Local Ideal Point Method for GIS-based Multicriteria Analysis: A Case Study in London, Ontario

GIS-based multicriteria analysis (GIS-MCA) is a procedure for transforming and combining geographic data and value judgments (preferences) to evaluate a set of alternatives with respect to relevant criteria. Ideal Point Method (IPM) is one of the most often used GIS-MCA techniques. It has been applied in many research/planning areas including environmental planning, urban/regional planning, waste management, water resource management and agriculture. One of the limitations of IPM is that it has conventionally been used as a global approach based on the implicit assumption that its parameters do not vary as a function of geographic space. The conventional IPM assumes a spatial homogeneity of its parameters within the whole study area. This thesis proposes a new IPM called local IPM. The local version of IPM is developed by localizing two parameters (criterion weights and ideal/nadir points) based on the range-sensitivity principle. The IPM methods are used to evaluate and analyse the spatial patterns of the quality of employment in London, Ontario. The case study shows that there are significant differences between the spatial patterns generated by the local and conventional IPM. The local IPM not only can display the general ‘spatial trend’ of the quality of employment in London, but also is able to highlight the areas with relatively high quality of employment in different neighborhoods. Furthermore, the local IPM provides a tool for visualizing and exploring spatial patterns. The parameters influencing the local IPM results can be mapped and further examined with GIS.