Journal cover Journal topic
AGILE: GIScience Series Open-access proceedings of the Association of Geographic Information Laboratories in Europe
Journal topic
Articles | Volume 3
AGILE GIScience Ser., 3, 72, 2022
AGILE GIScience Ser., 3, 72, 2022
24 Jun 2022
24 Jun 2022

Enriching geospatial data with computer vision to identify urban environment determinants of social interactions

Francisco Garrido-Valenzuela1,2, Sander van Cranenburgh1, and Oded Cats2 Francisco Garrido-Valenzuela et al.
  • 1Transport and Logistics Group, Department of Engineering Systems and Services, Faculty of Technology, Policy, and Management, Delft University of Technology, Delft, the Netherlands
  • 2Transport and Planning, Faculty of Civil Engineering and Geosciences, Delft University of Technology, the Netherlands

Keywords: social interaction, object recognition, urban design, computer vision

Abstract. Characteristics of urban space (co-)determine human behaviour, including their social interaction patterns. However, despite numerous studies that have examined how the urban space impacts social interactions, their relationships are still poorly understood. Recent developments in computer vision and machine learning fields offer promising new ways to analyse and collect data on social interactions. This study proposes a new computer vision-based approach to study how the urban space impacts social interactions. The proposed method uses pre-trained object detection models to detect social interactions (including their geo-locations) from street-view imagery. After that, it regresses urban space characteristics – which are also detected using object detection models – on social interactions. For this study, 294,852 street-level images from three Dutch cities are analysed. Results from linear regression analysis show that for these three Dutch cities people tend to meet in places with a strong presence of recreational attractions and bicycles. Also, the results of data collection and image processing can be used to identify the areas most likely to produce social interactions in urban space to conduct urban studies.

Publications Copernicus