Skip to main content
Springer Nature Link
Log in

Interactive synthesis and visualization of self-organizing trees for large-scale forest succession simulation

  • Regular Paper
  • Published:
Multimedia Systems Aims and scope Submit manuscript

Abstract

Realistic and interactive visualization of individual trees is a desirable functionality in numerous applications for landscape planning, ecosystem simulations, and forest management. However, achieving a persuasive visualization of extensive forests while maintaining an interactive experience remains a challenge. This paper introduces a new framework for a convincing and interactive visualization of large-scale forests originating from forest growth simulation. First, the GPU-based self-organizing tree synthesis algorithm is adapted to produce detailed tree models on-the-fly with the desired level of detail and at interactive rates. Next, the algorithm is enhanced to generate tree models corresponding to the forest simulation results and local growth conditions. Finally, a forest succession model, based on single trees, is linked to the tree synthesis algorithm, to produce detailed tree models that concur with the results of forest simulation. The results demonstrate that the generated trees follow predicted height from forest simulation, are adapted to their neighbors properly, and retain the typical form of the corresponding species. A decimation technique, integrated directly into tree geometry construction, lowers memory requirements for interactive visualization of forests containing thousands of trees. Finally, a combination of the GPU-based tree synthesis and load balancing enables interactive tree synthesis in-between individual frames.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11

Similar content being viewed by others

References

  1. Pretzsch, H., Grote, R., Reineking, B., Rötzer, T., et al.: Models for forest ecosystem management: a European perspective. Ann. Bot. 101(8), 1065–1087 (2008)

    Article  Google Scholar 

  2. Lewis, J.L., Sheppard, S.R.: Culture and communication: can landscape visualization improve forest management consultation with indigenous communities? Landsc. Urban Plan. 77(3), 291–313 (2006)

    Article  Google Scholar 

  3. Beneš, B., Massih, M.A., Jarvis, P., Aliaga, D.G., Vanegas, C.A.: Urban ecosystem design. In: Symposium on Interactive 3D Graphics and Games, I3D ’11, pp. 167–174. ACM, New York (2011)

  4. Reeves, W.T., Blau, R.: Approximate and probabilistic algorithms for shading and rendering structured particle systems. SIGGRAPH Comput. Graph. 19(3), 313–322 (1985)

    Article  Google Scholar 

  5. Favorskaya, M.N., Jain, L.C.: Modelling of Forest Ecosystems. In: Favorskaya, M.N., Jain, L.C. (eds.) Handbook on advances in remote sensing and geographic information systems: paradigms and applications in forest landscape modeling, pp. 397–415. Springer International Publishing, Cham (2017)

    Chapter  Google Scholar 

  6. Meitner, M.J., Sheppard, S.R., Cavens, D., Gandy, R., Picard, P., Harshaw, H., Harrison, D.: The multiple roles of environmental data visualization in evaluating alternative forest management strategies. Comput. Electron. Agric. 49(1), 192–205 (2005)

    Article  Google Scholar 

  7. Fabrika, M., Valent, P., Scheer, Ľ.: Thinning trainer based on forest-growth model, virtual reality and computer-aided virtual environment. Environ. Model. Softw. 100, 11–23 (2018)

    Article  Google Scholar 

  8. Kolmanič, S., Guid, N., Diaci, J.: ForestMAS—a single tree based secondary succession model employing Ellenberg indicator values. Ecol. Model. 279, 100–113 (2014)

    Article  Google Scholar 

  9. Kohek, Š., Strnad, D.: Interactive synthesis of self-organizing tree models on the GPU. Computing 97(2), 145–169 (2015)

    Article  MathSciNet  Google Scholar 

  10. Cordeiro, C.S., Chaimowicz, L.: Predictive lazy amplification: synthesis and rendering of massive procedural scenes in real time. In: 23rd SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI), 2010, pp. 263–270, IEEE, Gramado (2010)

    Chapter  Google Scholar 

  11. Bugmann, H.: A review of forest gap models. Clim. Change 51(3–4), 259–305 (2001)

    Article  Google Scholar 

  12. Larocque, G.R., Shugart, H.H., Xi, W., Holm, J.A.: Forest succession models. In: Larocque, G.R. (ed.) Ecological Forest Management Handbook. CRC Press, Boca Raton (2016)

    Chapter  Google Scholar 

  13. Bugmann, H.K.: A simplified forest model to study species composition along climate gradients. Ecology 77(7), 2055–2074 (1996)

