Computer Graphics Procedural Modeling of Soil Structure

  • Hansoo Kim
  • Minerva J. Dorantes
  • Darrell G. Schulze
  • Bedrich Benes
Chapter
Part of the Progress in Soil Science book series (PROSOIL)

Abstract

Soil scientists in the USA have created a large national database of written soil profile descriptions that follow a well-defined set of rules for describing soil morphological properties. Interpreting these soil descriptions is a skill that requires considerable practice and experience. While writing a soil description is straightforward, recreating a visual representation of a soil profile from a written description is very difficult. So far, there is no generalized approach for translating written or tabular soil descriptions into visual representations. We propose a novel procedural modeling approach inspired by procedural models commonly used in the field of computer graphics. Our framework takes tabular soil morphological data (i.e., soil profile descriptions) as textual input and translates it into visual features based on parametric models. These models can be used to generate two-dimensional soil profiles or to generate three-dimensional interactive models that allow rotation, scaling, and other forms of visual explorations. The procedural modeling technique enables the user to generate the soil profile visual representation with only a small amount of data. The images do not need to be stored because they are generated as needed.

Keywords

Tabular soil morphological data Procedural modeling Computer graphics 

References

  1. Ebert DS, Musgrave FK, Peachey D, Perlin K, Worley S (2002) Texture & modeling: a procedural approach. 3rd ed. Morgan KaufmannGoogle Scholar
  2. Horn BKP (1981) Hill shading and the reflectance map. In: Proceedings of the IEEE, vol 69, pp 14–47Google Scholar
  3. Parish YI, Müller P (2001) Procedural modeling of cities. In: Proceedings of the 28th annual conference on computer graphics and interactive techniques. ACM, pp 301–308Google Scholar
  4. Prusinkiewicz ALP, Lindenmayer A, Hanan JS, Fracchia FD, Fowler D (1990) The algorithmic beauty of plants. Springer, New YorkCrossRefGoogle Scholar
  5. Schoeneberger PJ, Wysocki DA, Benham EC, Soil Survey Staff (2012) Field book for describing and sampling soils, Version 3.0. Natural Resources Conservation Service, National Soil Survey Center, Lincoln, NEGoogle Scholar
  6. Smelik RM, Tutenel T, Bidarra R, Benes B (2014) A survey on procedural modelling for virtual worlds. Comput Graph Forum 33(6):31–50CrossRefGoogle Scholar
  7. Stava O, Pirk S, Kratt J, Chen B, Měch R, Deussen O, Benes B (2014) Inverse procedural modelling of trees. Comput Graph Forum 33(6):118–131CrossRefGoogle Scholar
  8. Stava O, Benes B, Měch R, Aliaga DG, Krištof P (2010) Inverse procedural modeling by sutomatic generation of L-systems. Comput Graph Forum 29(2):665–674CrossRefGoogle Scholar
  9. Vanegas CA, Garcia-Dorado I, Aliaga DG, Benes B, Waddell P (2012) Inverse design of urban procedural models. ACM Trans Graph 31(6):168CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Hansoo Kim
    • 1
  • Minerva J. Dorantes
    • 2
  • Darrell G. Schulze
    • 2
  • Bedrich Benes
    • 1
  1. 1.Department of Computer Graphics TechnologyPurdue UniversityWest LafayetteUSA
  2. 2.Agronomy DepartmentPurdue UniversityWest LafayetteUSA

Personalised recommendations