Spatializing the Social – Computational Strategies for Intervention in Informal Settlements

AUTHORS: Lila PanahiKazemi, Andrea Rossi

Published in the 39th IAHS World Congress – Changing Needs, Adaptive Buildings, Smart Cities



Traditional design and planning tools seem everyday less adequate to deal with the complexity of contemporary cities. Istanbul is a striking example of these contradictions [1]: indeed, the recent urban developments are eroding the informal settlements, commonly called Gecekondu, that during the last century shaped large part of the city. The development of neoliberal policies is threatening the future of these lively communities, while at the same time encouraging an increase in phenomena of social segregation and urban fragmentation [2]. This paper wants to propose an alternative method for the intervention in these areas, based on the application of computational techniques to understand, foresee and drive the growth of more sustainable and integrated settlements. The method is articulated in four phases: analysis, model creation, scenario planning and implementation. The analytical phase allows both for the understanding of the relational rules of the urban form of these areas and of the social and economical mechanisms that led to this kind of urban structure. This will inform the creation of a model, allowing in this way to create the background and keep the study linked to the current area, while at the same time allowing for a generalization of the assumptions [3]. The set of rules extracted in this way can be encoded successively in a complex computational model, where a set of generic algorithms of urban development [4] is coupled with the structural relationship of the neighbourhood analysed. The model is developed by interlinking different rules of urban development with social and economical simulation processes, allowing for the simulation of complex dynamics of change. The model built allows then for the creation of different scenarios of development, based on a combination of bottom-up processed driven by citizens decisions and top-down policies implemented by the municipalities. The scenarios can be tested and evaluated, allowing for the definition of alternative policies of intervention. The implementation phase can then be carried out in different ways, but, by maintaining a continuous process of feedback with the computational model and the reality of change, maintain a degree of control without imposing a rigid development.


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