Retrospective GIS-Based Multi-Criteria Decision Analysis: A Case Study of California Waste Transfer Station Siting Decisions

Geographic information science (GIS) and multicriteria decision analysis (MCDA) disciplines combine to provide valuable insights which guide decision-makers evaluating complex spatial criteria and alternatives, especially when there are conflicting stakeholder values and objectives. Although GIS and MCDA methods have been integrated to support forward-looking decision analyses, there is also advantage to applying these methods retrospectively in order to decipher the factors that composed previous spatially-complex decisions. The objective of this study is to demonstrate a methodology which applies
“retrospective GIS-based MCDA” to characterize decision-maker value preferences in past siting decisions without a priori knowledge of the decision-making process. As a representative case study, retrospective GIS-based MCDA is performed on municipal solid waste transfer station site decisions in Los Angeles County, California.
Potential attribute data were identified and compiled into a geographic information system. The attributes of actual facility sites and their surrounding vicinities were established as the presence case for a positive decision. This decision problem was structured considering two MCDA decision model types – value function using weighted linear combination and reference point. The attributes of historical site selections were decomposed and compared to unselected sites to identify attribute patterns. The value function MCDA model was parameterized using logistic regression to establish relative attribute weights which were applied to create a probability spatial distribution profile. The reference point MCDA rule model was parameterized contrasting attribute relative frequency Pareto between transfer station and general locations to create a satisfaction spatial distribution profile. These resulting models provide both relative rank and objective level of attributes represented in previous waste transfer station location decisions. The methodology is applicable to evaluation of spatial decisions in other domains, and can be extended to consider other MCDA decision models.