Volume from Outlines on Terrains

Authors Marc van Kreveld, Tim Ophelders, Willem Sonke, Bettina Speckmann, Kevin Verbeek

Thumbnail PDF


  • Filesize: 13.6 MB
  • 15 pages

Document Identifiers

Author Details

Marc van Kreveld
  • Department of Information and Computing Sciences, Utrecht University, The Netherlands
Tim Ophelders
  • Department of Mathematics and Computer Science, TU Eindhoven, The Netherlands
Willem Sonke
  • Department of Mathematics and Computer Science, TU Eindhoven, The Netherlands
Bettina Speckmann
  • Department of Mathematics and Computer Science, TU Eindhoven, The Netherlands
Kevin Verbeek
  • Department of Mathematics and Computer Science, TU Eindhoven, The Netherlands

Cite AsGet BibTex

Marc van Kreveld, Tim Ophelders, Willem Sonke, Bettina Speckmann, and Kevin Verbeek. Volume from Outlines on Terrains. In 11th International Conference on Geographic Information Science (GIScience 2021) - Part I. Leibniz International Proceedings in Informatics (LIPIcs), Volume 177, pp. 16:1-16:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)


Outlines (closed loops) delineate areas of interest on terrains, such as regions with a heightened risk of landslides. For various analysis tasks it is necessary to define and compute a volume of earth (soil) based on such an outline, capturing, for example, the possible volume of a landslide in a high-risk region. In this paper we discuss several options to define meaningful 2D surfaces induced by a 1D outline, which allow us to compute such volumes. We experimentally compare the proposed surface options for two applications: similarity of paths on terrains and landslide susceptibility analysis.

Subject Classification

ACM Subject Classification
  • Information systems → Geographic information systems
  • Theory of computation → Computational geometry
  • Terrain model
  • similarity
  • volume
  • computation


  • Access Statistics
  • Total Accesses (updated on a weekly basis)
    PDF Downloads


  1. Mark de Berg and Marc van Kreveld. Trekking in the Alps without freezing or getting tired. Algorithmica, 18(3):306-323, 1997. Google Scholar
  2. Enrico Feoli and Vincenzo Zuccarello. Spatial pattern of ecological processes: the role of similarity in GIS applications for landscape analysis. In Manfred Fischer, Henk J. Scholten, and David Unwin, editors, Spatial Analytical Perspectives on GIS, pages 175-185. Taylor & Francis, 1996. Google Scholar
  3. Fausto Guzzetti, Alberto Carrara, Mauro Cardinali, and Paola Reichenbach. Landslide hazard evaluation: a review of current techniques and their application in a multi-scale study, Central Italy. Geomorphology, 31(1-4):181-216, 1999. Google Scholar
  4. L. A. M. Hendriks, H. Leummens, A. Stein, and P. de Bruijn. Use of soft data in a GIS to improve estimation of the volume of contaminated soil. Water, Air, and Soil Pollution, 101(1-4):217-234, 1998. Google Scholar
  5. Matthew Hiatt, Willem Sonke, Elisabeth A. Addink, Wout M. van Dijk, Marc van Kreveld, Tim Ophelders, Kevin Verbeek, Joyce Vlaming, Bettina Speckmann, and Maarten G. Kleinhans. Geometry and topology of estuary and braided river channel networks automatically extracted from topographic data. Journal of Geophysical Research: Earth Surface, 125(1), 2020. Google Scholar
  6. Jeffrey Hollister and W. Bryan Milstead. Using GIS to estimate lake volume from limited data. Lake and Reservoir Management, 26(3):194-199, 2010. Google Scholar
  7. Alec Holt. Spatial similarity and GIS: the grouping of spatial kinds. In Proceedings of the 11th Annual Colloquium of the Spatial Information Research Center (SIRC05), pages 241-250, 1999. Google Scholar
  8. Krzysztof Janowicz, Martin Raubal, Angela Schwering, and Werner Kuhn. Semantic similarity measurement and geospatial applications. Transactions in GIS, 12(6):651-659, 2008. Google Scholar
  9. A. Jarvis, H.I. Reuter, A. Nelson, and E. Guevara. Hole-filled seamless SRTM data V4, 2008. URL: http://srtm.csi.cgiar.org.
  10. A. Keutterling and A. Thomas. Monitoring glacier elevation and volume changes with digital photogrammetry and GIS at Gepatschferner glacier, Austria. International Journal of Remote Sensing, 27(19):4371-4380, 2006. Google Scholar
  11. Maarten Kleinhans, Marc van Kreveld, Tim Ophelders, Willem Sonke, Bettina Speckmann, and Kevin Verbeek. Computing Representative Networks for Braided Rivers. In Proceedings of the 33rd International Symposium on Computational Geometry (SoCG 2017), volume 77 of LIPIcs, pages 48:1-48:16, 2017. Google Scholar
  12. John McIntosh and May Yuan. Assessing similarity of geographic processes and events. Transactions in GIS, 9(2):223-245, 2005. Google Scholar
  13. Robert B. McMaster and K. Stuart Shea. Generalization in Digital Cartography. Association of American Geographers, 1992. Google Scholar
  14. Colin W. Mitchell. Terrain Evaluation. Routledge, 2014. Google Scholar
  15. Giorgos Mountrakis, Peggy Agouris, and Anthony Stefanidis. Similarity learning in GIS: an overview of definitions, prerequisites and challenges. In Spatial Databases: Technologies, Techniques and Trends, pages 294-321. IGI Global, 2005. Google Scholar
  16. Pascal Peduzzi, Christian Herold, and Walter Claudio Silverio Torres. Assessing high altitude glacier thickness, volume and area changes using field, GIS and remote sensing techniques: the case of Nevado Coropuna (Peru). Cryosphere, 4(3):313-323, 2010. Google Scholar
  17. Paola Reichenbach, Mauro Rossi, Bruce D Malamud, Monika Mihir, and Fausto Guzzetti. A review of statistically-based landslide susceptibility models. Earth-Science Reviews, 180:60-91, 2018. Google Scholar
  18. Angela Schwering. Approaches to semantic similarity measurement for geo-spatial data: A survey. Transactions in GIS, 12(1):5-29, 2008. Google Scholar
  19. K. Stuart Shea and Robert B. McMaster. Cartographic generalization in a digital environment: When and how to generalize. In Proceedings of Auto-Carto 9, pages 56-67, 1989. Google Scholar
  20. Willem Sonke, Marc van Kreveld, Tim Ophelders, Bettina Speckmann, and Kevin Verbeek. Volume-based similarity of linear features on terrains. In Proceedings of the 26th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, pages 444-447, 2018. Google Scholar
  21. Kevin Toohey and Matt Duckham. Trajectory similarity measures. Sigspatial Special, 7(1):43-50, 2015. Google Scholar
  22. David J. Varnes. Landslide Hazard Zonation: a review of principles and practice. Number 3 in Natural Hazards. United Nations, 1984. Google Scholar
  23. David Julius Völker. A simple and efficient GIS tool for volume calculations of submarine landslides. Geo-Marine Letters, 30(5):541-547, 2010. Google Scholar
  24. C. J. Wills, F. G. Perez, and C. I. Gutierrez. Susceptibility to deep-seated landslides in California, 2011. California Geological Survey, Map Sheet 58. Google Scholar
Questions / Remarks / Feedback

Feedback for Dagstuhl Publishing

Thanks for your feedback!

Feedback submitted

Could not send message

Please try again later or send an E-mail