Abstract:Christopher Alexander has presented key concepts, such as wholeness, centres, and harmony-seeking computations, related to the coherence reached by a system. Wholeness is the global structural character of a given configuration existing in space. According to Alexander, wholeness is measurable although we do not have a mathematical language to describe it yet. Some authors have proposed a network perspective to address this problem. However, it is still poorly developed. This paper discusses how to improve the network approach already suggested in the literature. The aim is contributing to the debate on how to operationalise Alexander's theories through a network perspective. We check out different descriptive systems and different centrality measures, which can be used to reveal the spatial relationship between urban entities and its hierarchy. The main conclusion is that centrality measures seem to offer an opportunity to get closer to Alexander's concepts. However, a key point to move forward is a deeper investigation on how to describe the urban elements, how to identify spatial differentiation, and how to visualize the results. The relevance of such kind of research is the possibility of using those insights as analytical methods for supporting urban design.
Morfologia Urbana é um campo altamente dependente de dados espaciais urbanos. Sua dificuldade de obtenção constituiu durante muito tempo obstáculo ao desenvolvimento de pesquisas na área, porém, mais recentemente, o aumento na disponibilidade de dados, a emergência do big data e o crescente desenvolvimento de ferramentas e tecnologias de informação, vem abrindo novas possibilidades para explorar digitalmente o território. Não se trata apenas de disponibilidade abundante de dados e softwares para manipulá-los, mas novas capacidades de integrá-los, o que encoraja a cruzar fronteiras disciplinares. O presente artigo tem como foco a relação entre o campo da morfologia urbana, caracterizado por contornos bem definidos em termos de quais dados são requeridos, e o que tem sido feito na dita fronteira do conhecimento, onde dados de diferentes tipos são combinados. Como contribuição este trabalho identifica perspectivas para futuras pesquisas, mostrando como a morfologia urbana pode se beneficiar dessa revolução dos dados, em especial utilizando-se de novos mecanismos descritivos e analíticos. Isso é evidenciado através da exploração de grafos temporais, hipergrafos e grafos multicamadas, ainda pouco empregada nos estudos urbanos, mas que demonstra potencial para: a) descrições multidimensionais da forma urbana; b) explorações de análises do espaço-tempo.
Harmony-seeking computations, as proposed by Christopher Alexander, offer a way to tackle complexity. Smart, free agents, facing uncertainty, look for order in a context powered by fifteen attractors, or patterns. Harmony-seeking would then be a relatively guided path across those idealized patterns, towards wholeness and beauty. However, individuals acting to change the city must combine circumstances imposed by external and inner urban forces with personal interpretations of one or more of those patterns that could change all the time. Moreover, each action is intertwined with others, in an unpredictable outcome. This article explores the possibility of bringing together urban inner and outer forces and ingenious individuals’ actions of city change by hypothesizing: (a) wholeness as a structural attribute defined as spatial centrality; (b) beauty as meaning attached to places, evolving either from historic accumulation or individual assignment; (c) order as every meaningful approximation between them; (d) a disaggregated description of the urban organism, based on multi-layered graphs, in which would be possible to record both morphological and territorial characteristics (form, transport, infrastructure) and semantic attributes (land uses, public image, remote associations, symbolic relationships); and (e) a set of spatial differentiation measures, mostly based on centrality, potentially able to depict wholeness (by measuring the effect of each component on all others) and beauty (by measuring urban robustness derived from any selected set of components). A multilayer graph-based approach to spatial differentiation algorithms provides a framework for the description, analysis, and performance evaluation of every component, as well as the whole system, both through quantitative and qualitative representation.
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