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Network-based Home Range Analysis Using Delaunay Triangulation

机译:基于网络的家庭范围分析使用Delaunay三角测量

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The home range is the fundamental measurement of fish and wildlife space-use patterns. Kernel density estimation (KDE) is the most widely applied home range estimator, although its poor performance has recently been documented. In this paper, we suggest that KDE is inappropriate for home range estimation, because it assumes Euclidean-based space usage. Because animal space-use patterns show characteristics of network-based movement, we develop a network-based home range estimator. First, we use Delaunay triangulation (DT) to approximate a network of travel paths from a set of animal point locations. Then, we adapt KDE to estimate home ranges as a function of that network. Preliminary results suggest that network-based home range estimation using DT has the potential to improve the way ecologists measure animal space-use patterns.
机译:家庭范围是鱼类和野生动物空间空间模式的根本测量。核密度估计(KDE)是应用最广泛的家庭范围估计器,尽管其性能最近已记录不佳。在本文中,我们建议KDE不适合家庭范围估算,因为它假设基于欧几里德的空间使用量。由于动物空间使用模式显示了基于网络的运动的特征,我们开发了一种基于网络的家庭范围估计器。首先,我们使用Delaunay三角测量(DT)来近似来自一组动物点位置的旅行路径网络。然后,我们根据该网络调整KDE来估算归属范围。初步结果表明,使用DT的网络归属范围估计有可能改善生态学家测量动物空间使用模式的方式。

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