On ordered weighted averaging aggregation operators in multicriteria decisionmaking
IEEE Transactions on Systems, Man and Cybernetics
An extension of the Analytical Hierarchy Process using OWA operators
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
Environmental Modelling & Software
Spatial sensitivity analysis of multi-criteria weights in GIS-based land suitability evaluation
Environmental Modelling & Software
Multi-criteria assessment for linking regional conservation planning and farm-scale actions
Environmental Modelling & Software
Uncertainty analysis in a GIS-based multi-criteria analysis tool for river catchment management
Environmental Modelling & Software
Cellular automata-based spatial multi-criteria land suitability simulation for irrigated agriculture
International Journal of Geographical Information Science
A self-adapting fuzzy inference system for the evaluation of agricultural land
Environmental Modelling & Software
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This paper presents a spatial framework which can be used to perform multi-criteria assessments for different purposes. We tested the framework on a case study of evaluating potential expansion for irrigated pasture in the Limestone Coast of South Australia. The core of the framework is the fuzzy linguistic ordered weighted averaging (FLOWA) model which integrates and implements fuzzy quantifiers, Ordered Weighted Averaging (OWA) and Analytical Hierarchy Process (AHP) in the ArcGIS environment. Fifteen criteria were chosen, including groundwater, topography, landscape and soil attributes which significantly affect irrigated landuse. Criterion weights were determined at both objective and attribute levels using the AHP, and several scenarios were derived using the OWA operator for selected values of fuzzy quantifiers. The resultant evaluation map from the weighted linear combination (WLC) approach was then compared with regional present landuse map. Most currently irrigated areas are contained within the area predicted to be suitable for irrigated agriculture. Relatively large additional areas are also predicted to be suitable, suggesting potential expansion, or that factors including total regional water availability and enterprise-specific economics are at play. The framework provides a useful tool with flexibility and efficiency. It enhances the existing AHP and OWA methods in the spatial context, and incorporates the uncertainty mechanism for guiding the multi-criteria decision making. It is particularly valuable given its capability to generate and visualise a wide range of multi-criteria decision scenarios, which can facilitate a better understanding of the spatial patterns of alternative landuse suitability potentials for future regional-scale landuse planning and water resource management.