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Interactive exploration of movement data: A case study of geovisual analytics for fishing vessel analysis

机译：交互式探索运动数据：以地理视觉分析为例进行渔船分析的案例研究

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The analysis of large movement datasets is a challenging task, because of their size and spatial complexity. This paper presents an interactive geovisual analytics approach named Hybrid Spatio-Temporal Filtering that integrates filtering of multiple movement characteristics, geovisual representations of the data, and multiple coordinated views to enable analysts to focus on movement patterns that are of interest. In particular, we propose a novel technique that combines the fractal dimension and velocity of movement paths to filter out uninteresting records through an iterative signature-building process. In order to allow analysts to explore the data at different scales of the movement path length, fractal dimension estimation is performed using an adjustable moving window technique. These tools are provided in conjunction with a probability-based zonal incursion tool to visually represent when the movement nears areas of interest. The outcome is a geovisual analytics system that allows analysts to specify a hybrid filter consisting of the desired movement path complexity, the length of the paths to consider, and the velocity range that represents specific types of behaviors. This filtering of the data supports analysts in identifying movement paths that match their specified interests, resulting in a reduction in the amount of data shown to the analyst. The utility of the approach was validated through field trials, wherein fisheries enforcement officers analyzed and explored fishing vessel movement data using the prototype system. The participants responded positively to the features of the system and the support it provided for their data analysis activities. The combination of fractal dimension, velocity, and temporal filtering helped them to effectively identify subsets of data that conformed to particular behavioral patterns of interest.
机译：由于大型运动数据集的大小和空间复杂性，对其进行分析是一项具有挑战性的任务。本文提出了一种称为混合时空时空过滤的交互式地理可视化分析方法，该方法集成了对多个运动特征，数据的地理可视化表示以及多个协调视图的过滤，以使分析人员能够专注于感兴趣的运动模式。特别是，我们提出了一种新颖的技术，该技术结合了分形维数和运动路径速度，以通过迭代签名构建过程过滤掉无用的记录。为了使分析人员能够以不同尺度的移动路径长度浏览数据，使用可调整的移动窗口技术进行分形维数估计。这些工具与基于概率的区域侵入工具一起提供，以直观地表示运动何时接近目标区域。结果是一个地理视觉分析系统，使分析人员可以指定一个混合过滤器，该过滤器由所需的移动路径复杂度，要考虑的路径长度以及代表特定行为类型的速度范围组成。数据的这种过滤支持分析师确定与其指定兴趣相匹配的移动路径，从而减少了向分析师显示的数据量。通过实地试验验证了该方法的实用性，其中，渔业执法人员使用原型系统分析和探索了渔船移动数据。参与者对系统的功能及其为数据分析活动提供的支持做出了积极的回应。分形维数，速度和时间滤波的组合帮助他们有效地识别出符合特定行为模式的数据子集。

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