Geolocated social media as a rapid indicator of park visitation and equitable park access

Geographic distribution of Flickr photo user days.

Geographic distribution of Flickr photo user days (FUD) and Twitter user days (TUD). FUD and TUD are classified using Jenks optimization in order to illustrate variation given the positively-skewed distribution.

Assistant professor of urban planning Zoé Hamstead and collaborators analyze geographic human visitation dynamics in all New York City parks using Twitter and Flickr data.

Understanding why some parks are used more regularly or intensely than others can inform ways in which urban parkland is developed and managed to meet the needs of a rapidly expanding urban population. Although geolocated social media (GSM) indicators have been used to examine park visitation rates, studies applying this approach are generally limited to flagship parks, national parks, or a small subset of urban parks. Here, we use geolocated Flickr and Twitter data to explore variation in use across New York City's 2143 diverse parks and model visitation based on spatially-explicit park characteristics and facilities, neighborhood-level accessibility features and neighborhood-level demographics.

Findings indicate that social media activity in parks is positively correlated with proximity to public transportation and bike routes, as well as particular park characteristics such as water bodies, athletic facilities, and impervious surfaces, but negatively associated with green space and increased proportion of minority ethnicity and minority race in neighborhoods in which parks are located. Contrary to previous studies which describe park visitation as a form of nature-based recreation, our findings indicate that the kinds of green spaces present in many parks may not motivate visitation.

From a social equity perspective, our findings may imply that parks in high-minority neighborhoods are not as accessible, do not accommodate as many visitors, and/or are of lower quality than those in low-minority neighborhoods. These implications are consistent with previous studies showing that minority populations disproportionately experience barriers to park access. In applying GSM data to questions of park access, we demonstrate a rapid, big data approach for providing information crucial for park management in a way that is less resource-intensive than field surveys.


Zoé Hamstead, Assistant Professor
Department of Urban & Regional Planning

David Fisher
Natural Capital Project, Stanford University

Rositsa T. Ilieva
Urban Systems Lab, The New School

Spencer A.Wood
Natural Capital Project, Stanford University
School of Environmental and Forest Sciences, University of Washington

Timon McPhearson
Urban Systems Lab, The New School
Cary Institute of Ecosystem Studies
Stockholm Resilience Centre, Stockholm University

Peleg Kremer
Department of Geography and the Environment, Villanova University


Computers, Environment and Urban Systems

Date Published