Using VGI and Social Media Data to Understand Urban Green Space: A Narrative Literature Review

Effect of the COVID-19 pandemic on the popularity of protected areas for mountain biking and hiking in Australia: Insights from volunteered geographic information

Although the popularity of protected areas for recreation has been increasing, short term changes in visitation occurred during the COVID-19 pandemic. To examine how volunteer geographic information data can be used to monitor such often rapid changes in visitation across multiple locations, data from online fitness platforms for mountain biking (Trailforks) and remote area hiking (Wikiloc) were analysed before (2019) and during (2020-2021) the COVID-19 pandemic for 40 protected areas in Queensland, Australia. Mountain biking was popular with a total of 93,311 routes on Trailforks, with 26,936 routes in 2019, increasing to 37,406 in 2020, and then decreasing to 28,969 in 2021. Approximately 66% of all the routes were from just three urban protected areas out of the 12 with route data. There were 4367 routes for remote area hiking on Wikiloc across 36 protected areas, which increased slightly from 1081 in 2019, to 1421 in 2020 and to 1865 in 2021. Across 18 factors, distance from urban areas and networks of mountain biking trails best predicted popularity for mountain biking based on Generalised Linear Models. In contrast, average slope and large networks of hiking trails best predicted hiking, with similar results for each year. The two sources of online data were correlated with trail counter data, although not consistently. The results highlight how external factors affect visitation, but also how the same types of protected areas remained popular, and that the impacts of COVID-19 pandemic on visitation in South-East Queensland protected areas was less dramatic than for other regions. This study further highlights how volunteered geographic information can be used to assess the popularity of protected areas, including in rapidly changing conditions.

Management implications

Rapid changes in visitation can be challenging to monitor and manage, as occurred with the COVID-19 pandemic. The impacts of the COVID-19 pandemic on mountain biking and hiking and factors predicting protected area popularity were examined across different parks. Visitation increased at different stages of the pandemic, with mountain bikers' preferring urban parks with networks of mountain bike trails while some hikers preferred more remote large parks. Managers can expand on traditional methods of visitor monitoring by using volunteered geographic information to monitor rapid and longer-term trends of visitation to protected areas.

Changes in visits to green spaces due to the COVID-19 pandemic: Focusing on the proportion of repeat visitors and the distances between green spaces and visitors' places of residences

Through a quantitative approach, this study aimed to clarify the changes in the number of visitors and visits to green spaces according to green space type before and after the COVID-19 pandemic. We explored the changes in the proportion of repeat visitors and the distance between green spaces and visitors' places of residence. We used KDDI Location Analyzer, which performs novel analysis using mobile phone GPS and census data. The study area included 10 target sites (urban parks and nature trails in the backcountry) located in the Sapporo metropolitan area in Japan. The survey period included snow-free seasons from 2019 to 2021, and 2019 was considered the period "before the pandemic." The results revealed that the number of visits during the pandemic increased compared with those before the pandemic, except for those of urban parks near the city center. In 2020, the proportion of repeat visitors increased for all 10 target sites. In addition, since the outbreak of the pandemic, distances between all urban parks and visitors' residences decreased. The same trend was observed for nature trails in the backcountry close to the city center. These findings indicate a generally decreasing trend in the number of visits to green spaces as many people have been refraining from visiting the site since the outbreak of the pandemic. Contrastingly, the number of visits by repeat visitors who reside close to the target sites has increased in some cases, which compensated for the general decreases.

Using social media data to understand the impact of the COVID-19 pandemic on urban green space use

Having access to and visiting urban green space (UGS) improves liveability and provides considerable benefits to residents. However, traditional methods of investigating UGS visitation, such as questionnaires and social surveys, are usually time- and resource-intensive, and frequently provide less transferable, site-specific outcomes. This study uses social media data (Twitter) to examine spatio-temporal changes in UGS use in London associated with COVID-19 related lockdowns. It compares georeferenced Tweets posted in a 3 month period from 23 March to 23 June for 3 years covering the first lockdown in the UK in 2020, with Tweets for the same period in 2019 and 2021. The results show that (1) the land-use type of Public Park and Garden was the most frequently visited type of UGS, which may be correlated with these UGS areas remaining opening during the lockdown period; (2) the usage of UGS decreased in central London and increased in other areas during lockdown, which may correlated with working from home restrictions; (3) activities were positively associated with Physical activities maybe as a result of allowing people to take a single daily exercise, and (4) people spent more time in UGS areas on weekdays than weekends compared to pre-lockdown. This is the first study to examine social media data over consistent time period before, during and after the lockdown in relation to UGS. The results show that the findings and method can inform policy makers in their management and planning of UGS, especially in a period of social crisis like the COVID-19 pandemic.

