Urban Park Spatial Characteristics influence on visiting pattern:
A geo-located social media approach
This study applies statistical analysis methods to geo-located social media data (Twitter) to inspect 643 urban parks in Singapore. This study not only focuses on the critical factors affecting visitors’ visiting patterns but proposes novel urban park spatial characteristic measures responding to each attribute’s embedded effect, such as individual, cluster, or composite cluster. The findings indicate that visitors’ density and diversity are driven by different sets of park attributes. Our results provide a framework for the future planning and design of urban parks, which responds to dynamic park visit patterns with clarity on the priority of the spatial characteristics in response to the designed urban park typology.
