Analyze the usage of urban greenways through social media images and computer vision
Document Type
Article
Publication Date
7-1-2022
Abstract
Urban greenway is an emerging form of urban landscape offering multifaceted benefits to public health, economy, and ecology. However, the usage and user experiences of greenways are often challenging to measure because it is costly to survey such large areas. Based on the online postings from Instagram in 2017, this paper used Computer Vision (CV) technology to analyze and compare how the general public uses two typical greenway parks, The High Line in New York City and the Atlanta Beltline in Atlanta. Face and object detection analysis were conducted to infer user composition, activities, and key experiences. We presented the temporal patterns of Instagram postings as well as the group gatherings, smiling, and representative objects detected from photos. Our results have shown high user engagement levels for both parks while teens are significantly underrepresented. The High Line had more group activities and was more active during weekdays than the Atlanta Beltline. Stronger sense of escape and physical activities can be found in Atlanta Beltline. In summary, social media images like Instagram can provide strong empirical evidence for urban greenway usage when combined with artificial intelligence technologies, which can support the future practice of landscape architecture and urban design.
Identifier
85122854358 (Scopus)
Publication Title
Environment and Planning B Urban Analytics and City Science
External Full Text Location
https://doi.org/10.1177/23998083211064624
e-ISSN
23998091
ISSN
23998083
First Page
1682
Last Page
1696
Issue
6
Volume
49
Grant
OAC-2112356
Fund Ref
National Science Foundation
Recommended Citation
Song, Yang; Ning, Huan; Ye, Xinyue; Chandana, Divya; and Wang, Shaohua, "Analyze the usage of urban greenways through social media images and computer vision" (2022). Faculty Publications. 2833.
https://digitalcommons.njit.edu/fac_pubs/2833