从GPS轨迹中提取边界不确定的停留区:动物生态学的案例研究

M. Damiani, H. Issa, F. Cagnacci
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引用次数: 30

摘要

本文提出了一种基于时间感知、基于密度的低采样率GPS点轨迹停留区域识别聚类技术,并将其应用于动物迁徙研究。停留区被定义为通常不指定精确地理实体的空间的一部分,在该空间中,一个物体在一段时间内显著存在,尽管它离开的时间相对较短。停留区域可以划定,例如动物的居住地,即家园范围。所提出的技术能够通过指定与密度和存在相关的一小组参数,提取由密集和时间不相交的子轨迹表示的停留区域。虽然这项工作从动物生态学领域获得灵感,但我们认为该方法可以更广泛地关注并用于不同领域的视角,例如大时间尺度上的人类流动性研究。我们在一个案例研究中实验了这种方法,关于一群狍的季节性迁徙。
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Extracting stay regions with uncertain boundaries from GPS trajectories: a case study in animal ecology
In this paper we present a time-aware, density-based clustering technique for the identification of stay regions in trajectories of low-sampling-rate GPS points, and its application to the study of animal migrations. A stay region is defined as a portion of space which generally does not designate a precise geographical entity and where an object is significantly present for a period of time, in spite of relatively short periods of absence. Stay regions can delimit for example the residence of animals, i.e. the home-range. The proposed technique enables the extraction of stay regions represented by dense and temporally disjoint sub-trajectories, through the specification of a small set of parameters related to density and presence. While this work takes inspiration from the field of animal ecology, we argue that the approach can be of more general concern and used in perspective in different domains, e.g. the study of human mobility over large temporal scales. We experiment with the approach on a case study, regarding the seasonal migration of a group of roe deer.
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