Multi-objective optimisation framework for calibration of Cellular Automata land-use models

• DOI: 10.1016/j.envsoft.2017.11.012
• Publication Date: 2017-11-24T08:15:17Z
• Authors: Charles P. Newland; Holger R. Maier; Aaron C. Zecchin; Jeffrey P. Newman; Hedwig van Delden
• Keywords: automatic parameter adjustment; automatic calibration; 0207 environmental engineering; multi-objective optimisation; land-use model; 006; Cellular Automata; 02 engineering and technology; 15. Life on land

Abstract Modelling of land-use change plays an important role in many areas of environmental planning. However, land-use change models remain challenging to calibrate, as they contain many sensitive parameters, making the calibration process time-consuming. We present a multi-objective optimisation framework for automatic calibration of Cellular Automata land-use models with multiple dynamic land-use classes. The framework considers objectives related to locational agreement and landscape pattern structure, as well as the inherent stochasticity of land-use models. The framework was tested on the Randstad region in the Netherlands, identifying 77 model parameter sets that generated a Pareto front of optimal trade-off solutions between the objectives. A selection of these parameter sets was assessed further based on heuristic knowledge, evaluating the simulated output maps and parameter values to determine a final calibrated model. This research demonstrates that heuristic knowledge complements the evaluation of land-use models calibrated using formal optimisation methods.