A hybrid (semi) automatic calibration method for Cellular Automata land-use models: Combining evolutionary algorithms with process understanding. (December 2020) - Newland, Charles P.; van Delden, Hedwig; Zecchin, Aaron C.; Newman, Jeffrey P.; Maier, Holger R.
Abstract: This paper presents a hybrid automatic calibration method for transition potential based Cellular Automata land-use models by integrating two calibration methods, process-specific and optimisation-based, into a single hybrid approach, combining the advantages of these two methods. The hybrid approach features the detailed exploration of a large population of possible model parameterisations achieved using optimisation with valuable understanding of land-use systems and their dynamics commonly utilised in process-specific methods to better enhance the plausibility of the results obtained. The utility of the proposed hybrid approach is tested through an application to Madrid, Spain, and outperforms the two other methods (conventional multi-objective optimisation and process-specific) in terms of objective performance, quality of simulated output maps based on visual assessment, and parameter estimates that are more consistent with process understanding. Highlights: New method for automatic calibration of Cellular Automata land use models. Software developed to enable proposed method to be implemented easily. Method and software tested on case study of Madrid, Spain. Method outperforms alternative approaches; and. Method generates plausible simulated output and parameter values without over-calibration.