UDK UDC 004.932.2 Doi: 10.31772/2587-6066-2018-19-4-598-604
A. S. Pyataev
Reshetnev Siberian State University of Science and Technologies, 31, Krasnoyarsky Rabochy Av., Krasnoyarsk, 660037, Russian Federation
Nowadays tree modeling algorithms are used in different fields of activity: from computer games to the plantation forest management. Tree modeling algorithm parameters can depend on different factors: it could be features of landscape, climate or geographical location. Depending on the tasks to be solved, the detail level of the created model is chosen. Forest management tasks often do not require a high detail level, it is sufficient to construct a schematic plantation model. For computer games the creation of photorealistic models is required. The paper proposes an algorithm of 3D tree modeling which consists of the following steps: first step – building a tree framework (modeling the growth of a tree and adding new nodes), while under the framework is meant a set of three-dimensional vectors with attributive data for each vector; then building a tree and overlaying textures. The trunk and branches of the modeled tree are approximated by truncated cones, the axes of which are the vectors of the frame. The tree model constructing algorithm is iterative. Every iteration is a tree growth stage. Thus, the tree is gradually grown to the required level. The developed algorithm allows modeling trees of different state categories. The feature of the proposed algorithm is the possibility of constructing a three-dimensional tree model with any detail level. For example, for coniferous trees it is possible to built a tree up to each needle.
Keywords: tree modeling, growth model 3D.

1. Lindsay M. Grayson, Robert A. Progar, Sharon M. Hood Predicting post-fire tree mortality for 14 conifers in the PacificNorthwest, USA: Model evaluation, development, and thresholds. Forest Ecology and Management. 2017, Vol. 399, P. 213–226.

2. Christopher Thurnher, Mario Klopf, Hubert Hasenauer MOSES – A tree growth simulator for modelling stand response inCentral Europe. Ecological Modelling. 2017, Vol. 349, P. 58–76.

3. Alberto Bressan, Michele Palladino, Wen Shen Growth models for tree stems and vines. Journal of Differential Equations. 2017, Vol. 263, P. 2280–2316.

4. Shaojun Hu, Zhengrong Li, Zhiyi Zhang, Dongjian He,Michael Wimmer Efficient Tree Modeling from Airborne LiDAR Point Clouds. Computers & Graphics. 2017. Doi:10.1016/j.cag.2017.04.004.

5. Robert Beyera, Dominik Bayerc, Véronique Letortb, Hans Pretzschc, Paul-Henry Cournède Validation of a functional-structural tree model using terrestrial Lidar data. Ecological Modelling. 2017, Vol. 357, P. 55–57.

6. Markku Еkerblom, Pasi Raumonen, Raisa Makipaa, Mikko Kaasalainen Automatic tree species recognition with quantitative structure models. Remote Sensing of Environment. 2017, Vol. 191, P. 1–12.

7. Yan-yun Han, Bao-guo Wu, Kai-yi Wang, En-ying Guo, Chen Dong, Zhi-bin Wang Individual-tree form growth models of visualization simulation for managed Larix principis-rupprechtii plantation. Computers and Electronics in Agriculture. 2016, Vol. 123, P. 341–350.

8. Favorskaya M. N. [Landscape scenes modeling based on laser scanning data and digital aerial photographs]. V materialakh vserossiyskoy konferentsii «Obrabotka prostranstvennykh dannykh v zadachakh monitoringa prirodnykh i antropogennykh protsessov» [Proc. of the all-Russian conf. “Spatial data processing in the tasks of monitoring natural and anthropogenic processes”]. Novosibirsk, 2017, P. 39–43 (In Russ.).

9. Yinhui Yang, Rui Wang, Hongxin Zhang, Hujun Bao ExploreTree: Interactive tree modeling in semantic trait space with online intent learning. Graphical Models. 2017, Vol. 000, P. 1–13.

10. Mihajlenko I. M. [Plant growth mathematical modeling based on experimental data]. Sel’skokhozyaystvennaya biologiya. 2007, No. 1, P. 103–111.

11. Omelko A. M. [Mathematical model of tree growth in the stands of dark coniferous species]. Biologicheskie issledovaniya na gornotaezhnoy stantsii. 2006, No. 10, P. 86–98 (In Russ.).

12. Omelko A. M. [An L-Systems Based Model of Growth of Conifer Tree Growth]. Sibirskiy ekologicheskiy zhurnal. 2006, No. 2, P. 181–188 (In Russ.).

13. Omelko А. М., Yakovleva A. N. Crown Shape Prediction Model for Picea ajanensis and Abies Nephrolepis Trees in Young Dark Coniferous Stands. Forest science and technology. 2006, Vol. 2, No. 2, P. 129–136.

14. Pyataev A. S. [Tree modelling Algorythm based on Lindenmayer sistem]. V materialakh 20 mezhdunarodnoy konferentsii “Tsifrovaya obrabotka signalov i ee primenenie” [The 20-th International Conference “Digital signal processing and its applications”]. 2018 (In Russ.).

15. Web 3D Consortium. Available at:http://www.web3d.org/ (accessed: 10.06.2018).

Pyataev Alexey Sergeevich – postgraduate student, Department of Informatics and computer engineering, Reshetnev

Siberian State University of Science and Technologies.