URBAN GROWTH NETWORKS

We have seen that cities can be regarded as a singular organism, growing and evolving in the same ways in every part of the world despite the seemingly differing contexts they are set. This again is due to the logic’s of the social and cultural networks that are created among its inhabitants, the flows of information through the city defining its form.

The following analysis of an urban construct seeks to distinguish a relationship between defining connectivity and population in relation to biological scaling patterns discussed here. The tragically beautiful urban example I have chosen was created in a remarkably short time period; the 11 day period following the 2010 Haiti earthquake, in a field south east of the city centre. (Via New York Times )

The speed at which the refugee city was created highlights not only the tragedy of the events and the inhabitants need for basic shelter, but also the pure emergent forces defining its form. With architect, designer, city planner in sight the settlement evolved an efficient network of pathways and connections that effectively distributed much needed materials to the refugees. The fractal nature of this intricate path network can been seen evolving in complexity over the 11 day period.

The overall form of the emergent settlement is heavily defined by the physical nature of the land and its topology. This is due to the main connecting pathways that initially connect the whole site together following the contours and the shallowest gradients of the land; a process mimics the patterns that can be seen in the formation of geological configurations such as river networks and glacial movements. These formations arise out of the need for any energetic system to attain an equilibrium within their surroundings.

These maps chart the increasing connectivity of the camp over the course of its emergence. Tight pockets and clusters of habitation begin to emerge almost randomly over the site but by charting the average connectivity of the habitat and also its density we will start to see its patterns of growth and the evolution of its interconnected network.

Mapped here is all the collected data regarding occupied area, overall path network length, estimated population, density and connectivity. The most clear scaling correlations can be seen in the overall path length; as the population of the camp increases, less infrastructure is needed to serve the entire population. That is to say, the larger the camp, the more efficient and interconnected it becomes. Less obvious is the relationship between the population density and connectivity of the camp. As the initial population increases and spreads over the sit, its connectivity scales in a linear path. However as the density of the camp increases, its connectivity scales with a positive exponent, that is to say, as density increases, connectivity exponentially increases.

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