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Cellular Automata

It is a simulation model applied in geospatial analysis which may be characterized by its key attributes like State variable, Spatial framework, Neighborhood structure, Transition rules and Time.

Introduction

Cellular automata (CA) has the following key attributes:

  • State variables are a set of attributes that describe the automaton at a particular point in time
  • Spatial framework: lattice of cells (patches)
  • Neighborhood structure: ‘Moore’ (cell plus 8 surrounding cells) or ‘Von Neumann’ (cell and four cardinal neighbors). It is comparable to the neighborhoods used in neighborhood analysis.
  • Transition rules: rules that determine the state change
  • Time: discrete steps, i.e., simulation (moves over time)

Definition

The simulation runs in an environment consisting of cells in which a range of phenonmenon can be simulated using predefined functions on the cell over time.The neighbourhood structure can be a 'Moore' neighborhood with 8 surrounding cells or a 'Von Neumann' neighborhood with one cell and four cardinal neighbours. Dynamic environments can be better simulated through Cellular automata.

Limitations:

1. The cells cannot be moved

2.Not all phenomena are best represented in a cellular environment.

3.The fact that each cell is an autonomous element, they are not naturally grouped (to a house or a parcel or a road)

Outgoing relations