An Interactive Method to Dynamically Create Transition Rules in a Land-use Cellular Automata Model
Year: 2011
Type: book-chapter
Abstract: Cellular Automata -Simplicity Behind Complexity 4 analysis of variance (Lau and Kam, 2005) have been proposed for CA calibration.Computational intelligence techniques have also been tested, including artificial neural network (Li and Yeh, 2002b;Pijanowski et al., 2002), genetic algorithm (Shan et al., 2008), and data mining (Wang et al., 2010).Other methods involve the systematic testing of parameters (Jantz and Goetz, 2005;Jantz et al., 2003) and iterative calibration to achieve reasonable goodness-of-fit (Straatman et al., 2004).While these approaches might provide satisfactory simulation results, they often leave the modeler with little control on the mathematical equations used to determine the transition rules and the difficulty of understanding the geographical meaning of these rules (Verburg et al., 2004).This paper describes a semi-automated, interactive method that was designed and implemented to dynamically create transition rules and calibrate a land-use CA model.The proposed method combines the benefits of conditional and mathematical rules and is adaptable in terms of number of land-use classes, and spatial and temporal scale of the input data.It allows the modeler to acquire information about the importance of the factors associated to historical land-use changes within the study area and to interactively select the parameter values required for the model calibration.A detailed description of the steps involved in the CA calibration is provided.The CA model is then used to answer the following questions: a) how sensitive is the model to the conditions involved in the calibration, including the cell size, neighborhood configuration, parameter values and external driving factors?b) what is the performance of the model, in terms of presence and location, in simulating land-use changes using the transition rules identified by the proposed calibration method? How to referenceIn order to correctly reference this scholarly work, feel free to copy and paste the following:
Source: InTech eBooks
Parent work: Cellular Automata - Simplicity Behind Complexity
DOI: 10.5772/16073
Authors: Hasbani, J. G., N. Wijesekara, D.J. Marceau
Institution: University of Calgary
Language: English
Subfield: Global and Planetary Change
Field: Environmental Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W1515290276