A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Measuring pedestrians' movement and building a visual-based attractiveness map of public spaces using smartphones
Abstract Accurately measuring the distribution of vitality in urban public spaces and evaluating the attractiveness index of landscape elements can enhance the precision of public space design and the rational planning of urban microupdate strategies. This study introduces a method based on the SLAM algorithm to create a 3D visual exposure analysis and applied in two squares in Macau to calculate the relationship between pathfinding decisions and visual exposure. The results demonstrate that both the extent of visual exposure (seen from the observer) and the area of isovist field (seen from the object) can statistically indicate the attractiveness index of a space. Consequently, an attractiveness map of the site can be constructed. This study effectively captures walking trajectories and visual data in real-world settings, integrating site-specific and pedestrian information into a digital twin system. This approach not only advances quantitative methodologies but also facilitates postoccupancy evaluations of public space usage and environmental behavior research, thereby expanding the potential for future investigations in this domain.
Graphical abstract Display Omitted
Highlights We distinguish active attention and passive notice in pedestrians via visual exposure comparison. We developed the SLAM algorithm to create a 3D visual exposure analysis method. Our work introduces a visual attraction index scoring system for public spaces. Landmark buildings often dominate visual attraction, overshadowing nearby structures. Green landscapes generally score lower than average in visual attraction.
Measuring pedestrians' movement and building a visual-based attractiveness map of public spaces using smartphones
Abstract Accurately measuring the distribution of vitality in urban public spaces and evaluating the attractiveness index of landscape elements can enhance the precision of public space design and the rational planning of urban microupdate strategies. This study introduces a method based on the SLAM algorithm to create a 3D visual exposure analysis and applied in two squares in Macau to calculate the relationship between pathfinding decisions and visual exposure. The results demonstrate that both the extent of visual exposure (seen from the observer) and the area of isovist field (seen from the object) can statistically indicate the attractiveness index of a space. Consequently, an attractiveness map of the site can be constructed. This study effectively captures walking trajectories and visual data in real-world settings, integrating site-specific and pedestrian information into a digital twin system. This approach not only advances quantitative methodologies but also facilitates postoccupancy evaluations of public space usage and environmental behavior research, thereby expanding the potential for future investigations in this domain.
Graphical abstract Display Omitted
Highlights We distinguish active attention and passive notice in pedestrians via visual exposure comparison. We developed the SLAM algorithm to create a 3D visual exposure analysis method. Our work introduces a visual attraction index scoring system for public spaces. Landmark buildings often dominate visual attraction, overshadowing nearby structures. Green landscapes generally score lower than average in visual attraction.
Measuring pedestrians' movement and building a visual-based attractiveness map of public spaces using smartphones
Ai, Deng (author) / Wang, Haofeng (author) / Kuang, Da (author) / Zhang, Xiuqi (author) / Rao, Xiaojun (author)
2023-12-14
Article (Journal)
Electronic Resource
English
Pedestrians, urban spaces and health
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