Our aim is to promote the practice of spatial network analysis through
- Provision of software
- Provision of training
- Provision of a knowledge base as a foundation for evidence based decisions and policy
sDNA differs from previous forms of spatial network analysis by standardizing on the network link, thus enabling compatibility with existing link-node data and datasets. Our continuous space enhancement to existing network algorithms allows us to ensure that accuracy is not lost by treating links as atomic rather than divisible entities.
sDNA is easy to use with existing map data, and we support numerous workflows:
- ArcGIS and QGIS for analysts and researchers
- Standalone shapefile processing for other GIS users
- Autocad for architects and designers
- Command line interface for scripting
- Python interfaces for hackers
For more on the theory behind sDNA, see the following papers
Cooper, C. and Chiaradia, A. sDNA: how and why we reinvented Spatial Network Analysis for health, economics and active modes of transport. In Malleson, N. et al: GIS Research UK (GISRUK) 2015 Proceedings. http://dx.doi.org/10.6084/m9.figshare.1491375
Background from network analysis perspective including continuous space algorithm
- Chiaradia, A., Cooper, C., Wedderburn, M. Network geography and accessibility. Transport Practitioners Meeting, London, 2014.
Background on why network analysis makes sense for transport modelling
- Cooper, C. H. V. (2015) Spatial localisation of closeness and betweenness measures: a self-contradictory but useful form of network analysis. International Journal of GIS
Tidying up analytical details unaddressed in previous spatial network analysis literature
Examples of work done with sDNA:
- Cooper, C., Fone, D., Chiaradia, A. (2014) Measuring the impact of spatial network layout on community social cohesion: a cross-sectional study International Journal of Health Geographics 2014, 13:11 doi:10.1186/1476-072X-13-11
- Sarkar, C., Webster, C., Gallacher, J. (2014). Healthy Cities: Public health through urban planning Edward Elgar. ISBN:9781781955710 DOI:10.4337/9781781955727
- Sarkar, C., Webster, C., Gallacher, J. (2014). Morphometric Analysis of the Built Environment in UK Biobank: Data Analyses and Specification Manual. Cardiff University.
The sDNA Logo is actually a spatial network coloured according to one of the sDNA Output Measures.
Can you guess which one?