ISRN Forestry
Volume 2013 (2013), Article ID 196832, 12 pages
http://dx.doi.org/10.1155/2013/196832
Individual Growth Model for Eucalyptus Stands in Brazil Using Artificial Neural Network
1Department of Forestry, Faculty of Technology, University of Brasília, Campus Darcy Ribeiro, 70904-970 Brasília, DF, Brazil
2Department of Forestry, Federal University of Viçosa, Campus UFV, 36570-000 Viçosa, MG, Brazil
3Department of Forestry, Federal University of the Valleys of Jequitinhonha and Mucuri, Campus Diamantina, 39100-000 Diamantina, MG, Brazil
4Natural Resources Institute, Federal University of Itajubá, Campus Itajubá, 37500-903 Itajubá, MG, Brazil
Received 13 December 2012; Accepted 14 February 2013
Academic Editors: J. Kaitera, P. Newton, T. L. Noland, and P. Robakowski
Copyright © 2013 Renato Vinícius Oliveira Castro et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Linked References
- J. L. Clutter, J. C. Fortson, L. V. Pienaar, G. H. Brister, and R. L. Bailey, Timber Management: A Quantitative Approach, John Wiley & Sons, New York, NY, USA, 1983.
- L. S. Davis and K. N. Johnson, Forest Management, McGraw-Hill, New York, NY, USA, 1987.
- J. K. Vanclay, Modeling Forest Growth and Yield: Aplications to Mixed Tropical Forest, CAB International, Wallingford, UK, 1994.
- D. D. Munro, “Forest growth models—a prognosis,” in Growth Models for Tree and Stand Simulation, J. Fries, Ed., pp. 1–21, Royal College of Forestry, Stockholm, Sweden, 1974. View at Google Scholar
- R. M. Newnham, The development of a stand model for Douglas-fir [Ph.D. thesis], University of British Columbia, Canada, 1964.
- P. Soares and M. Tomé, “A distance dependent diameter growth model for first rotation eucalyptus plantation in Portugal,” in Empirical and Process—Bases Models for Forest Tree and Stand Growth Simulation, A. Amaro and M. Tomé, Eds., pp. 267–270, Salamandra, 1997. View at Google Scholar
- F. Crescente-Campo, P. Soares, M. Tomé, and U. Diéguez-Aranda, “Modeling noncatastrophic individual tree mortality for Pinus radiate plantations in northwestern Spain,” Forest Ecology and Management, vol. 257, no. 6, pp. 1542–1550, 2010. View at Google Scholar
- B. R. Mendes, N. Calegario, C. E. S. Volpato, and A. A. Melo, “Desenvolvimento de modelos de crescimento de árvores individuais fundamentado em equações diferenciais,” Cerne, vol. 12, pp. 254–263, 2006. View at Google Scholar
- F. B. Martins, Modelagem de crescimento em nível de árvore individual para plantios comerciais de eucaliptos [Ph.D. thesis], Universidade Federal de Viçosa, Brazil, 2011.
- ABRAF-Associação Brasileira de Florestas Plantadas, “Anuário estatístico da ABRAF: ano base 2010. Brasília,” 2011, http://www.abraflor.org.br/estatisticas/ABRAF11/ABRAF11-BR.pdf.
- M. A. Durlo, “Relações morfométricas para Cabralea canjerana (Well.) Mart,” Ciencia Florestal, vol. 11, no. 1, pp. 141–149, 2001. View at Google Scholar
- J. B. Della Flora, M. A. Durlo, and P. Soathelf, “Modelo de crescimento para árvores singulares—Nectandra megapotamica (Spreng.) Mez,” Ciencia Florestal, vol. 14, no. 1, pp. 165–177, 2004. View at Google Scholar
- M. A. Durlo, F. J. Sutili, and L. Denardi, “Modelagem da copa de Cedrela fissilis Vellozo,” Ciencia Florestal, vol. 14, no. 2, pp. 79–89, 2004. View at Google Scholar
- T. Chassot, Modelos de crescimento em diâmetro de árvores individuais de Araucaria angustifólia (Bertol.) Kuntze na floresta ombrófila mista [Ph.D. thesis], Universidade Federal de Santa Maria, Brazil, 2009.
- J. C. C. Campos and H. G. Leite, Mensuração Florestal: Perguntas e Respostas, Universidade Federal de Viçosa, Viçosa, Brazil, 2009.