    Article  Google Scholar 

  14. Pretzsch, H., Biber, P., Durskỳ, J.: The single tree-based stand simulator SILVA: construction, application and evaluation. For. Ecol. Manag. 162(1), 3–21 (2002)

    Article  Google Scholar 

  15. Nagel, J., Schmidt, M.: The silvicultural decision support system BWINPro. In: Hasenauer, H. (ed.) Sustainable Forest Management: Growth Models for Europe, pp. 59–63. Springer, Berlin (2006)

    Chapter  Google Scholar 

  16. Fabrika, M., Durskỳ, J.: Algorithms and software solution of thinning models for SIBYLA growth simulator. J. For. Sci. 51(10), 431–445 (2005)

    Article  Google Scholar 

  17. Ellenberg, H., Weber, H.E., Düll, R., Wirth, V., Werner, W., Paulissen, D.: Zeigerwerte von Pflanzen in Mitteleuropa. Scripta Geobotanica, vol. 18, pp. 1–248 (1992)

  18. Perttunen, J., Sievänen, R., Nikinmaa, E.: LIGNUM: a model combining the structure and the functioning of trees. Ecol. Model. 108(1), 189–198 (1998)

    Article  Google Scholar 

  19. Pretzsch, H.: Forest Dynamics, Growth and Yield: From Measurement to Model. Springer, Berlin (2009)

    Book  Google Scholar 

  20. Smelik, R.M., Tutenel, T., Bidarra, R., Benes, B.: A survey on procedural modelling for virtual worlds. Comput. Graph. Forum 33(6), 31–50 (2014)

    Article  Google Scholar 

  21. Bao, G., Li, H., Zhang, X., Dong, W.: Large-scale forest rendering: real-time, realistic, and progressive. Comput. Graph. 36(3), 140–151 (2012)

    Article  Google Scholar 

  22. Deussen, O., Colditz, C., Stamminger, M., Drettakis, G.: Interactive visualization of complex plant ecosystems. In: IEEE Visualization 2002, pp. 219–226. IEEE, Boston (2002)

  23. Cook, R.L., Halstead, J., Planck, M., Ryu, D.: Stochastic simplification of aggregate detail. ACM Trans. Graph. 26(3), 79:1–79:8 (2007)

    Article  Google Scholar 

  24. Neubert, B., Pirk, S., Deussen, O., Dachsbacher, C.: Improved model- and view-dependent pruning of large botanical scenes. Comput. Graph. Forum 30(6), 1708–1718 (2011)

    Article  Google Scholar 

  25. Gumbau, J., Chover, M., Remolar, I., Rebollo, C.: View-dependent pruning for real-time rendering of trees. Comput. Graph. 35(2), 364–374 (2011)

    Article  Google Scholar 

  26. Deussen, O., Hanrahan, P., Lintermann, B., Měch, R., Pharr, M., Prusinkiewicz, P.: Realistic modeling and rendering of plant ecosystems. In: Proceedings of the 25th Annual Conference on Computer Graphics and Interactive Techniques, SIGGRAPH ’98, pp. 275–286. ACM, New York (1998)

  27. Beneš, J., Kelly, T., Děchěrenko, F., Křivánek, J., Müller, P.: On realism of architectural procedural models. Comput. Graph. Forum 36(2), 225–234 (2017)

    Article  Google Scholar 

  28. Purvis, A., Sundstedt, V.: Perception of clones in forest rendering. In: Theory and Practice of Computer Graphics (TPCG), pp. 107–114. The Eurographics Association, Sheffield (2010)

    Google Scholar 

  29. Stoltman, A., Radeloff, V., Mladenoff, D.: Forest visualization for management and planning in Wisconsin. J. For. 102(4), 7–13 (2004)

    Google Scholar 

  30. Falcao, A.O., dos Santos, M.P., Borges, J.G.: A real-time visualization tool for forest ecosystem management decision support. Comput. Electron. Agric. 53(1), 3–12 (2006)

    Article  Google Scholar 

  31. Dong, T., Liu, S., Xia, J., Fan, J., Zhang, L.: A time-critical adaptive approach for visualizing natural scenes on different devices. PLoS One 10(2), 1–26 (2015)

    Article  Google Scholar 

  32. Garcia, I., Sbert, M., Szirmay-Kalos, L.: Tree rendering with billboard clouds. In: Proceedings of Third Hungarian Conference on Computer Graphics and Geometry, pp. 9–15, Budapest (2005)

