Grant: Discovery Grants Program - Individual

GIS-based multi-criteria decision analysis (MCDA) is used for decision-making in fields such as environmental, transportation, and landuse planning, waste management, hydrology, agriculture, and forestry. Yet important conceptual questions regarding the spatial, temporal, and scale components of GIS-MCDA remain largely unanswered. The proposed research program aims to expand my current NSERC-funded research in this field. The location component of input data in GIS-MCDA is often under-used. In recent work, some researchers have experimented with spatially explicit MCDA techniques such as the locally weighted linear combination (LWLC). The LWLC technique represents local variations in criterion outcomes through local weights. As a result, LWLC creates a more dispersed pattern of MCDA scores, which highlights local differences rather than general spatial pattern. The usefulness of this approach remains to be demonstrated in practical applications, which is one objective of this proposal. The time component in GIS-MCDA refers to repeated evaluations over time. Since MCDA scores are unitless and not directly comparable, issues arise when composite indices are used for tracking socio-economic or environmental system performance over time. In recent NSERC-funded work, I proposed "joint standardization" to make scores comparable when they are calculated for different points in time. Similar to global vs. local weighting, joint standardization can be associated with a global (in time) approach, while individual (time-specific) standardization represents a local approach. Consequently, individual standardization yields greater variation in results while joint standardization yields information about general temporal pattern. These two approaches will be further examined in this research, and their usefulness explored in practical applications. Finally, the scale component in GIS-MCDA involves both spatial and temporal elements, although the focus of this research will be on spatial scales. Scale is connected to the well-known Modifiable Areal Unit Problem (MAUP) in geospatial analysis. Both the scale and zoning effects of the MAUP influence the results of GIS-MCDA. Conducting GIS-MCDA case studies at different scales of analysis and using different zoning configurations will contribute to a better understanding of these effects. The proposed research aims to give decision-makers stringent guidelines for aligning the scale of analysis with the scale of action. Overall, the proposed research serves to explore fundamental questions that impact the validity of GIS-MCDA results. The scope of these effects will be explored and best-practice for handling the location, time, and scale components of GIS-MCDA developed. Ultimately, this research program aims to develop a conceptual framework for spatially and temporally explicit, and scale-specific, decision support.