Head/tail Breaks to Visualize the Well-connected Streets
Natural streets are road segments defined organically by good continuity instead of subjective decisions by government authorities. These streets in urban environments are not organized simply in linearity but in non-linearity of scaling hierarchy. For example, roads in Guangzhou include a variety of types, such as expressways, highways, pedestrian, etc. Certain key roads experience the heaviest traffic flow due to their extensive connections with numerous locations throughout the city. The scaling relationship behind the hierarchy of the traffic system is that there are far more less-connected roads than large ones, which is nonlinear and heavy-tailed in terms of its shape of distribution. The connectivity of natural streets can be quantified through topological analysis of space syntax. This scaling hierarchy of far more less-connected natural streets than large ones are able to be computed and visualized though head/tail breaks and power-law. In this report, we select Nasha district in Guangzhou, China as a case study for identifying natural streets and analyzing their scaling hierarchy behind (Figure 1). In total, there are 3,913 natural streets with 6 levels of hierarchy, and the distribution of connectivity-amount relationship can be well fit in power law. Through the case study, we can discover this quantitative analysis of scaling hierarchy has great potential for traffic management by finding out important roads for more effective decision making.
Figure 1: Illustration of natural street hierarchies in Nansha district and their statistics of power-law and head/tail breaks