Abstract
Virtual Geographic Environments (VGEs) represent a new analytical tool for understanding geographic processes. Among the fundamental solutions to advancing and deepening the development of VGEs are geographic modeling, geographic simulation, and geographic knowledge sharing. Forest is a major component of the geographic environment. This article proposes an integrated approach for analyzing and exploring plant growth processes and the relationship between plant growth and the environment, and describes the development of a software prototype that integrates ontology, artificial intelligence (AI) and virtual plant techniques. The strategy is as follows: First, we collect existing information on the growth and development patterns, morphological structure, and environment of a chosen plant from the botany, forestry, and ecology literature. Then, we construct an ontology framework to organize the collected information and individual cases into a knowledge base and support the inferential reasoning, botanical modeling and simulation. Through rule-based reasoning (RBR) and case-based reasoning (CBR), complex relationships between tree growth and the environment can be extracted. Next, the newly derived knowledge is integrated with a 3D method for modeling the growth of individual tree based on the same ontology framework. Finally, based on the description of the tree species, environment, growth stage, and phenophase, among other factors, key tree morphology parameters are derived via semantic reasoning. Using these parameters, a new 3D tree model is generated that is consistent with the specific habitat and growth phase. Our approach is useful for users who have little knowledge of botany or who lack the computer skills to construct realistic 3D tree models that are faithful to botanical features.
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Notes
Friedman-Hill E. Jess, the rule engine for the Javatm platform, http:/jessrules.com/jess.
The FaCT System, http://www.cs.man.ac.uk/~horrocks/FaCT/.
The Apache Software Foundation, 2011-2013, Reasoners and rule engines: Jena inference support. http://jena.apache.org/documentation/inference/index.html#RULEsyntax.
References
Allen MT, Prusinkiewicz P, Dejong TM (2005) Using L-systems for modeling source-sink interactions, architecture and physiology of growing trees: the L-PEACH model. New Phytol 3:869–880. doi:10.1111/j.1469-8137.2005.01348.x
Athanasiadis IN, Rizzoli AE, Janssen S et al (2009) Ontology for seamless integration of agricultural data and models. In: Sartori F, Sicilia MA, Manouselis N (eds) Metadata and semantic research. Springer, Berlin, pp 282–293
Batty R (1971) Modelling cities as dynamic system. Nature 231(5303):425–428
Bilke L, Fischer T, Helbig C et al (2014) TESSIN VISLab—laboratory for scientific visualization. Environ Earth Sci 72:3881–3889
Chamanara J, Konig-ries B (2014) A conceptual model for data management in the field of ecology. Ecol Inf 24:261–272. doi:10.1016/j.ecoinf.2013.12.003
Chen CX (2004) Studies of compilation of standard yield table of seedling stand of Cunninghamia lanceolata in general product area in Fujian. J Fujian For Sci Technol 4:1–4
Chen CX, Chen CH (2004) A study on establishment of normal yield table of seeding trees in margin product area of Chinese fir in Fujian Province. J Fujian Coll For 3:241–244
Chen CX, Xu KM, Zhan GB (1999) Study of compilation of standard yield table of seedling stand of Cunninghamia lanceolata in central product area in Fujian. East China For Manag 3:35–38
Chen M, Lin H, Hu MY (2013) Real-geographic-scenario-based virtual social environments: integrating geography with social research. Environ Plan 40:1103–1121
Cooper L, Walls RL, Elser J et al (2013) The plant ontology as a tool for comparative plant anatomy and genomic analyses. Plant Cell Physiol 54:e1–e1. doi:10.1093/pcp/pcs163
de la Asunción M, Castillo L, Fernández-Olivares J et al (2005) SIADEX: an interactive knowledge-based planner for decision support in forest fire fighting. Artif Intell Commun 4:257–268
de Reffye P, Edelin C, Francon J et al (1988) Plant models faithful to botanical structure and development. ACM SIGGRAPH Comput Graph 22(4):151–158
Gavin F, Sun ZH (2003) R5 model for case-based reasoning. Knowl-Based Syst 16:59–65
Godin C, Costes E, Sinoquet H (1999) A method for describing plant architecture which integrates topology and geometry. Ann Bot 84:343–357
Goodchild MF (2009) Geographic information systems and science: today and tomorrow. Ann GIS 15(1):3–9
Gruber TR (1993) A translation approach to portable ontology specifications. Knowl Acquis 2:199–220
