Group decision making with a fuzzy linguistic majority
Fuzzy Sets and Systems
On ordered weighted averaging aggregation operators in multicriteria decisionmaking
IEEE Transactions on Systems, Man and Cybernetics
Applications and extensions of OWA aggregations
International Journal of Man-Machine Studies
A framework for multi-source data fusion
Information Sciences: an International Journal - Special issue: Soft computing data mining
Approaches to Multisensor Data Fusion in Target Tracking: A Survey
IEEE Transactions on Knowledge and Data Engineering
Robust fusion of uncertain information
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Information combination operators for data fusion: a comparative review with classification
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Performance and geometric interpretation for decision fusion with memory
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
International Journal of Geographical Information Science
Handling heterogeneous bipolar information for modelling environmental syndromes of global change
Environmental Modelling & Software
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The monitoring of the environment's status at continental scale involves the integration of information derived by the analysis of multiple, complex, multidisciplinary, and large-scale phenomena. Thus, there is a need to define synthetic Environmental Indicators (EIs) that concisely represent these phenomena in a manner suitable for decision-making. This research proposes a flexible system to define EIs based on a soft fusion of contributing environmental factors derived from multi-source spatial data (mainly Earth Observation data). The flexibility is twofold: the EI can be customized based on the available data, and the system is able to cope with a lack of expert knowledge. The proposal allows a soft quantifier-guided fusion strategy to be defined, as specified by the user through a linguistic quantifier such as 'most of'. The linguistic quantifiers are implemented as Ordered Weighted Averaging operators. The proposed approach is applied in a case study to demonstrate the periodical computation of anomaly indicators of the environmental status of Africa, based on a 7-year time series of dekadal Earth Observation datasets. Different experiments have been carried out on the same data to demonstrate the flexibility and robustness of the proposed method.