Data for: An algorithm to reduce a river network or other graph-like polygon to a set of lines

Published: 24 January 2020| Version 1 | DOI: 10.17632/h4pygk4xrd.1
Contributor:
Ethan Schaefer

Description

This zip file includes all principal data (vector and raster) used in the figures of the paper: Schaefer, E. I., and Pelletier, J. D. (submitted), "An algorithm to reduce a river network or other graph-like polygon to a set of lines", Computers & Geosciences including both inputs to and outputs from the four skeletonization algorithms compared (Zhang and Suen, RivWidthCloud, DeepRiver, and the one presented), as well as some intermediate products. The (Python 2) code implementation of the skeletonization algorithm presented in that paper is also included, along with a manual. In short, the contents, by directory, are: numgeo_code: numgeo 0.0.2a0, the code described in the paper numgeo_sample_data: data used in figures and analysis in the paper numgeo_sample_data/constant_width_binary_tree_rasters: rater data used in Experiment #1 of the paper numgeo_sample_data/constant_width_binary_tree_shapefiles: vector data used in Experiment #1 of the paper numgeo_sample_data/noisy_binary_tree_rasters: rater data used in Experiment #3 of the paper numgeo_sample_data/noisy_binary_tree_shapefiles: vector data used in Experiment #3 of the paper numgeo_sample_data/simple_shapefiles: vector data used in illustrative examples numgeo_sample_data/variable_width_binary_tree_rasters: rater data used in Experiment #2 of the paper numgeo_sample_data/variable_width_binary_tree_shapefiles: vector data used in Experiment #2 of the paper numgeo_sample_data/yukon_rasters: rater data used in Experiment #4 of the paper numgeo_sample_data/yukon_shapefiles: vector data used in Experiment #4 of the paper

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Institutions

University of Arizona Department of Planetary Sciences and Lunar and Planetary Laboratory, University of Arizona, Western University

Categories

Computer Vision, Algorithms, Geomorphology, Fluvial Geomorphology, Geographic Information Systems, Computational Geometry, Computer Vision Algorithms

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