Name
Abstract | ||
|---|---|---|
Understanding of urban growth process is highly crucial in making development plan and sustainable growth management policy. As the process involves multi-actors, multi-behavior and various policies, it is endowed with unpredictable spatial and temporal complexities, it requires the occurrence of new simulation approach, which is process-oriented and has stronger capacities of interpretation. In this paper, A cellular automata-based model is designed for understanding the temporal process of urban growth by incorporating dynamic weighting concept and project-based approach. We argue that this methodology is able to interpret and visualize the dynamic process more temporally and transparently. |
Year | DOI | Venue |
|---|---|---|
2002 | 10.1007/3-540-45830-1_31 | ACRI |
Keywords | Field | DocType |
cellular automata-based model,project-based approach,urban growth,sustainable growth management policy,dynamic weighting concept,urban growth process,temporal process,dynamic process,temporal complexity,cellular automata,new simulation approach | Data science,Cellular automaton,Weighting,Development plan,Computer science,Operations research,Process dynamics,Sustainable growth rate,Design process,Sustainable development,Distributed computing | Conference |
Volume | ISSN | ISBN |
2493 | 0302-9743 | 3-540-44304-5 |
Citations | PageRank | References |
6 | 0.92 | 1 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jianquan Cheng | 1 | 6 | 0.92 |
| Ian Masser | 2 | 157 | 33.90 |