- P. Miehle, M. Battaglia, P. J. Sands et al., “A comparison of four process-based models and a statistical regression model to predict growth of Eucalyptus globulus plantations,” Ecological Modelling, vol. 220, no. 5, pp. 734–746, 2009. View at Publisher · View at Google Scholar · View at Scopus
- D. Merkl and H. Hasenauer, “Using neural networks to predict individual tree mortality,” in Proceedings of the Int’l Conference on Engineering Applications of Neural Networks, pp. 10–12, Gibraltar, UK, 1998.
- M. Weingartner, D. Merkl, and H. Hasenauer, “Improving tree mortality predictions of Norway Spruce stands with neural networks,” in Proceedings of the Symposiun on Integration in Environmental Information Systems, Austria, 2000.
- H. Hasenauer, D. Merkl, and M. Weingartner, “Estimating tree mortality of Norway spruce stands with neural networks,” Advances in Environmental Research, vol. 5, no. 4, pp. 405–414, 2001. View at Publisher · View at Google Scholar · View at Scopus
- M. J. Diamantopoulou, “Artificial neural networks as an alternative tool in pine bark volume estimation,” Computers and Electronics in Agriculture, vol. 48, no. 3, pp. 235–244, 2005. View at Publisher · View at Google Scholar · View at Scopus
- E. Görgens, Estimação do volume de árvores utilizando redes neurais artificiais [Ph.D. thesis], Universidade Federal de Viçosa, Brazil, 2006.
- M. L. M. Silva, D. H. B. Binoti, J. M. Gleriani, and H. G. Leite, “Ajuste do modelo de Schumacher e Hall e aplicações de redes neurais artificiais para estimar volumes de árvores de eucalipto,” Árvore, vol. 33, no. 6, pp. 1133–1139, 2009. View at Google Scholar
- J. M. Paruelo and F. Tomasel, “Prediction of functional characteristics of ecosystems: a comparison of artificial neural networks and regression models,” Ecological Modelling, vol. 98, no. 2-3, pp. 173–186, 1997. View at Publisher · View at Google Scholar · View at Scopus
- M. Gevrey, I. Dimopoulos, and S. Lek, “Review and comparison of methods to study the contribution of variables in artificial neural network models,” Ecological Modelling, vol. 160, no. 3, pp. 249–264, 2003. View at Publisher · View at Google Scholar · View at Scopus
- H. G. Leite, M. L. M. da Silva, D. H. B. Binoti, L. Fardin, and F. H. Takizawa, “Estimation of inside-bark diameter and heartwood diameter for Tectona grandis Linn. trees using artificial neural networks,” European Journal of Forest Research, vol. 130, no. 2, pp. 263–269, 2011. View at Publisher · View at Google Scholar · View at Scopus
- A. P. Braga, Carvalho, A. C. P. L. F, and T. B. Ludemir, “Redes neurais artificiais,” in Sistemas Inteligentes, S. O. Rezende, Ed., pp. 141–168, Manole, Barueri, Brazil, 2003. View at Google Scholar
- A. K. Jain, J. Mao, and K. M. Mohiuddin, “Artificial neural networks: a tutorial,” Computer, vol. 29, no. 3, pp. 31–44, 1996. View at Google Scholar · View at Scopus
- S. Haykin, Redes Neurais: Princípios e Prática, Bookman, Porto Alegre, Brazil, 2001.
- J. M. Barreto, Introdução às Redes Neurais Artificiais, Universidade Federal de Santa Catarina, Florianópolis, Brazil, 2002.
- B. T. Guan and G. Gertner, “Using a parallel distributed processing system to model individual tree mortality,” Forensic Science, vol. 37, pp. 871–885, 1991. View at Google Scholar
- B. T. Guan and G. Gertner, “Modeling red pine tree survival with an artificial neural network,” Forensic Science, vol. 37, pp. 1429–1440, 1991. View at Google Scholar
- D. L. Schomoudt, P. Li, and A. L. Abbot, “Machine vision using artificial neural networks with local 3d neighborhoods,” Computers and Electronics in Agriculture, vol. 97, pp. 101–119, 1997. View at Google Scholar
- Q. B. Zhang, R. I. Hebda, Q. J. Zhang, and R. I. Alfaro, “Modeling tree-ring growth responses to climatic variables using artificial neural networks,” Forest Science, vol. 46, no. 2, pp. 229–239, 2000. View at Google Scholar · View at Scopus
- C. Liu, L. Zhang, C. J. Davis, D. S. Solomon, T. B. Brann, and L. E. Caldwell, “Comparison of neural networks and statistical methods in classification of ecological habitats using FIA data,” Forest Science, vol. 49, no. 4, pp. 619–631, 2003. View at Google Scholar · View at Scopus
- S. A. Corne, S. J. Carver, W. E. Kunin, J. J. Lennon, and A. W. S. van Hees, “Predicting forest attributes in Southeast Alaska using artificial neural networks,” Forest Science, vol. 50, no. 2, pp. 259–276, 2004. View at Google Scholar · View at Scopus
- R. Özçelik, M. J. Diamantopoulou, J. R. Brooks, and H. V. Wiant Jr., “Estimating tree bole volume using artificial neural network models for four species in Turkey,” Journal of Environmental Management, vol. 91, no. 3, pp. 742–753, 2010. View at Publisher · View at Google Scholar · View at Scopus
- R. A. Demolinari, Crescimento de povoamentos de eucalipto não-desbastados [Ph.D. thesis], Universidade Federal de Viçosa, Viçosa, Brazil, 2006.
