The Logic Scoring of Preference (LSP) method is a part of general multicriteria decision making approach that has origins in the soft computing. The method can model simultaneity, replaceability, and a wide range of other aggregators to suit various evaluation objectives. As soft computing method, LSP is based on fuzzy reasoning and can aggregate an unlimited amount of inputs without loss of significance. The main objective of this research is to develop and test integrated methods that use LSP, complex systems theory and geographic information systems (GIS) to model urban land-use change. In this research study LSP is integrated into a GIS to determine land-use suitability and is integrated into both cellular automata (CA) and agent-based models (ABMs) to simulate urban growth at both regional and local spatial scales. LSP approaches were implemented with geospatial datasets for Metro Vancouver, Canada and several scenarios of land-use change have been created
