摘要
Urban parks are an important part of urban recreational spaces,and the development of analysis framework of recreational behavior and space is helpful for the design of urban parks to better meet the activity and usage requirements of visitors.In this paper,Xiaohong Stone Carving Park in Nanjing was taken as the research object to explore the relationship between landscape space and user behavior for design feedback.The orthographic image technology of unmanned aerial vehicle(UAV)and machine deep learning were used to analyze users behavior activities in the park,and the spatial characteristics of each node in the park were evaluated by semantic differential scale to explore the potential causes of behavior activities.The results showed that①there were significant differences in the number of visitors on holidays and working days,and young people and children were the main users.②The users activity of the park differed greatly on the inner and outer tour roads,and the users showed stronger willingness to stay on the inner tour roads.Recreational activities received more attention than cultural ones.③The overall distribution of users was significantly affected by hydrophilicity,and the recreational behavior and activity type were affected by multiple factors which include the hydrophilicity,safety,accessibility of cultural relics and the amount of recreational facilities.Finally,the enhanced strategies such as improving the cultural tour system,establishing hydrophilic safety belts and optimizing recreational facilities were put forward.
