通过渔船轨迹数据中的异常识别可疑行为
Identification of suspicious behaviour through anomalies in the tracking data of fishing vessels
AI总结：
研究通过分析AIS渔船轨迹中的静默异常（定位缺失超24小时）发现94.9%发生在距岸100公里内，提出将其作为识别非法活动的代理指标，以优化监测与执法。
摘要：
自动定位设备能生成包含人类、动物和物体移动信息的大型数据集，揭示移动模式、热点区域及重叠现象等。这些信息是在清理不同性质错误的数据后获得的。然而，对于附着在船只上的自动信息系统（AIS），这些错误可能源于对电子设备的故意操纵。因此，对异常的分析可以提供关于可疑行为的有价值信息。在此，我们分析了通过自动识别系统获得的渔船轨迹异常。静默异常图（即定位数据缺失超过24小时时发生的异常）显示，它们更可能发生在靠近陆地的区域，观察到94.9%的异常发生在距离海岸不到100公里处。这种行为表明，将静默异常识别为非法活动的代理指标具有潜力。随着船只高分辨率定位数据的日益普及和强大统计分析工具的发展，我们为自动检测非法活动提供了线索，可能有助于优化监测、控制和监视措施。
英文摘要：
Automated positioning devices can generate large datasets with information on the movement of humans, animals and objects, revealing patterns of movement, hot spots and overlaps among others. This information is obtained after cleaning the data from errors of different natures. However, in the case of Automated Information Systems (AIS), attached to vessels, these errors can come from intentional manipulation of the electronic device. Thus, the analysis of anomalies can provide valuable information on suspicious behaviour. Here, we analyse anomalies of fishing vessel trajectories obtained with the Automatic Identification System. The map of silence anomalies, those occurring when positioning data is absent for more than 24 h, shows that they occur more likely closer to land, observing 94.9% of the anomalies at less than 100 km from the shore. This behaviour suggests the potential of identifying silence anomalies as a proxy for illegal activities. With the increasing availability of high-resolution positioning of vessels and the development of powerful statistical analytical tools, we provide hints on the automatic detection of illegal activities that may help optimise monitoring, control and surveillance measures.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
