park visitors.

Given the importance of urban parks for recreation, it is critical to understand how they are used and perceived. Currently, relatively few studies have examined the public's activities and preferences at the same time. Social media data are increasingly recognized as a promising data source to study these two aspects. However, little is known regarding the utility and representativeness of social media data for urban parks. In particular, a lack of understanding exists on the comparability of research results measured by bottom-up social media data and top-down official survey data in urban park studies. This research used social media data from Ctrip and Dianping and survey data from the local government agency with park visits statistics and park satisfaction surveys to understand the public's visitation and satisfaction of 102 urban parks in central Shanghai. We first assessed the similarities between the social media data and survey data by correlation analysis. We then used the negative binomial regression model and beta regression model to examine the matches and mismatches of the different data sources in investigating factors influencing park visitation and park satisfaction. Our correlation results showed that the social media data significantly correlated with the survey data and that social media data performed better in more frequently visited parks. Our regression results showed that the water bodies, recreational facilities, and surrounding commercial facilities were the common influencing factors of park visitation and park satisfaction for all parks. While significant correlations were noticed between these two data sources, we found that the surrounding population density was negatively associated with park visitation measured by social media data but positively associated with park visitation measured by survey data. This study provides a comparative perspective to study park visitation and park satisfaction by combining social media data and official survey data. Clarifying the consistencies and inconsistencies between the social media data and official survey data is important because it could help us to understand the representativeness and potential biases of the social media data when used in visitation monitoring and satisfaction monitoring. • We compared social media data with survey data to understand park visitation, park satisfaction, and their influencing factors. • Water bodies, recreational facilities, and the surrounding commercial facilities were positive influencing factors for both park visitation and park satisfaction. • The surrounding population density had opposite effects on park visitation measured by different data sources. • Public transport accessibility and park size were important influencing factors for park visitation measured by social media data. [ABSTRACT FROM AUTHOR]

This study used Pierre Bourdieu's theory of practice to understand African Americans' underrepresentation at Cedar Hill State Park (CHSP) in Texas. Archival methods, site visits, and face-to-face interviews were conducted with 13 local African Americans. Four salient themes related to African Americans' under-representation were identified: (1) racial conflict within the field, (2) CHSP as a racialized space, (3) African American leisure habitus, and (4) lack of relevant attractions. These themes were closely related and together showed that perceived racial discrimination was a common factor which explained nonvisitation at CHSP. [ABSTRACT FROM AUTHOR]

Historical park visitation and weather data, taken at the daily time scale from 2000 to 2009 for Pinery Provincial Park in southern Ontario (Canada), were analysed as an objective measure of the weather sensitivity, temperature thresholds, and potential impacts of projected climate change for park visitation. Three seasonal weather-visitation models were constructed using multivariable linear regression (peak, shoulder, off-season). To account for both natural and institutional seasonality, the weather-visitation models included both climatic (temperature, precipitation) and social (weekends, holidays) variables, which demonstrated equably comparable effects on visitation across the three models. Critical temperature thresholds were identified for each season using one-way analysis of variance to determine the range of temperatures within which the threshold was evident; the specific degree of temperature associated with the threshold was identified within the seasonal regression models. Temperatures over 33 °C during the peak season and over 29 °C during the shoulder season indicated critical thresholds at which point conditions that were ‘too hot’ for some caused a decline in visitation. Furthermore, temperatures below 11 °C indicated another critical threshold, where conditions were ‘too cold’ for most and therefore park visitation was less sensitive to temperature variability below this threshold. A partial sensitivity analysis for the impact of a warmer, wetter climate on park visitation was conducted, illustrating the effect of a 1 °C to 5 °C warming in maximum temperatures, coupled with a 5% to 15% increase in total precipitation. In response to projected climate change, the weather-visitation models suggested that for each additional degree of warming experienced, despite the negative effects of increasing precipitation and more frequent heat extremes, annual park visitation could increase by 3.1%, annually. The projected increase in park visitation as a result of rising temperatures was mainly associated with shoulder season visitation, with only minor increases in peak season visitation. [ABSTRACT FROM PUBLISHER]

Environmental and conservation education programs are commonly offered in the rapidly expanding network of protected areas in developing countries. There have been few evaluations of these programs and their impacts on participants. At Serra Malagueta Natural Park in Cape Verde, we assessed changes in environmental knowledge, opinions, and behaviors among visiting school children and a comparison group that did not visit the park. Participation in the park’s conservation education program has a positive impact on environmental knowledge after the visit. The program may also contribute to student knowledge by influencing classroom teaching in anticipation of the park visit. [ABSTRACT FROM PUBLISHER]

