"Cities and towns have often developed infrastructure that enabled a variety of socio-economic interactions. Street networks within these urban settings provide key access to resources, neighborhoods, and cultural facilities. Studies on settlement scaling have also demonstrated that a variety of urban infrastructure and resources indicate clear population scaling relationships in both modern and ancient settings. This article presents an approach that investigates past street network centrality and its relationship to population scaling in urban contexts. Centrality results are compared statistically among different urban settings, which are categorized as orthogonal (i.e., planned) or self-organizing (i.e., organic) urban settings, with places having both characteristics classified as hybrid. Results demonstrate that street nodes have a power law relationship to urban area, where the number of nodes increases and node density decreases in a sub-linear manner for larger sites. Most median centrality values decrease in a negative sub-linear manner as sites are larger, with organic and hybrid urban sites’ centrality being generally less and diminishing more rapidly than orthogonal settings. Diminishing centrality shows comparability to modern urban systems, where larger urban districts may restrict overall interaction due to increasing transport costs over wider areas. Centrality results indicate that scaling results have multiples of approximately ⅙ or ⅓ that are comparable to other urban and road infrastructure, suggesting a potential relationship between different infrastructure features and population in urban centers. The results have implications for archaeological settlements where urban street plans are incomplete or undetermined, as it allows forecasts to be made on past urban sites’ street network centrality. Additionally, a tool to enable analysis of street networks and centrality is provided as part of the contribution."
From https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0259680
Construction
Data: The subfolders contain the shapefile data for site street networks. Each subfolder represents a site analysed or where data were gathered. The subfolders also contain network centrality output and other network data; the nodeCentrality.csv file in the output subfolder is the file that contains centrality outputs used in the analysis for each site.
centrality_results_median.csv: The file contains centrality results for different urban places collected. Data indicate: the urban name, area, number of nodes (No. Nodes), node density (No. Nodes/Area), different median centrality measures (e.g., betweenness, closeness, etc.), period streets date to, the street period, which is a simplified indication for the main period the street likely dates to, Gini coefficient values that show disparity within centrality values, type of cities (orthogonal, organic, or hybrid (i.e. mixed), region where the data are from, and how complete the data are (complete, mostly complete, or partially complete). References are provided for sources where data are provided. Additionally, a Global Efficiency, which measures how well nodes communicate or connect in a network (Porta et al. 2006), metric is given as a measure for overall centrality, although the values are not used in the research paper’s analysis.
Locations: This folder provides the shapefile locations of the urban data used.
StreetCentrality.zip: This is the Python (3.6) project used to conduct the network analysis. The code is provided along with information on running the code and analysis conducted.
Yale University