Modeling Land Use Change With Logic Scoring Of Preference Method Gis And Cellular Automata

Multicriteria Evaluation (MCE) has been used as a land suitability method and is often coupled with Cellular Automata (CA) for land-use and urban growth modeling. MCE, however, exhibits limitations including data loss and insufficient logical requirements. The Logic Scoring of Preference (LSP) is an alternative approach that can overcome these issues. LSP is a soft computing system evaluation method efficient in nonlinear aggregation with flexible logic requirements. The main objective of this research study was to develop an integrated LSP and geographic information system (GIS) methodology for modeling land-use change. Moreover, the LSP method was further integrated into a CA to model urban growth. The LSP methodology was tested with geospatial datasets of coastal BC, Canada and several scenarios of future land-use change were generated. This research contributes to the field of spatio-temporal modeling with a novel integration of LSP, GIS, and CA for land-use suitability analysis and modeling.