Background: Parks are important for providing opportunities for physical activity among youth. Apart from engaging in physical activity whilst visiting a park, active transportation (e.g. walking or cycling) to parks is potentially an additional source of physical activity. Previous research has shown that a major barrier to young people visiting parks is their inability to visit parks unaccompanied by an adult. It is not known, however, whether young people who have greater independent mobility and territorial range (ability to move around their neighbourhood alone or with friends, unaccompanied by an adult) are more likely to visit parks. This study examined park visitation and travel mode to parks and whether independent mobility and territorial range were associated with park visitation among youth living in disadvantaged areas of Victoria, Australia. Methods: In 2010–11, 311 youth aged 8–16 years self-reported their park use, active transport, independent mobility to parks, and territorial range. Logistic regression models determined the odds of park visitation (once per week or more) according to independent mobility and territorial range, adjusting for key covariates. Results: Overall, 75% of participants reported visiting parks, and 37% visited their ‘usual’ park at least once per week. Of those who reported visiting parks, 87% travelled to the park they usually visited using active transport: 57% walked, 22% cycled, and 8% used a scooter/skateboard. Just 15% and 13% of youth regularly walked or cycled alone to parks/playgrounds respectively, and 25% and 19% regularly walked or cycled with friends or siblings (no adults) respectively. For the 84% who reported having parks/playgrounds within walking distance from home, those who regularly walked alone to parks (OR 3.61; CI=1.67, 7.80), and regularly walked (OR 2.27; CI=1.14, 4.55) or cycled (OR 3.38; CI=1.73, 6.62) with friends to parks, were significantly more likely to visit a park at least once per week, compared to others. Conclusions: This study showed that active transport is frequently used by this sample of young people to travel to parks. Findings also highlight the potential importance of providing opportunities for youth aged 8–16 years to visit local parks independent of an adult. [ABSTRACT FROM AUTHOR]

• Smartphone data was used to study park visitations for mid-sized cities. • Temporal and spatial patterns of park visitations were presented. • A fixed effects regression model was built with confounding factors controlled. • Water bodies and playgrounds are significant factors for park visitation. • Implications on urban planning and park management practices were discussed. City parks provide essential services for the physical activities and the health improvement of residents. Most related literature focuses on the factors affecting park visitations in large cities, but relatively little is known regarding long-term park visitations, especially in mid-sized cities. By using smartphone mobility data tracking the activities of 28 parks in the College Station and Bryan Metropolitan area of Texas, USA, we present the temporal and spatial patterns of park usage within a two-year timeframe. We model the effects of the socio-economic, built environment, climate, and spatial/accessibility factors on park visitations through a fixed effects regression. Results show variations among park service areas. Water bodies and playgrounds are significant factors enhancing park visitations while walking paths, sports facilities, and pavilions are not. Contrary to previous research, high-income block groups show lower participation in park activities. The study also reveals how smartphone mobility data can be applied to case studies investigating urban design/planning and understanding of the social aspects associated with urban greenspaces. It provides empirical evidence on park visitations as well as what factors future planners, landscape architects, and park managers should consider when deciding on park investment and planning decisions for mid-sized cities. [ABSTRACT FROM AUTHOR]

Park visitation is a popular recreational activity among urban residents. The decision to visit a park is related to the park's attraction as the pull factor. The attractions include park's products such as its facilities, services and programmes provided by the management. In many situations, lack of attractive products or recreational opportunities contributes to the decline in its visitation. Since year 2005, Putrajaya Botanical Garden has faced a similar situation, whereby its low visitation could be associated to unexciting product features offered by the park's management. In this study, an evaluation was carried out on the products' performance in attracting people to visit the park. Hence, 18 park attributes were chosen as attractions or pull factors to determine their relationships with socio-demographic background of visitors and their visitation attributes. Income and education attainment were identified as the significant reasons of visitation to Putrajaya Botanical Garden. Among the most important findings is the "park tranquil setting", which is considered to be the park's biggest attraction, among other attributes. Based on the factor analysis, three key factors were identified and labelled as "facilities and park settings", "services and key visitors' attractions" and "programmes and activities". Meanwhile, "facilities and park setting" also showed the strongest positive relationships to the visitors' extent of visitation. The study revealed the attractiveness of the park's products would have the influence on people's decision to visit it. These findings therefore contribute to the important idea to the current understanding of pull factors that influence park visitation to Putrajaya Botanical Garden as a thematic nature park. [ABSTRACT FROM AUTHOR]

The authors fitted a number of time-series econometric models to monthly visitation data of a national park to examine the effect of impaired visibility on visitation demand. Using a polynomial distributed lag model, the long-run elasticity of demand with respect to visibility in the Great Smoky Mountain National Park (GSMNP) was estimated. The GSMNP, the most visited national park in the USA, has significant air quality issues. Although the park has observed some fluctuation in visitation, the results indicate that the demand for visitation in general and for specific recreational visits are mean reverting and highly stable. Further, park visitation in a given month is significantly affected by the cumulative effect of the visibility condition in both the current and preceding months. Estimated elasticity reveals that a programme aiming to improve the average visibility by 10% (5.5 km) from the current level could result in an increase of roughly one million recreational visits annually, and that the increase would be higher for overnight visitors than for day visitors because of overnight visitors' relatively elastic demand. This demand model could assist park managers in their planning as they weigh the anticipated benefits of a visibility improvement programme against increased visitation and its associated costs. [ABSTRACT FROM AUTHOR]

This study examines U.S. National Park visitation from 1990 through 2008. Using data from the Visitor Services Project of the Park Studies Unit at the University of Idaho, 180 different National Park Service units are analyzed on the basis of nine variables common to all park units, such as group size, distance traveled, and first-time visitation. Data are also analyzed by four park types that have been created for the study: Type I, natural parks/monuments; Type II, recreation areas/ shorelines; Type III, military parks/battlefields; and Type IV, historical/cultural parks. Data show specific differences for the four park types on the basis of several of the demographic and travel variables. Implications are provided for managers wanting to use these data to improve their understanding of visitor demand, market segmentation, and programme delivery. Future research is proposed to learn more about the visitor experience, visitation trends, and data sharing. [ABSTRACT FROM AUTHOR]