We propose that the emergent phenomenon know as ‘desakota’, the rapid urbanization of densely populated rural populations in the newly developed world, particularly China, can be simulated using agent-based models which combine both local and global features. We argue that deskota represents a surprising and unusual form of urbanization wellmatched to processes of land development that are driven from the bottom up but moderated by the higher-level macro economy.
We develop a simple logic which links local household reform to global urban reform, translating these ideas into a model structure which reflects these two scales. Our model first determines the rate of growth of different spatial aggregates using linear statistical analysis. It then allocates this growth to the local level using developer agents who determine the transformation or mutation of rural households to urban pursuits based on local land costs, accessibilities, and growth management practices. The model is applied to desakota development in the Suzhou region between 1990 and 2000. We show how the global rates of change predicted at the township level in the Wuxian City region surrounding Suzhou are tempered by local transformations of rural to urban land uses which we predict using cellular automata rules. The model, which is implemented in the RePast 3 software, is validated using a blend of data taken from remote sensing and government statistical sources. It represents an example of generative social science that fuses plausible behavior with formalized logics matched against empirical evidence, essential in showing how novel patterns of urbanization such as desakota emerge.
This working paper is available as a PDF. The file size is 653KB.
Authors: Michael Batty, Yichun Xie, Kang Zhao
Publication Date: 1/8/2005