Integrating local multi-criteria evaluation with spatially explicit uncertainty-sensitivity analysis

Abstract

The conventional methods of Multi-Criteria Evaluation (MCE) fail to account for local variability in criteria values and criteria preferences, disregarding local influence in spatial decision making. Moreover, understanding the interaction between MCE model input and output has paramount importance in terms of the level of confidence in the model results and their subsequent use in decision making. This research contributes to spatial MCE methodology by articulating the presence of uncertainty included in criteria weights and extending a local MCE technique with a spatially explicit uncertainty and sensitivity analysis. The article presents a methodology for multi-criteria evaluation extended by an integrated uncertainty-sensitivity analysis and illustrates it on the example of a land prioritization model for conservation practices.

Keywords::

• GIS
• global sensitivity analysis
• local multi-criteria evaluation
• uncertainty analysis

Acknowledgments

Any opinion, findings, conclusions, and recommendations expressed in this material are those of the authors(s) and do not necessarily reflect the views of the National Science Foundation. We also appreciate the feedback provided by two anonymous reviewers on the previous version of this manuscript.

Additional information

Funding

Financial support for this work was provided by the National Science Foundation Geography and Spatial Sciences Program Grant No. BCS-1263071.