Network Population Density for Southwark
Using the excellent SANET extension for ArcGIS 9.3 I was able to take some of my data for Southwark that I had geocoded to address level, and estimate the population density using the OS Mastermap ITN product. The procedure is essentially a Kernel Density Estimation that takes place on a given network rather than across 2D space, this effectively controls for the effect of spatial structure, such as urban form, of which the data relates to residential locations. The estimation is made for c.300,000 people in Southwark on a network with around 30,000 road segments so it is to be expected that the calculation takes several hours to run. The KDE process is parameterised in much the same way as the straightforward density estimation procedures in the ARCGIS Spatial Analyst toolboxes, bandwidth and cell size are specified. In this case though cell size relates to the length of segments into which the network has to be cut in order to represent the output. Additionally, SANET allows you to control how you handle road intersections, either by using a continuous or discontinuous approach to the bifurcation, i arbitrarily chose the continuous approach, essentially meaning that the density estimation can turn corners. A straightforward representation can be made in 2D as below.
The interesting aspect to this image that is obscured in 2D smoothed representations is the relative usage of different streets, clearly visible are the residential streets as distinct from the more commercial area on Southwark’s Bankside, and along major roads, and the effect of open space and water features in reducing network density (i.e. if only one side of a road has residences on it). I’ve attempted to explore this further by using ArcScene’s 3D visualisation capabilities, but the complexity of the data make this an incredibly arduous process. The result i was able to obtain outside of ArcScene simply crashing are below.
In this example, Southwark is presented in a kind of 2.5D perspective in which the streets have been extruded so that their height represents the population density at that point. I’ve included some contextual elements, the Thames, and parks, wooded areas, and other water features. Whether or not this image is in anyway an improvement over a simple 2D representation is open to debate, but the selections below do present an interesting cross section of the data.
