2026-07-23T01:18:41Z https://drops.dagstuhl.de/oai

oai:drops-oai.dagstuhl.de:9370 2024-03-06T10:44:09Z ddc:004 open_access

The Use of Particle Swarm Optimization for a Vector Cellular Automata Model of Land Use Change (Short Paper) Lu, Yi Laffan, Shawn Vector cellular automata (CA) Particle swarm optimization (PSO) Land use simulation Ipswich Cellular automata (CA) is an important area of research in GIScience, with recent research developing vector-based models in addition to the traditional raster data formats. One active area of research is the calibration of transition rules, particularly when applied to vector CA. Here we evaluate a particle swarm optimization (PSO) process to calibrate a vector CA model of land use change for a sub-region of Ipswich in Queensland, Australia, for the period 1999-2016. We compare the results with those for a raster CA of the same dataset. The spatial indices of the vector PSO-CA model exceed that of the raster model, with spatial accuracies being 82.45% and 76.47%, respectively. In addition, the vector PSO-CA model achieved a higher kappa coefficient. Vector-based PSO-CA model can be used for the exploration of urbanization process and provide a better understanding of land use change. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Yi Lu and Shawn Laffan 2018 Is Part Of LIPIcs, Volume 114, 10th International Conference on Geographic Information Science (GIScience 2018) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/LIPIcs.GISCIENCE.2018.42 urn:nbn:de:0030-drops-93702 https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.GISCIENCE.2018.42 eng https://creativecommons.org/licenses/by/3.0/legalcode