Abstract In many geomorphic applications, it is necessary to reduce a polygon to a set of axial lines. For example, consider a fluvial channel network. On the one hand, this network has a polygonal footprint with reaches of finite width organized into a branching network. On the other hand, measuring the length or sinuosity of these reaches, as examples, requires the reduction of their polygonal footprints to axial lines. Here we present a new algorithm that can objectively reduce a polygon to such a set of axial lines, formally called a skeleton. Across four illustrative test cases, we show that this vector-based algorithm has some advantages over three raster-based algorithms in current geomorphic use because it generates smooth, continuous, well-centered skeletons and supports a useful scale-independent metric for the removal of spurious portions. Skeletons in this algorithm are uniquely constructed using a minimum of two parameters: a sampling interval (similar to a resolution) and a numeric pruning criterion (which determines skeleton complexity). We have implemented the algorithm as a freely available, open-source, GIS-ready Python code package without commercial dependency.

中文翻译：

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一种将河流网络或其他类似图形的多边形缩减为一组线的算法

摘要 在许多地貌应用中，需要将一个多边形简化为一组轴线。例如，考虑一个河流通道网络。一方面，该网络具有多边形覆盖区，具有有限宽度的范围，组织成分支网络。另一方面，作为示例，测量这些河段的长度或曲折度需要将它们的多边形足迹减少到轴线。在这里，我们提出了一种新算法，可以客观地将多边形缩减为这样一组轴线，正式称为骨架。在四个说明性测试案例中，我们表明这种基于矢量的算法在当前地貌使用中比三种基于栅格的算法具有一些优势，因为它生成平滑、连续、良好居中的骨架并支持有用的与尺度无关的度量，用于去除虚假部分。该算法中的骨架使用最少两个参数唯一地构建：采样间隔（类似于分辨率）和数字修剪标准（确定骨架复杂性）。我们已将该算法实现为免费提供、开源、支持 GIS 的 Python 代码包，没有商业依赖。