Analyze the usage of urban greenways through social media images and computer vision

亚特兰大 社会化媒体 大都市区 建筑 城市规划 计算机科学 地理 社会学 万维网 工程类 土木工程 考古
作者
Yang Song,Huan Ning,Xinyue Ye,Divya Chandana,Shaohua Wang
出处
期刊:Environment And Planning B: Urban Analytics And City Science [SAGE Publishing]
卷期号:49 (6): 1682-1696 被引量:30
标识
DOI:10.1177/23998083211064624
摘要

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.
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