Abstract
Spatial Design Network Analysis (sDNA) is a toolbox for 3-d spatial network analysis, especially street/path/urban network analysis, motivated by a need to use network links as the principal unit of analysis in order to analyse existing network data. sDNA is usable from QGIS & ArcGIS geographic information systems, AutoCAD, the command line, and via its own Python API. It computes measures of accessibility (reach, mean distance/closeness centrality, gravity), flows (bidirectional betweenness centrality) and efficiency (circuity) as well as convex hull properties, localised within lower- and upper-bounded radial bands. Weighting is flexible and can make use of geometric properties, data attached to links, zones, matrices or combinations of the above. Motivated by a desire to base network analysis on route choice and spatial cognition, the definition of distance can be network-Euclidean, angular, a mixture of both, custom, or specific to cyclists (avoiding slope and motorised traffic). In addition to statistics on network links, the following outputs can be computed: geodesics, network buffers, accessibility maps, convex hulls, flow bundles and skim matrices. Further tools assist with network preparation and calibration of network models to observed data.To date, sDNA has been used mainly for urban network analysis both by academics and city planners/engineers, for tasks including prediction of pedestrian, cyclist, vehicle and metro flows and mode choice; also quantification of the built environment for epidemiology and urban planning & design.
Highlights
As most Spatial Design Network Analysis (sDNA) users are not themselves programmers, an instance of R-portable [35] is included in the distribution to make use of relevant R libraries, and this is called from the front end tools without users needing to program in R
The sDNA source includes a suite of automated system level tests which are run from the Debug configuration of the Visual Studio project
Along with data and batch file of command line calls to sDNA to generate output, are provided as supplementary material
Summary
SDNA computes various measures of reach, including weight, junction and link count, and length; mean distance (the inverse of closeness), bidirectional betweenness (weighted either by product or a variant of the Huff [32] model without distance decay, as the latter can be handled using multiple radii), circuity [14,15] and geometric properties of the convex hull of the radius These can all be localised within lower- and upper-bound networkEuclidean radii and weighted by user defined expressions based on link geometry, zoning systems, origin–destination matrices or network attached data (the latter giving a means to import building data via GIS join). – – Mean distance between zones under chosen metric Total weight of geodesics between zones Number of geodesics between zones
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