Seoul street-view database for urban environment research
Hokyun Kim , Bohyun Cho , Hyoji Choi , Jonghyun Kim , Yurim Jang , Miru Hong , Min Hyeong Kim , Bon Mu Do , Wonchang Hur , Bogang Jun , Donghyeon Yu , Bo-yong Park
Computational Urban Science ›› 2026, Vol. 6 ›› Issue (1) : 12
Seoul street-view database for urban environment research
Street-view imagery provides valuable insights into the physical and social dimensions of urban environments. Seoul, South Korea, known for its rapid urban transformation, presents a distinctive blend of traditional urban centers and newly developed districts. To gain a comprehensive understanding of Seoul’s urban development, we constructed a street-view database spanning 14 years (2010–2023), comprising 423,353 images. To enhance data quality, noise components within the images were removed using advanced object detection and image inpainting techniques. We then segmented objects relevant to the commercial ecosystem and extracted features related to the intensity, shape, and texture for each object. The dataset includes street-view images, object masks, and their associated feature sets, all of which are publicly accessible to the research community. This resource offers a robust foundation for examining dynamic changes in Seoul’s urban environment. By leveraging this dataset, researchers can investigate the unique characteristics of Seoul’s evolving urban landscape and explore their implications for the commercial area.
Street-view imagery / Urban environment / Object detection / Segmentation / Feature engineering
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The Author(s)
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