By Alan Wilson
A ‘science of towns and areas’ is necessary for assembly destiny demanding situations. the realm is urbanising: large towns are being created and are carrying on with to develop swiftly. there are various making plans and improvement concerns bobbing up in several manifestations in nations around the globe. those advancements can, in precept, be simulated via mathematical computing device types which supply instruments for forecasting and trying out destiny situations and plans. those versions can symbolize the functioning of towns and areas, predicting the spatial demography and the financial system, the most flows equivalent to trip to paintings or to providers, and the mechanisms of destiny evolution. during this booklet, the most ideas interested by the layout of this variety of versions are articulated, offering an account of the present cutting-edge in addition to destiny study challenges.
Alan Wilson has over 40 years operating with city and neighborhood types and has contributed vital discoveries. He has distilled this adventure into what serves as either an advent and a evaluate of the examine frontier. subject matters coated comprise the Lowry version, the retail version, ideas of account-based versions and the tools rooted in Boltzmann-style statistical modelling and the Lotka-Volterra method of process evolution. functions variety from city and neighborhood making plans to wars and epidemics.
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Extra resources for The Science of Cities and Regions: Lectures on Mathematical Model Design
Example text
They are concerned with individual behaviour within social, cultural and political environments and the study of these environments through such concepts as ‘social movements’. If individuals are thought of as ‘agents’, then at a micro scale, they function within (exogenously) given structures. This leads to the idea of the ‘agency-structure’ problem: how structures are created by, or at least influenced by, individual behaviour. This is the sociological analogue of the aggregation problem in economics.
We can then choose, in different circumstances, whether to locate micro units in these arrangements or macro sectors. We have presented this as a model design issue earlier: choosing an appropriate level of disaggregation. The ‘aggregation problem’ remains with us! Economists have been less effective at this scale. It can be argued that this has arisen from poor choice of spatial system—a tendency to use continuous rather than discrete spatial representations—and also rather artificial representations of systems—too many people for example assumed to be behaving in some ‘economic rational’ way when clearly they don’t.
It is also the case, of course, that the good historian will offer hypotheses to explain this evolution and this should provide further insights for the modeller. An excellent example on both counts is provided by Cronon’s (1992) book Nature’s metropolis. This was the basis of the model example offered at the end of Chap. 2 on the evolution of the North American urban system. 6 The Physical Environment Physical environments have not played much role hitherto in the urban and regional modelling world beyond building in topography to network representation.