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

Urban park green space use analysis based on trajectory big data: Experience from a medium-sized city in China

Regular visits to park green space offer remarkable benefits for the physical and mental health of urban residents. Achieving a comprehensive understanding of the utilization across the entire city is a prerequisite for improving the overall utilization rate of park green spaces. Traditional social survey methods are limited by their sample size and time-consuming nature, while methods based on geographic location big data are gaining momentum. This study focuses on Xuchang, a medium-sized city in China, and systematically analyzes the current state and influencing factors of park green space utilization by mining GPS trajectory big data from April 3 to 12, 2022. Results indicate that residents' choices of park green spaces are highly diverse. Approximately 20% of visitors on holidays and weekends, and about 25% of visitors on weekdays, prefer the park green space closest to their homes. Notably, the distance threshold for park green space visits on weekdays, weekends, and holidays is 3633, 3824, and 4127 m, respectively. These distances are significantly higher than the several hundred meters specified in planning documents or commonly used in accessibility analyses. For individuals who frequently visit park green spaces, distance is the most critical influencing factor. Conversely, for those who occasionally visit, distance is not the primary consideration. For individuals who rarely or never visit park green spaces, personal attitudes play an essential role. In comparison to weekdays, the number of visitors on holidays and weekends is larger, the travel distance is longer, and they are more inclined to choose larger parks. Visits are concentrated in the afternoon and evening, and weather changes remarkably affect park green space utilization. Importantly, no compensatory effect is observed between the frequency and duration of park green space visits. These findings hold important implications for urban planning, management, and the promotion of park green space utilization.

Effects of the spatial patterns of urban parks on public satisfaction: evidence from Shanghai, China

CONTEXT

Urban parks need to meet the growing demand for activities vital to residents' well-being and urban development. A holistic understanding of public satisfaction with urban parks is a prerequisite for improving management.

OBJECTIVE

The spatial patterns and composition of urban parks vary greatly, and the objective of this study is to comprehensively investigate public satisfaction with urban parks and the impact of their structure.

METHODS

With the metropolis of Shanghai, China, as an example, we employed 111,814 social media data sets for 50 urban park sites to quantify public satisfaction via the long short-term memory model. We analyzed the internal, boundary and external dimensions of spatial patterns and described the internal landscape patterns from the perspectives of size, heterogeneity, aggregation, shape, diversity and landscape elements. Moreover, we used all-subset regression and hierarchical partitioning to quantify the relationship and mechanism of action between spatial patterns and public satisfaction.

RESULTS

The results indicate that the mean value of public satisfaction with urban parks was 0.716 (ranging from 0 to 1), which is generally positive or neutral. Satisfaction was influenced by the internal, boundary, and external spatial patterns of urban parks. The independent contribution rates of external transportation facility density (51.49%) and internal edge density (48.51%) to satisfaction.

CONCLUSIONS

We highlight the roles of spatial patterns, especially the degree of external transportation convenience and the edge density of urban parks at the landscape level. The findings provide guidance and recommendations for the planning and design of public satisfaction-oriented urban parks.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s10980-023-01615-z.

Ecosystem Services: A Social and Semantic Network Analysis of Public Opinion on Twitter

Social media data reveal patterns of knowledge, attitudes, and behaviours of users on a range of topics. This study analysed 4398 tweets gathered between 17 January 2022 and 3 February 2022 related to ecosystem services, using the keyword and hashtag "ecosystem services". The Microsoft Excel plugin, NodeXL was used for social and semantic network analysis. The results reveal a loosely dense network in which information is conveyed slowly, with homogeneous, medium-sized subgroups typical of the community cluster structure. Citizens, NGOs, and governmental administrations emerged as the main gatekeepers of information in the network. Various semantic themes emerged such as the protection of natural capital for the sustainable production of ecosystem services; nature-based solutions to protect human structures and wellbeing against natural hazards; socio-ecological systems as the interaction between human beings and the environment; focus on specific services such as the storage of atmospheric CO₂ and the provision of food. In conclusion, the perception of social users of the role of ecosystem services can help policymakers and forest managers to outline and implement efficient forest management strategies and plans.

Urban Green Space and Subjective Well-Being of Older People: A Systematic Literature Review

A growing number of articles have identified and reported the benefits and importance of urban green spaces for improving human well-being, but there is a significant knowledge gap regarding the impact of urban green spaces on the subjective well-being of older adults. The literature search (August 2015-August 2022) was derived from two major scientific databases, Google Scholar, and Web of Science. As a result, 2558 articles were found, 1527 of which were retrieved from WOS and the rest from Google Scholar. Bibliometric methods and VOSviewer software were used to screen and organize the articles in the relevant fields. Finally, 65 articles met the review criteria. The included studies aim to capture the benefits of various features of urban green spaces in meeting or enhancing the subjective well-being needs of older adults. The results of our review further support the existence of a strong link between older adults' subjective well-being and various features of urban green spaces, providing new insights for future in-depth reexamination and policy development. Furthermore, the relationship between urban green spaces and older adults' subjective well-being depends not only on the urban green spaces themselves but also on the characteristics of the older adult population that uses them.

Human health risk-based soil environmental criteria (SEC) for park soil in Beijing, China

Urban parks are important places that allow urban residents to experience nature but are also associated with the risk of exposure to contaminated soil. Therefore, it is necessary to establish appropriate soil environment criteria (SEC) to manage park soil quality. Studies on the demographic characteristics and behavioral patterns of urban park visitors are helpful for the selection of sensitive receptors and the determination of parameters in the establishment of SEC. This study explored the park visitors' demographic characteristics and behavioral patterns, and applied the results to derive SEC. Eighty-six parks in Beijing were selected, and mobile phone data were obtained to analysis the demographic characteristics and residence time of the visitors. Kruskal-Wallis test, kernel density estimation and random forest model were used for data analysis. The CLEA model was used to derive SEC. The results showed that the demographic characteristics and behavioral patterns of visitors in different types of parks were quite different. Parks were mostly used by males and visitors aged 31-45. Most visitors stayed in the park for 1-2 h, and the distance from a given visitor's home to the park was the most important factor affecting stay time. Then, several parameters such as the parameters related to the receptors and occupation period were optimized, and the SEC of sensitive parks and non-sensitive parks were derived. Exposure frequency may be the main reason for the difference of SEC between the two types of parks. The SECs of sensitive parks were higher than the soil screening values (SSVs) for class 1 land in GB36600-2018, indicating that the current SSVs for some parks may be too conservative. This study provides a reference for the formulation and revision of soil environmental standards for park land, and suggests strengthening research on human behavioral patterns.