Abstract
Spatial Networks represent the connectivity structure between units of space as a weighted graph whose links are weighted as to the strength of connections. In case of urban spatial networks, the units of space correspond closely to streets and in architectural spatial networks the units correspond to rooms, convex spaces or star-convex spaces. Once represented as a graph, a spatial network can be analysed using graph theory and spectral graph theory. We present four steps of modelling a spectrum for an urban spatial network; present an implementation of a state-ofthe-art spectral graph-drawing algorithm and showcase a Spatial Eigenvector Centrality index, which is based on a novel definition of spatial networks based on Fuzzy Closeness indicators computed using Easiest Path distances.
Original language | English |
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Title of host publication | Proceedings of the Symposium on Simulation for Architecture and Urban Design (simAUD 2016) |
Editors | Ramtin Attar, Angelos Chronis, Sean Hanna, Michela Turrin |
Publisher | simAUD |
Pages | 103-110 |
Number of pages | 8 |
ISBN (Print) | 978-1-365-05872-1 |
Publication status | Published - 2016 |
Event | SimAUD EU 2016: 7th annual Symposium on Simulation for Architecture and Urban Design - London, United Kingdom Duration: 16 May 2016 → 18 May 2016 |
Conference
Conference | SimAUD EU 2016: 7th annual Symposium on Simulation for Architecture and Urban Design |
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Country/Territory | United Kingdom |
City | London |
Period | 16/05/16 → 18/05/16 |
Keywords
- Spatial Network Analysis
- Spectral Graph Theory
- Spatial Eigenvector Centrality
- Spectral Graph Drawing
- Dominant Eigenvectors
- Generalized Power Iteration