Varoudis, Tasos;
Hanna, Sean;
(2024)
Beyond Axial Lines: High-Resolution Geometric Analysis of London's Urban Fabric Using LIDAR Scans.
In:
Proceedings of SSS14: The 14th International Space Syntax Symposium.
Space Syntax Network: Nicosia, Cyprus.
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Abstract
Space Syntax urban analyses have typically been performed on high-level approximations of the spatial network, in the form of axial lines (Penn et al. 1998), street segments (Hillier & Iida 2005), or similar, which necessarily lack some information at the smallest scales. Yet some key theoretical principles rely explicitly on locally observable features: intelligibility (Hillier et al. 1987), for example, is the correlation between long-range structure and that of the local. This paper investigates the highest resolution model of London’s geometry yet available to determine the degree to which local surface geometries correlate with long-range structural features of the urban network, particularly global measures of network centrality: integration and choice. By employing a LIDAR scan of ground and building surface geometry encompassing 2800 km^2 around London, captured as a dense cloud of points and transformed into 200-meter squares of 200 pixels, the research first queried the degree to which long-range structural features of the network are immediately evident in the local surface geometry data through clustering and unsupervised learning methods and trace its relationship to longer-scale centrality measures. We conclude that traditional measures of network centrality can be learned to be predicted from local features, suggesting an alternative to traditional syntactical intelligibility. Finally, we determine the scale at which the differentiation between foreground and background networks is most clearly discernible through local features is approximately 4 km, which coincides with that seen to best predict movement and is within the range of a typical journey length.
| Type: | Proceedings paper |
|---|---|
| Title: | Beyond Axial Lines: High-Resolution Geometric Analysis of London's Urban Fabric Using LIDAR Scans |
| Event: | The 14th International Space Syntax Symposium (SSS14) |
| Location: | Nicosia |
| Dates: | 24 Jun 2024 - 28 Jun 2024 |
| Open access status: | An open access version is available from UCL Discovery |
| Publisher version: | https://cyprusconferences.org/14sss/ |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | space syntax, intelligibility, LIDAR, machine learning, neural networks |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment > The Bartlett School of Architecture |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10194319 |
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