4.7 Article

NETVOLC: An algorithm for automatic delimitation of volcano edifice boundaries using DEMs

期刊

COMPUTERS & GEOSCIENCES
卷 56, 期 -, 页码 151-160

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.cageo.2013.03.011

关键词

Morphometry; Volcano landform; Digital elevation model; Minimum cost flow networks

资金

  1. CONICET
  2. Fundacion Miguel Lillo

向作者/读者索取更多资源

Accurately delimiting boundaries is required for characterizing landforms through measurement of their geomorphometric parameters. Volcanism produces a wide range of landforms, from symmetric cones to very irregular massifs, that can gradually merge with the surroundings and contain other elements, thus complicating landform delimitation. Most morphometric studies of volcanoes delimit landforms manually, with the inconvenience of being time-consuming and subjective. Here we propose an algorithm, NETVOLC, for automatic volcano landform delimitation based on the premise that edifices are bounded by concave breaks in slope. NETVOLC applies minimum cost flow (MCF) networks for computing the best possible edifice outline using a DEM and its first- and second-order derivatives. The main cost function considers only profile convexity and aspect; three alternative functions (useful in complex cases) also consider slope, elevation and/or radial distance. NETVOLC performance is tested by processing the Mauna Kea pyroclastic cone field. Results using the main cost function compare favorably to manually delineated outlines in 2/3rds of cases, whereas for the remaining 1/3rd of cases an alternative cost function is needed, introducing some degree of subjectivity. Our algorithm provides a flexible, objective and time-saving tool for automatically delineating volcanic edifices. Furthermore, it could be used for delineating other landforms with concave breaks in slope boundaries. Finally, straightforward modifications can be implemented to extend the algorithm capabilities for delimiting landforms bounded by convex breaks in slope, such as summit craters and calderas. (c) 2013 Elsevier Ltd. All rights reserved.

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