When comparing an urban system to an elasto-plastic lattice, an analogy to the solid state of matter can be exploited using the concepts of the band theory similarly. Thereafter, the population dynamics – in a region of certain stability in the state space and within appropriate energy bands – can be described in terms of Cellular Automata, with two mobile agents or pseudo particles: the inhabitant (representative of an average individual) and the recurson (representative of its multidimensional resources). As in the solid state, transition rules take the form of two coupled transport equations, comprising the terms equivalent to the generation-recombination and circulation processes. The first process can be compared to a predator–prey growth model, typical of Ecology; whereas the circulation process – composed of a drift component and a diffusion component – should be compared to the concentration-sprawl demographic balance seen in urban occupation and dynamics. Thus, it needs to be defined and determined an urban potential function, an equivalent population charge, mobility and diffusion parameters, as well as net growth factors. This analogy, discussed within the context of a case study for Great Mendoza, plausibly explains the varied growth rates of the political departments, as well as the principal urban trends for spatial occupation.
[1]
Soohong Park,et al.
Incorporating Cellular Automata simulators as analytical engines in GIS
,
1997,
Trans. GIS.
[2]
M. Batty,et al.
Spatial Analysis: Modelling in a GIS Environment
,
1998
.
[3]
Peter Kareiva,et al.
Spatial ecology : the role of space in population dynamics and interspecific interactions
,
1998
.
[4]
Valentin L. Popov,et al.
Theoretical principles of modeling elastoplastic media by movable cellular automata method. I. Homogeneous media
,
2001
.
[5]
Lubos Mitas,et al.
Role of dynamic cartography in simulations of landscape processes based on multivariate fields
,
1997
.
[6]
Simon A. Levin,et al.
Biologically generated spatial pattern and the coexistence of competing species
,
1997
.
[7]
Michael Batty,et al.
Modeling Complexity : The Limits to Prediction
,
2001
.
[8]
Michael Batty,et al.
Visualizing Urban Dynamics
,
1996
.