Urban volumetrics: spatial complexity and wayfinding, extending space syntax to three dimensional space

Authors: Lingzhu Zhang, Alain J F Chiaradia

20 pages, 5 figures, 2 tables

Results of the summarizing process for the arXiv paper: 2012.14419v1

  • Comprehensive Summary
  • Key points
  • Layman's Summary
  • Blog article
The summary is not ready yet

Abstract: Wayfinding behavior and pedestrian movement pattern research relies on objective spatial configuration representation and analysis, such as space syntax, to quantify and control for the difficulty of wayfinding in multi-level buildings and urban built environments. However, the space syntax's representation oversimplifies multi-level vertical connections. The more recent segment and angular approaches to space syntax remain un-operationalizable in three dimensional space. The two dimensional axial-map and segment map line representations are reviewed to determine their extension to a novel three dimensional space line representation. Using an extreme case study research strategy, four representations of a large scale complex multi-level outdoor and indoor built environment are tested against observed pedestrian movement patterns N = 17,307. Association with the movement pattern increases steadily as the representation increases toward high three-dimensional space level of definition and completeness. A novel hybrid angular-Euclidean analysis was used for the objective description of three dimensional built environment complexity. The results suggest that pedestrian wayfinding and movement pattern research in a multi-level built environment should include interdependent outdoor and indoor, and use full three-dimensioanal line representation.

Submitted to arXiv on 28 Dec. 2020

Tools for this paper

Explain it differently 3 free rewrites left today
Export BibTeX · RIS (Zotero, Mendeley, EndNote) · Markdown (Notion, Obsidian) · Premium
Citation alerts Premium
Journal club Slides to present it Premium
For journalists Press kit and hype check Premium

Ask questions about this paper to our AI assistant

You can also chat with multiple papers at once here.

⚠The license of the paper does not allow us to build upon its content and the AI assistant only knows about the paper metadata rather than the full article.

Figures and plots

Ask about a figure by number or use its question button to request visual analysis. Up to two figures and four image panels per question. Values read from plots are approximate; check the original data.

AI assistant instructions?

Assess the quality of the AI-generated content by voting

Score: 0

Why do we need votes?

Votes are used to determine whether we need to re-run our summarizing tools. If the count reaches -10, our tools can be restarted.

The previous summary was created more than a year ago and can be re-run (if necessary) by clicking on the Run button below.

⚠The license of this specific paper does not allow us to build upon its content and the summarizing tools will be run using the paper metadata rather than the full article. However, it still does a good job, and you can also try our tools on papers with more open licenses.

Disclaimer: The AI-based summarization tool and virtual assistant provided on this website may not always provide accurate and complete summaries or responses. We encourage you to carefully review and evaluate the generated content to ensure its quality and relevance to your needs.