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Honeybees are critically important for the environment and to the economy. However, there are in substantial decline worldwide, leading to serious threat to the stability and yield of food crops. Beekeeping is of pivotal importance, combining the wide economical aspect of honey production and the important ecological services provided by honeybees. In this scenario, the prompt identification of beekeeping areas is strategic, since it maximised productivity and lowered the risks of colony losses. Fuzzy logic is an ideal approach for problem-solving tasks, as it is specifically designed to manage problems with a high degree of uncertainty. This research tested a novel GIS-based approach to assess beekeeping suitability of lands located in Calabria (Southern Italy), without relying to Analytic Hierarchy Process - Multiple Criteria Decision Making (AHP-MCDM), thus avoiding the constraints due to the technique and decision makers' influences. Furthermore, the data used here were completely retrieved from open access sources, high-lighting that our approach is characterized by low costs and can be easily reproduced for a wide arrays of geographical contexts. Notably, the results obtained by our experiments were validated by the actual beekeeping reality. Besides beekeeping, the use of this system could not only be applied in beekeeping land suitability evaluations, but may be successfully extended to other types of land suitability evaluations. (C) 2017 The Authors. Production and hosting by Elsevier B.V. on behalf of King Saud University.