时空和语义结合的船舶轨迹数据压缩方法  

A vessel trajectory data compression method combining spatio-temporal and semantic features

作　　者：刘海砚[1] 郭漩 刘俊楠[3] LIU Haiyan;GUO Xuan;LIU Junnan(Institute of Data and Target Engineering,Information Engineering University,Zhengzhou 450000,China;School of Computer and Artificial Intelligence,Zhengzhou University,Zhengzhou 450000,China;School of Geo-Science and Technology,Zhengzhou University,Zhengzhou 450000,China)

机构地区：[1]信息工程大学数据与目标工程学院,河南郑州450000 [2]郑州大学计算机与人工智能学院,河南郑州450000 [3]郑州大学地球科学与技术学院,河南郑州450000

出　　处：《测绘学报》2023年第11期1974-1982,共9页Acta Geodaetica et Cartographica Sinica

基　　金：国家自然科学基金(42301526);河南省自然科学基金(182300410005);地理信息工程国家重点实验室基金(SKLGIE2023-M-4-1);河南省重点研发与推广专项(科学攻关)(232102211026)。

摘　　要：大数据时代积累了覆盖范围广、时效性强的船舶轨迹数据。对海量冗余轨迹数据进行压缩,可提高检索效率,降低数据存储和传输负担;然而现有方法容易忽略移动对象的运动特征。因此,本文提出一种顾及轨迹时空特征和航行语义特征的压缩方法。首先,分析船舶轨迹的空间、时间和语义特征,设计顾及时空语义特征的轨迹数据压缩流程;其次,通过道格拉斯-普克和滑动窗口法计算轨迹点的时空和语义特征值;然后,加权融合轨迹点的时空和语义特征,构建轨迹点的重要性排序,并通过指定压缩比例获取保留轨迹点数目,实现船舶轨迹数据压缩;最后,根据压缩算法效率、质量和实例分析,表明本文方法可保留行驶的动态语义信息和时空形态特征,既可根据压缩比例控制压缩过程,又可显著减少数据冗余,为后续轨迹挖掘等应用提供数据基础。A large amount of vessel trajectory data with a wide coverage and strong timeliness has been accumulated in the big data era,whose spatio-temporal and semantic state changes can be represented by some trajectory points.To increase trajectory retrieval efficiency and reduce storage and transmission burden,this paper proposes a trajectory compression method upon trajectory spatio-temporal features and navigation semantic features.First,spatio-temporal and semantic features of vessel trajectory are analyzed,and a trajectory data compression method is proposed.Then,trajectory points with significant spatio-temporal and semantic features are extracted by Douglas-Peucker and sliding window methods to construct spatio-temporal and semantic ranks,respectively.To synthesize these features,the weighted fusion method is introduced to combine these ranks,thus ranking the trajectory points in order.Finally,vessel trajectory can be compressed by calculating reserved point number from compression ratio.The proposed method is verified through comparative analysis of efficiency and quality,and a compression case.The experiments indicate that the method could not only reduce redundancy significantly,but also retain the dynamic semantics and spatio-temporal morphological features of driving,thus providing a solid foundation for trajectory mining.

关 键 词：数据压缩 轨迹数据压缩 时空特征 语义特征 船舶轨迹 

分 类 号：P208[天文地球—地图制图学与地理信息工程]