- M. G. Silva, Produtividade, idade e qualidade da madeira de Eucalyptus destinada à produção de polpa celulósica branqueada [Ph.D. thesis], Universidade de São Paulo, São Paulo, Brazil, 2011.
- T. D. Keister and G. R. Tidwell, “Competition ratio dynamics for improved mortality estimates in simulated growth of forests stands,” Forest Science, vol. 21, pp. 46–51, 1975. View at Google Scholar
- G. R. Glover and J. N. Hool, “A basal area ratio predictor of loblolly pine plantation mortality,” Forest Science, vol. 25, pp. 275–282, 1979. View at Google Scholar
- R. C. de Miranda, J. C. C. Campos, F. de Paula Neto, and L. M. de Oliveira, “Predição da mortalidade regular para eucalipto,” Árvore, vol. 13, pp. 152–173, 1989. View at Google Scholar
- S. A. Machado, A. E. Tonon, A. F. Filho, and E. B. Oliveira, “Comportamento da mortalidade natural em bracatingais nativos em diferentes densidades iniciais e classes de sítio,” Ciencia Florestal, vol. 12, pp. 41–50, 2002. View at Google Scholar
- R. Maestri, C. R. Sanquetta, and J. C. Arce, “Modelagem do crescimento de povoamentos de Eucalyptus grandisatravés de processos de difusão,” Floresta, vol. 33, pp. 169–182, 2003. View at Google Scholar
- L. M. B. Rossi, H. S. Koehler, C. R. Sanquetta, and J. E. Arce, “Modelagem da mortalidade em florestas naturais,” Floresta, vol. 37, pp. 275–291, 2007. View at Google Scholar
- D. Zhao, B. Borders, M. Wang, and M. Kane, “Modeling mortality of second-rotation loblolly pine plantations in the Piedmont/Upper coastal plain and lower coastal plain of the southern United States,” Forest Ecology and Management, vol. 252, no. 1–3, pp. 132–143, 2007. View at Publisher · View at Google Scholar · View at Scopus
- A. R. Stage, “Prognosis model for stand development,” USDA Forest Service Research Papers INT-137, USDA, Washington, DC, USA, 1973. View at Google Scholar
- StatSoft Inc, STATISTICA (data analysis software system), version 8. 0, 2007.
- R. P. Lippmann, “An introduction to computing with neural nets,” IEEE ASSP Magazine, vol. 4, no. 2, pp. 4–22, 1987. View at Google Scholar · View at Scopus
- A. P. Braga, Carvalho, A. P. L. F, and T. B. Ludemir, Redes Neurais Artificiais: Teoria e Aplicações, Rio de Janeiro, Rio de Janeiro, Brazil, 2000.
- R. G. D. Steel and J. H. Torrie, Principles and Procedures of Statistics, McGraw-Hill, New York, NY, USA, 1960.
- P. A. Murphy and H. S. Sternitzke, Growth and Yield Estimation for Loblolly Pine in the West Gulf, Southern Forest Experiment Station, New Orleans, La, USA, 1979.
- J. Siipilehto, “A comparison of two parameter prediction methods for stand structure in Finland,” Silva Fennica, vol. 34, no. 4, pp. 331–349, 2000. View at Google Scholar · View at Scopus
- A. Monty, P. Lejeune, and J. Rondeux, “Individual distance-independent girth increment model for Douglas-fir in southern Belgium,” Ecological Modelling, vol. 212, no. 3-4, pp. 472–479, 2008. View at Publisher · View at Google Scholar · View at Scopus
- H. Pretzsch, P. Biber, and J. Ďurský, “The single tree-based stand simulator SILVA: construction, application and evaluation,” Forest Ecology and Management, vol. 162, no. 1, pp. 3–21, 2002. View at Publisher · View at Google Scholar · View at Scopus
- F. A. Graybill, Theory and Application of Linear Model, Duxbury, North Scituate, Mass, USA, 1976.
