Urban network analysis: centrality, demand flows, accessibility, mixed uses, and statistics
Cityseer provides Processing algorithms for urban network analysis: network centrality
(closeness and betweenness), demand-weighted flow betweenness from weighted origins and
destinations, land-use accessibility, mixed-use diversity, and localised statistics. Metrics
are computed on a dual graph representation where each road segment is a node connected
to its neighbours. All distances are network distances walked along the streets, not
straight-line distances, with support for multiple distance thresholds, shortest and
simplest (angular) paths, boundary polygons, and optional adaptive sampling.
Requires the cityseer Python library: pip install cityseer
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