Space syntax and potentials for predicting walkability and pedestrian movement: axial and visual graph analysis, Jolfa neighborhood

Document Type : Research article

Authors

1 Laboratory of Urban Morphology Studies, University of Art, Tehran, Iran; Department of Urban Planning, Faculty of Engineering, Sheikhbahaee University, Isfahan, Iran

2 Urban Planning and Design Department, College of Architecture and Urban Planning, Art University of Isfahan, Isfahan, Iran.

3 Urban Planning and Development Research Group, Academic Center for Education, Culture and Research (ACECR), Alborz, Iran

10.22059/jurbangeo.2023.351426.1760

Abstract

According to the theory of natural movement, street networks interact with pedestrian movement and walkability. In addition to permeability criteria, visual perception has an impact on pedestrian preferences and behaviors by providing a capacity for understanding and wayfinding. This research aims to investigate the correlation between the visual and spatial characteristics of the environment in the Jolfa neighborhood of Isfahan city. The set of space syntax tools, including Axial, Isovist, and Visual Graph Analysis, were used to quantify and interpret the configurational and visual criteria in the historical area of Jolfa. The Spearman correlation coefficient was used to calculate the correlation between both integration and connectivity with isovist area, isovist perimeter, compactness, occlusivity, through-vision, and visual clustering. The results show that, in addition to integration, connectivity, and intelligibility, visual properties (i.e., isovist area, isovist perimeter, and occlusivity) had a significant impact on movement patterns in this area. To Validate the results, the agent-based model was used to compare the space syntax simulation of the pedestrian movement with the actual environment. It was shown that visual features derived from space syntax can predict pedestrian movement in the real world. Visual characteristics are complementary to spatial configuration and can help with spatial perception, wayfinding, and pedestrian movement.

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