VECTOR CELLULAR AUTOMATA BASED GEOGRAPHICAL ENTITY

by : 1 Hu Shiyuan and 2. Li Deren
1. School of Resource and Environmental Science , Wuhan University, 129 Luoyu Road, Wuhan, China, 430079
2. School of Remote Sensing Information Engineering, Wuhan University, 129 Luoyu Road, Wuhan, China, 430079

Cellular automata (CA) are mathematical models for systems in which many simple
components act together to produce complicated patterns of behavior (Wolfram, 1985).CA have close associations with complexity theory and have been employed in the exploration of a diverse range of urban phenomena. Urban applications of CA range from traffic simulation and regional-scale urbanization to land-use dynamics, historical urbanization, and urban development. The integration of GIS and CA will accelerate GIS’s ability of simulating geographical process greatly especially (Zhou et al., 2001).

CA models are usually based on fine regular tessellations such as a grid, in which every cell is identical, has identical relations with each of its neighbors, and has a standard neighborhood of cells in which these relations operate. These neighborhoods are strictly local in that they are based on physically adjacent cells. In geographic and urban models, this may be over-simplistic (O'Sullivan, 2000), and it has some restrictions in cellular shape, neighborhood and neighbor rules,which restrict the CA’s ability to simulate real world.The standard CA exists some problems mainly as follows: (1) Space partition, namely determination of space pixel. Each kind of graphical object has itself space scale in the system which plenty of graphical entities exist together. In addition, graphical entity
represents different behavior in different space scale. It is a problem how to determinate a uniform spatial resolution. (2) Precision & Quantity. CA models are usually based on fine regular tessellations, cell is similar to the grid of grid data in GIS, it exists some problems such as imprecise locating and tremendous quantity. (3) Cell space is divided into regular tessellations on abstract space in standard CA. Every cell is identical, has identical relations with each of its neighbors. This kind of CA can expose local reciprocity among cells. But geographical system is a typical complex system, which is a compound system consisted of physical, social and economic subsystems. The complexity is an essential characteristic of Geo-Spatial System for its complexity properties such as non-equilibrium, multi-scale, indeterminacy, hierarchy, self-organizing, self-similarity, randomicity, iterativeness, and so
forth. So regular space system exists hardly in real world.
This paper will explore the relation between geographical space and cellular automata,and
build a extended CA model based on geographical entity in irregular geographical spaces.
In addition, this paper will explore the integrated pattern of GIS and CA.