Metabopolis: Biomorphic Transportation Framework for Cities of the Future

Abstract

Rapid increased in economic growth and employment opportunities in Bangkok have led to an influx of labour immigration resulting in a surge of sub-urbanization around the metropolitan. The expansion of the city resulted in the elimination of existing vital agricultural land, forest and water basins. (Tonmanee & Kuneepong, 2004) The lack of planning for city growth, have led to an ecological imbalance causing many problems such as the dissolution of agricultural settlements from urban sprawl, congestion in the core of the city, irrational and ever growing commuting distances. (Doxiadis, 2005b)

This thesis proposes a study that combines computational growth models and architecture, derived from two city growth theories, Ekistics and Metabolism, to help understand the dynamic urban sprawl of cities. Through code based design, we can attempt to control the direction of growth through physical infrastructural arrangements, topology and geometry of street and rail systems (Batty, 2008).

Computational application of biomorphic growth simulations with the Processing language will be explored in order find an alternative design methodology towards

The site, located in southern Lopburi of Thailand, was chosen based on the continual growth of Bangkok and the decrease of surrounding agricultural land (Tonmanee & Kuneepong, 2004). The government’s proposal of a high speed rail have brought an increase in demand to transform existing agricultural settlements towards an unbalance urbanization.

The integration of biomorphic growth studies with transportation infrastructure design allow for new possibilities to improve the urban design of expanding cities.

In response to the research question, the overall thesis displays the ability to enhance the design process by integrating computational application throughout the design methodology and development. Computational application demonstrated the ability to expand and provide inspiration beyond the capability of traditional methods.