TY - JOUR
T1 - An algorithm to reduce a river network or other graph-like polygon to a set of lines
AU - Schaefer, E. I.
AU - Pelletier, J. D.
N1 - Publisher Copyright:
© 2020 Elsevier Ltd
PY - 2020/12
Y1 - 2020/12
N2 - 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.
AB - 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.
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U2 - 10.1016/j.cageo.2020.104554
DO - 10.1016/j.cageo.2020.104554
M3 - Article
AN - SCOPUS:85093657482
SN - 0098-3004
VL - 145
JO - Computers and Geosciences
JF - Computers and Geosciences
M1 - 104554
ER -