โ Scribed by Yichun Xie; Daniel G. Brown
No coin nor oath required. For personal study only.
GeoComputation is an evolving research field with a primary focus on exploring new modeling paradigms and techniques derived from advances in computation for the goal of enriching geographic analysis of highly complex, and often non-deterministic problems . Agent-based models, cellular automata, fuzzy sets, genetic algorithms, and neural networks have attracted attention as useful research tools. In recent years, computational geometry, interactive exploratory data analysis and mining, numerical modeling, and many other research themes have been entering the scope of GeoComputation . Simulation in spatial analysis and modeling has been one of the key approaches of many researchers of GeoComputation. A dynamic geographic simulation represents the spatiotemporal dynamics of a physical system, a human system, or a coupled human-physical system that incorporates multiple stochastic and dynamic processes with the aim of solving or understanding problems or systems with multiple and often conflicting objectives . Solving these multi-objective problems presents a significant challenge and may have to rely on alternative evaluations of optimal solutions . As Page (2003) so cogently argues: ''. . . our models become better, more accurate, if they make assumptions that more closely match the behavior of real people . . .'' In addition to the model inputs, algorithms, assumptions, and outputs, the human dimension (modeler) is the most important fifth element to keep honesty toward the sensitivity test and to establish credibility in complex modeling and simulation . The diversifications and complexities embedded in geo-simulations become the main theme of this special issue.
๐ SIMILAR VOLUMES
Three approaches to modelling spatial data in which simulation plays a vital role are described and illustrated with examples. The ยฎrst approach uses ยฏexible regression models, such as generalized additive models, together with locational covariates to ยฎt a surface to spatial data. We show how the b
Urban sprawl is an essential environmental issue to be monitored and forecasted in order to think about alternatives that could lead to a more sustainable future development. Thus, the objective of the project presented here is to simulate the past and future transformation of suburban land use patt