Fusing multi-source social media data and street view imagery to inform urban space quality: a study of user perceptions at Kampong Glam and Haji Lane

Abstract

AbstractThis study proposes a novel approach to urban perception studies by integrating street view imagery and multi-source social media data to infer user perceptions and preferences of urban spaces, thereby informing placemaking strategies. With advanced pre-trained Google Cloud Vision AI, this study regards street view imagery as a baseline to compare with user-generated content from social media platforms, namely, Flickr, TripAdvisor, and X (formerly Twitter), together revealing spatial elements perceived by users and diverse demands across users groups. The research evaluates urban space qualities at two spatial levels through a case study at Kampong Glam district and Haji Lane, focusing on Uniqueness, Vitality, and Liveability derived from classic urban theories. The transition in user focus from spatial and transport features in Google Street View to activities and decorations in Flickr imagery emphasizes the spatial features that contribute to Uniqueness and Vitality. In addition, textual data from Twitter and TripAdvisor differentiate residents' and tourists' perceptions of Liveability, encompassing aspects like History, Religion, Space, and Activity. The findings articulate alignments of users' perceptions from street to district levels and diverse preferences on spatial features contributing to Uniqueness, Vitality, and Liveability, offering valuable insights for user-centric placemaking and urban planning.