Abstract
Urban green spaces are really vital for the well-being of human in urban areas. In urban planning for green space site selection, the study of the bond among the usage of green spaces and their categories that really influence their use can provide useful references. A spatial and temporal research on the allocation of visitors in 157 green areas was carried out in Shanghai to know which green spaces are denser or crowdsourced by utilizing social media big data. We evaluated the association with statistical testing and Kernel Density Estimation among the spatial pattern of the visitor spread in urban green areas. We used check-in data from social media to test this study comparing the number of humans who visit various green parks. We have classified green areas into various categories and our main findings are focused on their characteristics: (1) famous category of green parks according to visitors' preferences, (2) Differences in the number of visitors by daytime, and (3) crowdsourced area based upon number of check-ins. The main aim of this article is to remind policy makers of the value of providing local people access to green areas and to empower cities with a framework for contacting green parks with the purpose of increasing the comfort of urban people with the architecture of smart city.