  33. Fuhrmann, A.L., Umlauf, E., Mantler, S.: Extreme model simplification for forest rendering. In: Proceedings of the First Eurographics Conference on Natural Phenomena, NPH’05, pp. 57–67. Eurographics Association, Aire-la-Ville (2005)

  34. Kratt, J., Coconu, L., Dapper, T., Schliep, J.W., Paar, P.: Adaptive billboard clouds for botanical tree models. In: Hayek, W. (ed.) Peer Reviewed Proceedings of Digital Landscape Architecture 2014 at ETH Zurich, pp. 274–282. Wichmann, Berlin (2014)

    Google Scholar 

  35. Decaudin, P., Neyret, F.: Volumetric billboards. Comput. Graph. Forum 28(8), 2079–2089 (2009)

    Google Scholar 

  36. Bruneton, E., Neyret, F.: Real-time realistic rendering and lighting of forests. Comput. Graph. Forum 31(2), 373–382 (2012)

    Article  Google Scholar 

  37. Aakala, T., Shimatani, K., Abe, T., Kubota, Y., Kuuluvainen, T.: Crown asymmetry in high latitude forests: disentangling the directional effects of tree competition and solar radiation. Oikos 125(7), 1035–1043 (2016)

    Article  Google Scholar 

  38. Weber, J., Penn, J.: Creation and rendering of realistic trees. In: Proceedings of the 22nd Annual Conference on Computer Graphics and Interactive Techniques, SIGGRAPH ’95, pp. 119–128. ACM, New York (1995)

  39. Prusinkiewicz, P., James, M., Měch, R.: Synthetic topiary. In: Proceedings of the 21st Annual Conference on Computer Graphics and Interactive Techniques, SIGGRAPH ’94, pp. 351–358. ACM, New York (1994)

  40. Sen, S.I., Day, A.: Modelling trees and their interaction with the environment: a survey. Comput. Graph. 29(5), 805–817 (2005)

    Article  Google Scholar 

  41. Runions, A., Lane, B., Prusinkiewicz, P.: Modeling trees with a space colonization algorithm. In: Proceedings of the Third Eurographics Conference on Natural Phenomena, NPH’07, pp. 63–70. Eurographics Association, Aire-la-Ville (2007)

  42. Pałubicki, W., Horel, K., Longay, S., Runions, A., Lane, B., Měch, R., Prusinkiewicz, P.: Self-organizing tree models for image synthesis. ACM Trans. Graph. 28(3), 58:1–58:10 (2009)

    Google Scholar 

  43. Longay, S., Runions, A., Boudon, F., Prusinkiewicz, P.: TreeSketch: interactive procedural modeling of trees on a tablet. In: Proceedings of the International Symposium on Sketch-Based Interfaces and Modeling, SBIM ’12, pp. 107–120. Eurographics Association, Aire-la-Ville (2012)

  44. Greene, N.: Voxel space automata: modeling with stochastic growth processes in voxel space. ACM SIGGRAPH Comput. Graph. 23(3), 175–184 (1989)

    Article  Google Scholar 

  45. Měch, R., Prusinkiewicz, P.: Visual models of plants interacting with their environment. In: Proceedings of the 23rd Annual Conference on Computer Graphics and Interactive Techniques, SIGGRAPH ’96, pp. 397–410. ACM, New York (1996)

  46. Soler, C., Sillion, F., Blaise, F., Dereffye, P.: An efficient instantiation algorithm for simulating radiant energy transfer in plant models. ACM Trans. Graph. 22(2), 204–233 (2003)

    Article  Google Scholar 

  47. Yi, L., Li, H., Guo, J., Deussen, O., Zhang, X.: Tree growth modelling constrained by growth equations. Comput. Graph. Forum (2017). https://doi.org/10.1111/cgf.13263

    Google Scholar 

  48. Hädrich, T., Benes, B., Deussen, O., Pirk, S.: Interactive modeling and authoring of climbing plants. Comput. Graph. Forum 36(2), 49–61 (2017)

    Article  Google Scholar 

  49. Lipp, M., Wonka, P., Wimmer, M.: Parallel generation of multiple L-systems. Comput. Graph. 34(5), 585–593 (2010)

    Article  Google Scholar 

  50. Kohek, Š., Strnad, D.: Interactive large-scale procedural forest construction and visualization based on particle flow simulation. Comput. Graph. Forum 37(1), 389–402 (2018)

