Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6962250 | Environmental Modelling & Software | 2018 | 26 Pages |
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.
Related Topics
Physical Sciences and Engineering
Computer Science
Software
Authors
Charles P. Newland, Holger R. Maier, Aaron C. Zecchin, Jeffrey P. Newman, Hedwig van Delden,