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Model
Generative

Typology
Urban tissue (block & network)

Size
4km x 4km

Fitness criteria
Density, connectivity, open space

 
 
 
Most studies take the reductions approach of focusing on block morphologies or network structures with no regard to how the two influence, interact or co-evolve over time.
 
 
 
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Co-Evolution

The concept of co-evolution and co-development is not exclusive to living organisms and can be found in the development and evolution of systems of different kinds. Cities, as a collection of differentiated systems that co-develop and co-evolve over time, exhibit similar properties. In modelling interactions between systems of different kinds, the relation between systems, their association and interactions with one another becomes central to the notion of development and evolution of cities over time. The systemic modelling of blocks and networks can be categorised under 3 different scenarios:

  • Block dominated

  • Network dominated

  • Co-evolved

Co-evolved morphologies are more evident in historical patterns of cities as opposed to planned settlements. It is hard to identify a particular pattern type or hierarchy in the development of such tissues, as the evolution of the tissue generally occurs due to many factors during development and at both local and global scales. Unlike the first two scenarios, co-evolved morphologies are not top-down. Hierarchy does not reside within systems (in that a system dominates another, as was the case in the previous two scenarios), but emerges through interactions at the local scale as the model develops.

 

Computational Modelling of Urban Tissues

 
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Low-density tissue

Gene Count: 14      
Network Types: Secondary & tertiary      
Network Length: 786      
Number of Buildings: 1,681      
Solution Time: 36.3 seconds      
Area: 2km x 2km    

 
 
 
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Low-density morphology

The experiment focused on a low-density tissue with a similar morphology to neighbourhoods outside of urban cores. The relational model focused on buildings of small footprints with long-segmented networks. In addition, the building depth is relatively shallow to allow for courtyards. The black and white image has been split in half. On the right is the aerial photograph of west London and on the left is a computationally generated urban tissue embodying the same qualities.

 
 
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Medium-density tissue

 

Gene Count: 14      
Network Types: Secondary & tertiary      
Network Length: 1,804      
Number of Buildings: 4,888      
Solution Time: 42.3 seconds      
Area: 2km x 2km    

 
 

Medium-density morphology

The medium-density tissue follows a similar morphology as urban residential neighbourhoods of high-density evolved cities such as Tokyo or Istanbul. The building footprints are deeper and the heights taller than the low-density examples looked at. The computational model focused on buildings of medium sized footprints that were density packed coupled short-segmented networks.

 
 
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Generation: 20      
Population Size: 15      
Number of Blocks: 690      
Number of Buildings: 13,888      
Number of Genes: 69,440      
Solution Time: 29.4 seconds     

 
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High-density tissue

Gene Count: 14      
Network Types: Secondary & tertiary      
Network Length: 3,166      
Number of Buildings: 9,012      
Solution Time: 49.8 seconds      
Area: 4km x 4km   

 
 

Hyper-density morphology

The hyper-density tissue focused on the generation of multiple network and block types. Density measures vary across the tissue as do the morphologies including street and building types.

 
 
 
 
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