A Literature Review of Big Data-Based Urban Park Research in Visitor Dimension

Urban parks provide multiple benefits to human well-being and human health. Big data provide new and powerful ways to study visitors’ feelings, activities in urban parks, and the effect they themselves have on urban parks. However, the term “big data” has been defined variably, and its applications on urban parks have so far been sporadic in research. Therefore, a comprehensive review of big data-based urban park research is much needed. The review aimed to summarize the big data-based urban park research in visitor dimension by a systematic review approach in combination with bibliometric and thematic analyses. The results showed that the number of publications of related articles has been increasing exponentially in recent years. Users’ days data is used most frequently in the big data-based urban park research, and the major analytical methods are of four types: sentiment analysis, statistical analysis, and spatial analysis. The major research topics of big data-based urban park research in visitor dimension include visitors’ behavior, visitors’ perception and visitors’ effect. Big data benefits urban park research by providing low-cost, timely information, a people-oriented perspective, and fine-grained site information. However, its accuracy is insufficient because of coordinate, keyword classification and different kinds of users. To move forward, future research should integrate multiple big data sources, expand the application, such as public health and human–nature interactions, and pay more attention to the big data use for overcoming pandemic. This review can help to understand the current situation of big data-based urban park research, and provide a reference for the studies of this topic in the future.

Patterns of Urban Green Space Use Applying Social Media Data: A Systematic Literature Review

Scientific interest in the potential of urban green spaces, particularly urban parks, to improve health and well-being is increasing. Traditional research methods such as observations and surveys have recently been complemented by the use of social media data to understand park visitation patterns. We aimed to provide a systematic overview of how social media data have been applied to identify patterns of urban park use, as well as the advantages and limitations of using social media data in the context of urban park studies. We used the PRISMA method to conduct a systematic literature analysis. Our main findings show that the 22 eligible papers reviewed mainly used social media data to analyse urban park visitors’ needs and demands, and to identify essential park attributes, popular activities, and the spatial, social, and ecological coherence between visitors and parks. The review allowed us to identify the advantages and limitations of using social media data in such research. These advantages include a large database, real-time data, and cost and time savings in data generation of social media data. The identified limitations of using social media data include potentially biased information, a lack of socio-demographic data, and privacy settings on social media platforms. Given the identified advantages and limitations of using social media data in researching urban park visitation patterns, we conclude that the use of social media data as supplementary data constitutes a significant advantage. However, we should critically evaluate the possible risk of bias when using social media data.

Using Social Media Data to Evaluate Urban Parks Use during the COVID-19 Pandemic

In the context of increasing urbanization and associated economic, social and environmental challenges, cities have increasingly acknowledged the importance of urban parks in delivering social, economic and environmental benefits to the population. The importance has been demonstrated also during the COVID-19 pandemic that generated lockdowns and reduced the capacity of urban inhabitants in accessing such benefits. The present study aims to determine how the presence in urban parks was reflected on social media during the pandemic period of 2020. We examined Instagram posts associated with a sample of eight urban parks in Bucharest, Romania and also the entire history of Google reviews between January and August 2020. The selection of parks was made according to their size, location in Bucharest, previous reported number of visitors and profile of attractiveness. Results revealed that the peak period of the COVID-19 pandemic and the first initiation of the lockdowns strongly affected the recreation and leisure activities that people performed almost daily in the parks of Bucharest. Reviews and comments of the population were not that focused on the pandemic even after the restrictions were lifted, but they evidenced the positive and negative aspects of each park. Our results can represent a useful instrument for local administrations in determining both the flow of visitors but also their perceptions towards the endowments, landscape and most important management of urban parks.

How Did Built Environment Affect Urban Vitality in Urban Waterfronts? A Case Study in Nanjing Reach of Yangtze River

The potential of urban waterfronts as vibrant urban spaces has become a focus of urban studies in recent years. However, few studies have examined the relationships between urban vitality and built environment characteristics in urban waterfronts. This study takes advantage of emerging urban big data and adopts hourly Baidu heat map (BHM) data as a proxy for portraying urban vitality along the Yangtze River in Nanjing. The impact of built environment on urban vitality in urban waterfronts is revealed with the ordinary least squares (OLS) and geographically weighted regression (GWR) models. The results show that (1) the distribution of urban vitality in urban waterfronts shows similar agglomeration characteristics on weekdays and weekends, and the identified vibrant cores tend to be the important city and town centers; (2) the building density has the strongest positive associations with urban vitality in urban waterfronts, while the normalized difference vegetation index (NDVI) is negative; (3) the effects of the built environment on urban vitality in urban waterfronts have significant spatial variations. Our findings can provide meaningful guidance and implications for vitality-oriented urban waterfronts planning and redevelopment.