We present a visual analytics approach to explore and analyze movement data as collected by ecologists interested in understanding migration. Migration is an important and intriguing process in animal ecology, which may be better understood through the study of tracks for individuals in their environmental context. Our approach enables ecologists to explore the spatio-temporal characteristics of such tracks interactively. It identifies and aggregates stopovers depending on a scale at which the data is visualized. Statistics of stopover sites and links between them are shown on a zoomable geographic map which allows to interactively explore directed sequences of stopovers from an origin to a destination. In addition, the spatio-temporal properties of the trajectories are visualized by means of a density plot on a geographic map and a calendar view. To evaluate our visual analytics approach, we applied it on a data set of 75 migrating gulls that were tracked over a period of 3 years. The evaluation by an expert user confirms that our approach supports ecologists in their analysis workflow by helping to identifying interesting stopover locations, environmental conditions or (groups of) individuals with characteristic migratory behavior, and allows therefore to focus on visual data analysis.

中文翻译：

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海鸥数据迁移模式的可视化探索

我们提出了一种可视化分析方法来探索和分析对了解迁移感兴趣的生态学家收集的运动数据。迁徙是动物生态学中一个重要而有趣的过程，通过研究个体在其环境背景下的轨迹可以更好地理解这一过程。我们的方法使生态学家能够以交互方式探索此类轨迹的时空特征。它根据数据可视化的规模来识别和聚合中途停留。中途停留站点的统计数据和它们之间的链接显示在可缩放的地理地图上，该地图允许交互式探索从起点到目的地的定向中途停留序列。此外，轨迹的时空特性通过地理地图上的密度图和日历视图进行可视化。为了评估我们的可视化分析方法，我们将其应用于 75 只迁徙海鸥的数据集，这些数据集在 3 年内被跟踪。专家用户的评估证实，我们的方法通过帮助识别有趣的中途停留地点、环境条件或具有特征迁移行为的（组）个体来支持生态学家的分析工作流程，因此可以专注于视觉数据分析。