Indicators for self-organization potential in urban context

Abstract

Self-organization is a basic mechanism by which complex urban systems organize themselves. This mechanism emerges from individual agents’ local interactions, often with unpredictable consequences at the regional level. These emergent patterns cannot be controlled by traditional hierarchical methods, but they can be steered and encouraged towards desirable goals. Self-organization is often used as an allegory for all ‘unplanned’ activity in cities. It is important to study the actual mechanisms of self-organization in cities to link the theory of self-organization to planning praxis. This work builds on ongoing work exploring novel complex planning tools and methods. Here I explore the key features of open dynamic systems identified in the literature as indicators of self-organizing capacity. I study their applicability in urban spatial planning, and propose three measurable characteristics for estimating the self-organization potential of urban activities. Flow reflects generic accessibility, and is measured using space syntax. Internal order refers to autonomously organizing entities, in this case the clustering tendencies of activities. Enriching rests upon increasing complexity and is measured as changes in degrees of entropy over time. The results indicate that (1) the study area meets the criteria for self-organization, and (2) these characteristics can be applied to discover nodes of higher potential for self-organization in a city.

An Urban Cellular Automata Model for Simulating Dynamic States on a Local Scale

“…In such an environment, more flexible planning could provide a frame for urban processes, but the potential impact of the frame must be scrutinized-in this endeavor micro simulations are useful, along with other "complexity planning tools" such as measurement based on fractality, scaling or computation [32,55,56]. In practice, with micro simulation models it is possible to model the environmental factors affecting actors, and then by altering the virtual "planning rules", for example permitted proximities or other factors, to learn how the guidelines affect the dynamics.…”

“…In Nekala, several indicators for self-organization potential were discovered in addition to the enclave form: high accessibility, increasing diversity and self-organization of certain actors [32]. In Vaasa, characteristics indicating similar behavior were perceived, but these were less marked than in the more mature Nekala.…”

“…A documented simultaneous agglomeration tendency of several activities revealed less than four percent of activities outside the clusters in all the time series for 1971, 1986 and 2007, while large concentrations of activities were also rare [32]. This study was carried out in Nekala old industrial area in Tampere, Finland.…”

“…The research on clustering of several coexisting industries in a single area is limited. Such approaches, however, are necessary given that according to many studies certain special local scale demarcated and self-organizing areas constantly emerge in the city, impacting on urban dynamics on a regional level and with great potential for cultural and economic life in the city [5,[29][30][31][32]. On complex, resilient trajectory, these areas support the cultural and economic viability of the whole city, hence making it important to explore means of supporting their self-organization.…”

Self‐Organization and Urban Development: Disaggregating the City‐Region, Deconstructing Urbanity in Amsterdam

“…Since the 1960s, self‐organization has been understood as the mechanism of internal change within complex urban systems and widely used to build models of city evolution (Allen and Sanglier, ; Allen, ; Thrift, ). Since then, definitions of this concept have proliferated in different fields, from biology to information sciences, natural sciences and sociology (for a historical view see Partanen, and Batty, ). These definitions build upon the assumption that self‐organizing systems show the ‘emergence of order on the global level (of a system) from the individual dynamics of its components without any central coordination and without specific action from outside' (Ismael, : 333; Haken, ).…”