As many urban areas undergo increasing densification, there is a growing need for spatial analysis methods that can operate in 3D to analyze the urban environment and aid in decision-making processes. Weighted linear combination (WLC) multicriteria evaluation (MCE) is frequently implemented in geographic information systems (GIS) to aid in spatial decision-making analysis. However, its decision logic limits the number of criteria that can be handled and aspects of human reasoning that can be represented. Logic Scoring of Preference (LSP) is an advanced MCE method that better models human reasoning through flexible soft computing decision logic operators and can support large numbers of criteria inherent to decision-making. This research (1) develops and implements the 3D LSP-MCE method to examine the suitability of high-rise residential units, and (2) demonstrates the robustness of results through sensitivity and cost-suitability analyses. The 3D suitability analysis was performed with datasets for the City of Vancouver, Canada using LSP aggregation structures that reflect the unique requirements and preferences of three demographic profiles (young families, working professionals, active seniors). The results vary considerably between preference scenarios, demonstrating the method's flexibility in representing the unique priorities and requirements of different demographics. Cost-suitability analysis indicated that cost has a significant effect on the overall value of residential units. The proposed 3D LSP-MCE method could be adapted to benefit other user groups such as tax assessors, urban planners and developers to assess and select from various urban densification development scenarios.
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Thesis advisor: Dragicevic, Suzana
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