Small urban green spaces are abundant in densely populated urban areas, but little is known about their impact on the urban heat island effect and thermal comfort. Therefore, this study selected as research sites four small urban green spaces in a typical high-density built-up area, Chuo Ward in Tokyo, Japan. The ENVI-met software 5.1.1 simulation method was used to analyze these sites’ microclimate and thermal comfort conditions. The following are the results: (1) Small urban green spaces significantly reduce urban air temperatures, particularly during hot weather, with temperature reductions ranging from 2.40 °C to 2.67 °C, consistently lower than the highest temperatures in Tokyo’s Chuo Ward, mainly between 1:00 and 2:00 p.m. (2) Thermal comfort analysis indicates that small urban green spaces can significantly improve urban thermal comfort during the day, particularly around noon, by reducing one or two thermal comfort levels compared to typical urban street blocks. However, these differences gradually diminish throughout the evening and night, and thermal comfort inside and outside green spaces becomes more uniform. (3) Green space size is not the only factor influencing thermal comfort; the layout of plants within the green space and the layout of the surrounding buildings also have an impact. Despite their small size, even small green spaces can significantly enhance comfort. This study highlights the need to promote urban sustainability through the extensive integration of small green spaces in dense urban environments. Small green spaces can serve as a high-frequency, low-cost solution for environmental sustainability by addressing the increasingly severe urban heat island effect as well as environmental challenges that in the urbanization process.
Urban green spaces (UGSs) can meet the spiritual and cultural needs of citizens and provide various ecosystem services. In the context of the COVID-19 pandemic, the utilization of UGSs has been affected in various countries worldwide. This study considered 13 UGSs in Guangzhou, China, as examples. It obtained user check-in data by sampling the check-in pages of Sina Weibo locations using a Python-based web crawler program. The study was conducted for 731 days from 1 October 2019 to 30 September 2021, during different phases of the pandemic. Based on automated Chinese corpus recognition technology, statistical results were obtained after periodization and sentiment calculation. The study assessed the pandemic’s impact on the use of UGSs by analyzing the time, frequency, and emotions of residents visiting UGSs. The study concluded that the emotions of UGS users during COVID-19 tended to be positive. They tended to choose UGSs with low expected population density and visited UGSs on weekdays. Additionally, the religious attributes of UGSs also influenced their utilization.
We employed publicly available user-generated content (UGC) data from the website Tripadvisor and developed an autoregressive integrated moving average (ARIMA) model using the R language to analyze the seasonality of the use of urban green space (UGS) in Okinawa under normal conditions and during the COVID-19 pandemic. The seasonality of the use of ocean-area UGS is primarily influenced by climatic factors, with the peak season occurring from April to October and the off-peak season from November to March. Conversely, the seasonality of the use of non-ocean-area UGS remains fairly stable throughout the year, with a relatively high number of visitors in January and May. The outbreak of the COVID-19 pandemic greatly impacted visitor enthusiasm for travel, resulting in significantly fewer actual postings compared with predictions. During the outbreak, use of ocean-area UGS was severely restricted, resulting in even fewer postings and a negative correlation with the number of new cases. In contrast, for non-ocean-area UGS, a positive correlation was observed between the change in postings and the number of new cases. We offer several suggestions to develop UGS management in Okinawa, considering the opportunity for a period of recovery for the tourism industry.