    Article  Google Scholar 

  51. King, D., Davies, S., Supardi, M.N., Tan, S.: Tree growth is related to light interception and wood density in two mixed dipterocarp forests of Malaysia. Funct. Ecol. 19(3), 445–453 (2005)

    Article  Google Scholar 

  52. Sumida, A., Miyaura, T., Torii, H.: Relationships of tree height and diameter at breast height revisited: analyses of stem growth using 20-year data of an even-aged Chamaecyparis obtusa stand. Tree Physiol. 33(1), 106–118 (2013)

    Article  Google Scholar 

  53. Zhang, S.: Foliage simplification based on multi-viewpoints for efficient rendering. J. Softw. 9(7), 1655–1665 (2014)

    Article  Google Scholar 

  54. Zhang, X., Bao, G., Meng, W., Jaeger, M., Li, H., Deussen, O., Chen, B.: Tree branch level of detail models for forest navigation. Comput. Graph. Forum 36(8), 402–417 (2017)

    Article  Google Scholar 

  55. Wang, Z., Bovik, A.C., Sheikh, H.R., Simoncelli, E.P.: Image quality assessment: from error visibility to structural similarity. IEEE Trans. Image Process. 13(4), 600–612 (2004)

    Article  Google Scholar 

  56. Wimmer, M., Scherzer, D., Purgathofer, W.: Light space perspective shadow maps. In: Keller, A., Jensen, H.W. (eds.) Rendering Techniques 2004 (Proceedings Eurographics Symposium on Rendering), pp. 143–151. Eurographics Association, Aire-la-Ville (2004)

    Google Scholar 

  57. Xu, L., Mould, D.: A procedural method for irregular tree models. Comput. Graph. 36(8), 1036–1047 (2012)

    Article  Google Scholar 

  58. Neubert, B., Franken, T., Deussen, O.: Approximate image-based tree-modeling using particle flows. ACM Trans. Graph. 26(3), 88:1–88:8 (2007)

    Article  Google Scholar 

  59. Zhang, X., Li, H., Dai, M., Ma, W., Quan, L.: Data-driven synthetic modeling of trees. IEEE Trans. Vis. Comput. Graph. 20(9), 1214–1226 (2014)

    Article  Google Scholar 

  60. Kim, D., Kim, J.: Procedural modeling and visualization of multiple leaves. Multimed. Syst. 23(4), 435–449 (2017)

    Article  Google Scholar 

  61. Zhu, X., Jin, X., You, L.: High-quality tree structures modelling using local convolution surface approximation. Vis. Comput. 31(1), 69–82 (2015)

    Article  Google Scholar 

  62. Stava, O., Pirk, S., Kratt, J., Chen, B., Měch, R., Deussen, O., Benes, B.: Inverse procedural modelling of trees. Comput. Graph. Forum 33(6), 118–131 (2014)

    Article  Google Scholar 

  63. Mongus, D., Žalik, B.: An efficient approach to 3D single tree-crown delineation in LiDAR data. ISPRS J. Photogramm. Remote Sens. 108, 219–233 (2015)

    Article  Google Scholar 

Download references

Acknowledgements

We thank the Slovenian Research Agency and Ministry for Agriculture, Forestry and Food for funding our research in the scope of the Target Research Program V4-1420. The authors acknowledge the financial support from the Slovenian Research Agency (Research Funding no. P2-0041, as well as Research Project no. J2-8176).

Author information

Authors and Affiliations

  1. Faculty of Electrical Engineering and Computer Science, University of Maribor, Koroška cesta 46, 2000, Maribor, Slovenia

    Štefan Kohek, Damjan Strnad, Borut Žalik & Simon Kolmanič

Authors
  1. Štefan Kohek
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Damjan Strnad
    View author publications

    You can also search for this author inPubMed Google Scholar

  3. Borut Žalik
    View author publications

    You can also search for this author inPubMed Google Scholar

  4. Simon Kolmanič
    View author publications

    You can also search for this author inPubMed Google Scholar

Corresponding author

Correspondence to Štefan Kohek.

Additional information

Communicated by F. Wu.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kohek, Š., Strnad, D., Žalik, B. et al. Interactive synthesis and visualization of self-organizing trees for large-scale forest succession simulation. Multimedia Systems 25, 213–227 (2019). https://doi.org/10.1007/s00530-018-0597-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00530-018-0597-6

Keywords