We present a statistical characterization of the morphological features emerging from the complex processes governing the growth of the road network, particularly in a mostly self-organized urban setting. Apart from the usual fractal analysis, the roads are quantified by their lengths and straightnesses, while the segmented blocks are characterized by their areas, perimeters and circularities. When applied to the Metro Manila conurbation, one of the megacities in Asia with the fastest growing populations, we observe dense space-filling and nontrivial statistical distributions of roads and blocks that can be attributed to the geographical constraints of the metropolis. The emergence of the scale-free regimes is explained using a simple rule-based model patterned after the assumed dynamical interplay between the local and global factors involved in individual street formation. By viewing road network growth from a quantitative complex systems perspective, we can gain insights into the underlying rules operating at the local scales that give rise to the global spatial patterns.
Road networks are some of the oldest and most permanent man-made structures in space, serving as valuable records of the conditions of the society through long periods of time. Quantitatively analyzing these networks will therefore reveal rich insights into the socio-political conditions of the society through history, and can provide awareness for effectively managing the growth and evolution in the future. Here, we extracted the state of the road network of Manila, Philippines at various points in history through georeferencing and digitization of hand-drawn historical maps. Visual and metrical analyses revealed key well-planned periods punctuating the otherwise self-organized growth, particularly the more recent densification at reclamation areas coincident with the rapid economic growth. The road network of Manila shows statistical regularities that are also observed for other global road network data sets, although the recent reclamation significantly increase the statistics of the very short and peripheral nodes. Finally, the clusters of nodes with the highest closeness centralities mimic the historical shape of the network, allowing for an automatic identification of the core historical sections of the city. Studies such as this one extract useful information from these permanent spatial records, which may then be useful for developing sound policy measures for handling further urbanization.
We compare the statistical distributions of the geometrical properties of road networks for two representative datasets under different levels of planning: the cities comprising Metropolitan Manila show the conditions under bottom-up self-organized growth, while Brasilia and the Australian Capital Territory centered at Canberra represent the case of strict top-down planning. The distribution of segmented areas of the cities shows a dual power-law behavior, with the larger areas following the ∼1.9 scaling exponent observed in other cities, while the smaller areas show a lower exponent of ∼0.5, believed to be due to practical considerations. While all cities are found to favor the formation of straight road segments, the planned city roads have a preponderance of sinuous roads, with sinuosities approaching π. A simple model based on a nearest-neighbor directed branching coupled with sectional grid formations is proposed to capture the nontrivial statistical features observed.
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