New Book Chapter: Agent-based modelling and geographical information systems
- Visualization and exploratory spatial data analysis
- Space time modelling
- Spatial algorithms
- Spatial regression and statistics
- Enabling interactions through the use of neogeography ”
Representing the world as a series of layers of fixed and non-fixed objects (adapted from Benenson and Torrens, 2004). |
The chapter therefore introduces agent-based models to those interested in geocomputational methods, argues why such models should be used to study geographical problems before discussing how one can use GIS to create geographical explicit agent-based models. Through a series of examples we demonstrate how raster or vector spatial data can be used to model various aspects of our daily lives from that of the micro movement of pedestrians over seconds and minutes, to that of the macro patterns of urban growth over years and decades. By integrating spatial data and agent-based models at different spatial and temporal scales, such a modeling approach provides the flexibility to aid social scientists to explore the complex world that we inhabit.
A sample of application domains for spatial agent-based models discussed in the chapter. |
Reference Cited:
Benenson, I. and Torrens, P.M. (2004), Geosimulation: Automata-Based Modelling of Urban Phenomena, John Wiley & Sons, London, UK.
Full Reference to Chapter:
Crooks, A.T. (2015), Agent-based Models and Geographical Information Systems, in Brunsdon, C. and Singleton, A. (eds.), Geocomputation: A Practical Primer, Sage, London, UK, pp. 63-77. (pdf)