Sea ice plays a significant role in global climate change. Marginal ice zone (MIZ) is defined as the transition zone between open ocean and pack ice where intensive air-ice-ocean-wave interactions between the ocean and the atmosphere occur. This definition of MIZ is rather vague, which affects its mapping. Previous data-driven methods extracted MIZ from single source data and conveniently used a single classification threshold. In this study, we propose to apply a concept-driven top down extraction method. We use a fuzzy inference system (FIS) to integrate multiple ice properties based upon the MIZ definition, and use membership functions to quantify the uncertainty of the threshold for several ice characteristics. This concept-driven method is applied to mapping the Antarctic MIZ between 2010 and 2021. Results show that a FIS successfully combines the ice concentration and ice thickness, while it allowed us to map the MIZ as objects with vague boundaries, thus well-presenting its indeterminate nature in space.

海冰在全球气候变化中扮演着重要角色。边缘冰区 (MIZ) 被定义为公海和浮冰之间的过渡区，在那里海洋和大气之间发生了强烈的空气-冰-海-波相互作用。MIZ的这个定义比较模糊，影响了它的映射。以前的数据驱动方法从单一源数据中提取 MIZ，并方便地使用单一分类阈值。在这项研究中，我们建议应用概念驱动的自上而下提取方法。我们使用模糊推理系统 (FIS) 根据 MIZ 定义整合多个冰特性，并使用隶属函数来量化多个冰特性阈值的不确定性。这种概念驱动的方法用于绘制 2010 年至 2021 年间的南极 MIZ。