Hemmerling R, Evers JB, Smolenova K et al (2013) Extension of the GroIMP modelling platform to allow easy specification of differential equations describing biological processes within plant models. Comput Electron Agric 92:1–8. doi:10.1016/j.compag.2012.12.007
Katari MS, Nowicki SD, Aceituno FF et al (2010) VirtualPlant: a software platform to support systems biology research. Plant Physiol 152:500–515
Lin H, Huang FR, Lu XJ et al (2010) Preliminary study on virtual geographic environment cognition and representation. J Remote Sens 4:822–838
Lin D, Chen CC, Tang LY et al (2011) Interactive pruning operation on virtual tree based on color encoding. J Comput-Aided Des Compu Graph 23(11):1799–1807
Lin H, Chen M, Lu G et al (2013a) Virtual geographic environments (VGEs): a new generation of geographic analysis tool. Earth Sci Rev 126:74–84
Lin H, Chen M, Lu GN (2013b) Virtual geographic environment—a workspace for computer-aided geographic environments. Ann Assoc Am Geogr 103(3):465–482
Lintermann B, Deussen O (1999) Interactive modeling of plants. IEEE Comput Graph Appl 1:56–65
Lopez G, Favreau R, Simth C et al (2008) Integrating simulation of architectural development and source-sink bebaviour of Peach trees by incorporating markov chains and physiological organ function submodels into L-PEACH. Funct Plant Biol 35:761–771
Lu GN (2011) Geographic analysis-oriented virtual geographic environment: framework, structure and functions. Sci China-Earth Sci 54:733–743
Meng XX, Li J, Su XL et al (2012) Large-scale ontology development and agricultural application based on knowledge domain framework. J Integr Agric 11(5):808–822
Novák P, sindelár R (2013) Ontology-based industrial plant description supporting simulation model design and maintenance. Industrial Electronics Society, IECON2013, 39th Annual Conference of the IEEE, Vienna, Austria
Prusinkiewicz P, Lindenmayer A (1990) The algorithmic beauty of plants. Springer-Verlag, New-York
Quan L, Tan P, Zeng G et al (2006) Image-based plant modeling. ACM Trans Graph (TOG) 3:599–604
Rasinmaki J, Mākinen A, Kalliovirta J (2009) SIMO: an adaptable simulation framework for multiscale forest resource data. Comput Electron Agric 66:76–84. doi:10.1016/j.compag.2008.12.007
Shen ZW, Chen CC, Tang LY et al (2012) Construction of ontology-based knowledge base system applied to plant modeling. J Fuzhou Univ (Nat Sci Ed) 1:51–57
Sonohat G, Sinoquet H, Kulandaivelu V et al (2006) Three-dimensional reconstruction of partially 3D-digitized peach tree canopies. Tree Physiol 26:337–351
Studer R, Benjamins VR, Fensel D (1998) Knowledge engineering: principles and methods. Data Knowl Eng 25:161–197
Tang LY, Chen CC, Zou J et al (2011) OntoPlant: an integrated virtual plant software package for different scale applications. In: Leung Y, Zhou C, Lees B (eds) proceedings of 2011 ieee international conference on spatial data mining and geographical knowledge services (ICSDM2011). IEEE Computer Society, BeiJing, pp 308–314
The Gene Ontology Consortium (2012) The gene ontology: enchancements for 2011. Nucl Acids Res 40:D559–D564. doi:10.1093/nar/gkr1028/
Walls RL, Athreya B, Cooper L et al (2012) Ontologies as integrative tools for plant science. Am J Bot 99(8):1263–1275
Watson I (1999) Case-based reasoning is a methodology not a technology. Knowl-Based Syst 12:303–308. doi:10.1016/S0950-7051(99)00020-9
Xie XH, Tang LY, Zou J et al (2012) Integrating rule-based and case-based reasoning for simulation of tree growth: a case of cunninghamia lanceolata. Scientia Silvae Sinicae 9:68–75
Yu XT (1997) Chinese fir Cultivation. Fujian Science and Technology Publish House, Fuzhou
Yu XT, He ZY, Fang TJ et al (1980) Research report on division of Chinese Fir product area and classification of site condition. J Fujian Coll For 1:14–39
Acknowledgments
We thank Prof. Guo Dian-sheng for scientific discussions and other members of our work group for help in developing the system. We thank Prof. Lin Hui and Dr. Chen Min for their valuable suggestions. We thank the experts for giving their opinions on the weighting of environmental factors. This work was supported by the “863” Hi-Tech Research and Development program of China (Grant No. 2012AA102002), a program of the National Science Foundation of China (Grant No. 41471334).
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Tang, L., Chen, C., Huang, H. et al. An integrated system for 3D tree modeling and growth simulation. Environ Earth Sci 74, 7015–7028 (2015). https://doi.org/10.1007/s12665-015-4763-2
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DOI: https://doi.org/10.1007/s12665-015-4763-2