Spatial Design Network Analysis (sDNA)

Both analyse the configuration of street networks, but sDNA is link-based and geometrically accurate rather than relying on hand-drawn axial lines. It uses real segment lengths, turn angles and even 3D gradient, lets you blend metric, angular and topological distance, supports weighting links by population or floorspace, and always works within explicit radii. This makes results more reproducible and better integrated with GIS, while still producing the closeness- and betweenness-style configurational measures that space syntax pioneered.

Closeness (reported as mean distance or related accessibility measures) describes how easily a link reaches everything else within its radius — it captures destination accessibility and centrality. Betweenness counts how often a link lies on the shortest routes between other links, capturing through-movement or flow potential. A quiet cul-de-sac near many shops can have high closeness but low betweenness, whereas a busy arterial may have high betweenness; the two together describe a segment's dual role as place and route.

sDNA computes every measure within a bounded radius — a metric, angular or topological bandwidth such as 800 metres or 5 minutes — that defines each link's network neighbourhood. Small radii reveal local, walkable structure relevant to pedestrians, while large radii capture city-wide vehicular structure. Because a link can be locally central but globally peripheral (or vice versa), conclusions depend on the radius chosen, so analysts report a range of radii rather than a single value.