Analysis of spatial form and structure of commercial pedestrian blocks based on Isovist and big data

Abstract

Commercial pedestrian blocks play an indispensable role in urban life. With the development of urban commercial intensification, the construction of commercial pedestrian blocks has ushered in a period of rapid development. To explore the spatial form and structural features of commercial pedestrian blocks, we examined the Qingniwa-Tianjin Street commercial pedestrian block in Dalian, China. We developed a new quantitative research method, using Isovist-App software simulation, big data statistics and Arc GIS analysis methods to explore the spatial morphological structure characteristics of commercial districts. The results show that Tianjin Street’s pedestrian axis has low spatial permeability and monotonous browsing routes. This suggests that the outdoor pedestrian space design does not attract crowds to wander around and stroll. The overall centrality of the space was relatively high, and the spatial accessibility was good. The walking route provided a wide field of vision, stimulating people’s desire for exploration. The space is highly guided, and people can visit according to the designed route. There is a big difference in the spatial aggregation and dispersion of POI facilities. Transportation, sports, and leisure facilities are the most evenly distributed, while shopping and life service street facilities vary considerably. During holidays, the intensity and duration of crowd activities are the largest, followed by working days and weekends. The people in the block mainly gather in the western and southern commercial complexes, and the attractiveness of outdoor pedestrian streets is lower than that of commercial complexes. Node space B has pedestrian streets with varying spatial interfaces and inconsistent visual appeal. The results can be used to support the spatial form and structural renewal design of commercial pedestrian blocks. The methods presented in this study provide a quantitative approach for the spatial analysis of other functional areas in the city.

A Spatial Visual Quality Evaluation Method for an Urban Commercial Pedestrian Street Based on Streetscape Images—Taking Tianjin Binjiang Road as an Example

“…The higher the spatial distribution of the street walking index, the walking safety index, the facility richness index, the positive business index, and the street greening index, the higher the corresponding concentration of people, which echoes the S-O-R (stimuli-organism-response) theory, which focuses on people's perception and behaviors in environmental stimuli and argues that the environmental stimuli affect the state of the individual's organism and then stimulate behaviors and responses [42,43]. The theory has been introduced to the study of pedestrian behavior in recent years, and the S-O-R theory provides a suitable theoretical tool for exploring the effects of microscale environmental stimuli on individual psychology and behavior and for exploring the human-environment relationship in pedestrian behavior.…”

Advancing Urban Life: A Systematic Review of Emerging Technologies and Artificial Intelligence in Urban Design and Planning

“…[31] Examines the Street commercial pedestrian block characteristics using Isovist_App software simulation and spatial analysis. [55] This study employs machine learning and a Fully Convolutional Network (FCN) for image segmentation to improve street quality. [31] Conducts a deep learning-based classification analysis of public space images.…”