STUDY OF CELLULAR AUTOMATA MODELS FOR URBAN GROWTH

by: Nagaratna P Hegde, *Dr I V MuraliKrishna, **Dr K V ChalapatiRao

Abstract :
Differential equations, partial differential equations and in some instances,
empirical equations have been the underlying mathematical tools behind spatial
simulation models. Approaches based on cellular automata models are proposed
herein to replace the conventional tools. Issues such as the definition of transition rules, computer implementation with raster geographical information systems and model verification are discussed.

Cellular automata (CA) models consist of a simulation environment represented
by a grid of space (raster), in which a set of transition rules determine the
attribute of each given cell taking into account the attributes of cells in its
vicinities. These models have been very successful in view of their operationality,
simplicity and ability to embody both logics- and mathematics-based transition
rules. It is thus evident that even in the simplest CA, complex global patterns can
emerge directly from the application of local rules, and it is precisely this property
of emergent complexity that makes CA so fascinating and their usage so
appealing.

Keywords Geographic Information Systems; Simulation ,CellularAutomata

INTRODUCTION
Cellular Automata (CA) models were originally conceived by Ulam and Von
Neumann in the 1940s to provide a formal framework for investigating the
behavior of complex, extended systems. CA are dynamic, discrete space and
time systems. A cellular automaton system consists of a regular grid of cells,
each of which can be in one of a finite number of k possible states, updated
synchronously in discrete time steps according to a local, identical interaction