Lingzhu Zhang and Chiaradia, A.J.F. 2022. Walking in the cities without ground, how 3D complex network volumetrics improve analysis. Environment and Planning B: Urban Analytics and City Science. 49 (7), pp. 1857-1874. https://doi.org/10.1177/23998083211070567
| Title | Walking in the cities without ground, how 3D complex network volumetrics improve analysis |
|---|---|
| Type | Journal article |
| Authors | Lingzhu Zhang and Chiaradia, A.J.F. |
| Abstract | Pedestrian route choice, wayfinding behaviour and movement pattern research rely on objective spatial configuration model and analysis. In 3D indoor and outdoor multi-level buildings and urban built environments (IO-ML-BE), spatial configuration analysis allows to quantify and control for route choice and wayfinding complexity/difficulty. Our contribution is to compare the interaction of the level of definition (LOD) of indoor and outdoor multi-level pedestrian network spatial models and complexity metric analyses. Most studies are indoor or outdoor and oversimplify multi-level vertical connections. Using a novel open data set of a large-scale 3D centreline pedestrian network which implement transport geography 2D data model principles in 3D, nine spatial models and twelve spatial complexity analyses of a large-scale 3D IO-ML-BE are empirically tested with observed pedestrian movement patterns (N = 17,307). Bivariate regression analyses show that the association with movement pattern increases steadily from R2 ≈ 0.29 to 0.56 (space syntax, 2.5D) and from R2 ≈ 0.54 to 0.72 (3D sDNA) as the 3D transport geography spatial model LOD and completeness increases. A multivariate stepwise regression analysis tests the bi-variate findings. A novel 3D hybrid angular-Euclidean analysis was tested for the objective description of 3D multi-level IO-ML-BE route choice and wayfinding complexity. The results suggest that pedestrian route choice, wayfinding and movement pattern analysis and prediction research in a multi-level IO-ML-BE should use high-definition 3D transport geography network spatial model and include interdependent outdoor and indoor spaces with detailed vertical transitions. |
| Journal | Environment and Planning B: Urban Analytics and City Science |
| Journal citation | 49 (7), pp. 1857-1874 |
| ISSN | 2399-8083 |
| 2399-8091 | |
| Year | 2022 |
| Publisher | Sage |
| Accepted author manuscript | File Access Level Open (open metadata and files) |
| Digital Object Identifier (DOI) | https://doi.org/10.1177/23998083211070567 |
| Web address (URL) | https://doi.org/10.1177/23998083211070567 |
| Publication dates | |
| Published online | 27 Jan 2022 |