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首页> 美国卫生研究院文献>Saudi Journal of Biological Sciences >A novel GIS-based approach to assess beekeeping suitability of Mediterranean lands
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A novel GIS-based approach to assess beekeeping suitability of Mediterranean lands

机译：一种基于GIS的新颖方法来评估地中海地区养蜂的适宜性

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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, highlighting 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.
机译：蜜蜂对环境和经济至关重要。但是，世界范围内的下降幅度很大，对粮食作物的稳定性和单产构成了严重威胁。养蜂至关重要，将蜂蜜生产的广泛经济方面与蜜蜂提供的重要生态服务相结合。在这种情况下，迅速确定养蜂区域是具有战略意义的，因为它可以最大程度地提高生产力并降低群体损失的风险。模糊逻辑是专门用于解决问题的理想方法，因为它专为管理具有高度不确定性的问题而设计。这项研究测试了一种新颖的基于GIS的方法来评估位于卡拉布里亚（意大利南部）的土地的养蜂适宜性，而无需依赖于层次分析法-多标准决策（AHP-MCDM），从而避免了由于技术和决策而受到的限制制造者的影响。此外，这里使用的数据是从开放访问源中完全检索出来的，这突显了我们的方法具有成本低廉的特点，并且可以轻松地针对各种地理环境进行复制。值得注意的是，通过我们的实验获得的结果已通过实际的养蜂现实得到了验证。除了养蜂，该系统的使用不仅可以应用于养蜂土地适宜性评估，而且可以成功地扩展到其他类型的土地适宜性评估。

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