- D. A. Hamilton Jr., “A logistic model of mortality in thinned and unthinned mixed conifer stands of northern Idaho,” Forest Science, vol. 32, no. 4, pp. 989–1000, 1986. View at Google Scholar · View at Scopus
- I. E. Bella, “A new competition model for individual tree,” Forest Science, vol. 17, pp. 364–372, 1971. View at Google Scholar
- R. F. Daniels, “Simple competition indices and their correlation with annual loblolly pine tree growth,” Forest Science, vol. 22, pp. 454–456, 1976. View at Google Scholar
- H. Hasenauer and R. A. Monserud, “A crown ratio model for Austrian Forests,” Forest Ecology and Management, vol. 84, no. 1–3, pp. 49–60, 1996. View at Publisher · View at Google Scholar · View at Scopus
- S. Vospernik, R. A. Monserud, and H. Sterba, “Do individual-tree growth models correctly represent height: diameter ratios of Norway spruce and Scots pine?” Forest Ecology and Management, vol. 260, no. 10, pp. 1735–1753, 2010. View at Publisher · View at Google Scholar · View at Scopus
- H. Hasenauer, “Princípios para a modelagem de ecossistemas florestais,” Revista Ciência & Ambiente, vol. 20, pp. 53–69, 2000. View at Google Scholar
- Q. V. Cao, “Predictions of individual-tree and whole-stand attributes for loblolly pine plantations,” Forest Ecology and Management, vol. 236, no. 2-3, pp. 342–347, 2006. View at Publisher · View at Google Scholar · View at Scopus
- M. Tome and H. E. Burkhart, “Distance-dependent competition measures for predicting growth of individual trees,” Forest Science, vol. 35, no. 3, pp. 816–831, 1989. View at Google Scholar · View at Scopus
- H. Hasenauer, R. A. Monserud, and T. G. Gregoire, “Using simultaneous regression techniques with individual-tree growth models,” Forest Science, vol. 44, no. 1, pp. 87–95, 1998. View at Google Scholar · View at Scopus
- M. S. González, RÍO, M. del, I. Cañellas, and G. Montero, “Distance independent tree diameter growth model for cork oak stands,” Forest Ecology and Management, vol. 225, no. 1–3, pp. 262–270, 2006. View at Google Scholar
- K. Andreassen and S. M. Tomter, “Basal area growth models for individual trees of Norway spruce, Scots pine, birch and other broadleaves in Norway,” Forest Ecology and Management, vol. 180, no. 1–3, pp. 11–24, 2003. View at Publisher · View at Google Scholar · View at Scopus
- C. H. Peng and X. Wen, Recent Applications of Artificial Neural Networks in Forest Resource Management: An Overview, American Association for Artificial Intelligence Technical, Menlo Park, Calif, USA, 1999.
- E. Dogan, B. Sengorur, and R. Koklu, “Modeling biological oxygen demand of the Melen River in Turkey using an artificial neural network technique,” Journal of Environmental Management, vol. 90, no. 2, pp. 1229–1235, 2009. View at Publisher · View at Google Scholar · View at Scopus
- P. W. West, “Simulation of diameter growth and mortality in regrowth eucalypt forest of southern Tasmania,” Forensic Science, vol. 27, pp. 603–616, 1981. View at Google Scholar
- D. W. Hann and C. H. Wang, Mortality Equations for Individual Trees in the Mixed-Conifer Zone of Southwest Oregon, vol. 67 of Research Bulletin, Forest Research Laboratory, Oregon, Wash, USA, 1990.
- R. A. Monserud and H. Sterba, “Modeling individual tree mortality for Austrian forest species,” Forest Ecology and Management, vol. 113, no. 2-3, pp. 109–123, 1999. View at Publisher · View at Google Scholar · View at Scopus
- F. Crecente-Campo, P. Soares, M. Tomé, and U. Diéguez-Aranda, “Modelling annual individual-tree growth and mortality of Scots pine with data obtained at irregular measurement intervals and containing missing observations,” Forest Ecology and Management, vol. 260, no. 11, pp. 1965–1974, 2010. View at Publisher · View at Google Scholar · View at Scopus
- M. Palahí and T. Pukkala, “Optimising the management of Scots pine (Pinus sylvestris L.) stands in Spain based on individual-tree models,” Annals of Forest Science, vol. 60, no. 2, pp. 105–114, 2003. View at Google Scholar · View at Scopus
- F. C. C. Uzoh and W. W. Oliver, “Individual tree height increment model for managed even-aged stands of ponderosa pine throughout the western United States using linear mixed effects models,” Forest Ecology and Management, vol. 221, no. 1–3, pp. 147–154, 2006. View at Publisher · View at Google Scholar · View at Scopus