Use of digital photographs as an alternative to diameter tape and caliper in upper-stem diameter measurements

Authors

DOI:

https://doi.org/10.33448/rsd-v10i16.23153

Keywords:

Dendrometry; Smalian's formula; Diameter measurements.

Abstract

In forest volume estimation, biases do not derive only from data processing and estimates but may be of selection when the sample does not guarantee the representativeness of population, of admission when the sample came from a special population, of wrong sampling, or it can be immeasurable such as systematic errors and caused by the operator or the instrument itself. The volume of a stand can be obtained using mathematical expressions that use the variables height and diameter, or circumference where the diameter is obtained using caliper and the circumference through diameter tape, and both incur errors that depend on the shape and deformity of the trunk cross sections. This paper proposes a new methodology based on the use of digital images of the trunk sections and the use of the Artificial Neural Networks technique to obtain the sectional area in upper-stem diameter measurements whose volume estimation is more precise and accurate than the obtained by caliper and diameter tape when compared to the real volume data obtained by the xylometer. With a database of Eucalyptus sp. clonal stands, the proposed methodology was able to accurately estimate the sectional area of trunk cross sections, resulting in volume estimates with only 0.26% of average variation compared to the xylometer, while caliper and tape presented, respectively, -1.41% and 4.08% of variation. The results obtained from the digital images also proved not to be biased, while the diameter tape overestimated volumes and the caliper underestimated them.

References

Amorim, L. M., Leite, E. da S., Souza, D. R. de, Silva, L. F. da, Mello, C. R. de, & Lima, J. M. de. (2021). Artificial neural networks and regression analysis for volume estimation in native species. Revista Brasileira de Engenharia Agrícola e Ambiental, 25(10), 664–669. https://doi.org/10.1590/1807-1929/agriambi.v25n10p664-669

Bernardi, L. K. (2020). Inferência Multimodelos na predição de multiprodutos em povoamentos de Eucalyptus sp [Dissertação (Mestrado em Planejamento e Uso de Recursos Renováveis) - Universidade Federal de São Carlos, Sorocaba, SP, 65 f. https://repositorio.ufscar.br/handle/ufscar/12384

Bernardi, L. K., Thiersch, M. F. B. M., Arteaga, A. J. M., Almeida, A. A. A., Pádua, F. A., & Thiersch, C. R. (2021). Diferentes modelos para o afilamento do tronco de Eucalyptus sp. para o cenário florestal brasileiro. Ciência Florestal, 31(3), 1364–1382. https://doi.org/10.5902/1980509840376

Bila, J. M. (2011). Relações hipsométricas de ecossistemas de mopane Colophospermum mopane em Mabalane, Província de Gaza, Moçambique. Pesquisa Florestal Brasileira, 31(66), 155–160. https://doi.org/10.4336/2011.pfb.31.66.155

Correa, A. P. M., Lima, A. P. L. de, Lima, S. F. de, Silva, W. G. da, Stolle, L., & Silva, A. A. P. da. (2020). Spacing effect on growth and yeld of fast rotation Eucalyptus at 24 months of age. Research, Society and Development, 9(6), e49963404. https://doi.org/10.33448/rsd-v9i6.3404

Diéguez-Aranda, U., Castedo-Dorado, F., Álvarez-González, J. G., & Rojo, A. (2006). Compatible taper function for Scots pine plantations in northwestern Spain. Canadian Journal of Forest Research, 36(5), 1190–1205. https://doi.org/10.1139/x06-008

Dobner Jr., M., Higa, A. R., & Urbano, E. (2012). Determinação da idade e intensidade ótimas para realização do primeiro desbaste em um povoamento de Eucalyptus dunnii. FLORESTA, 42(3), 485. https://doi.org/10.5380/rf.v42i3.21028

Figueiredo-Filho, A., Machado, S. A., & Carneiro, M. R. A. (2000). Testing accuracy of log volume calculation procedures against water displacement techniques (xylometer). Canadian Journal of Forest Research, 30(6), 990–997. https://doi.org/10.1139/x00-006

Fischer, F., Scolforo, J. R. S., Acerbi-Júnior, F. W., Mello, J. M., & Maestri, R. (2001). Exatidão dos modelos polinomiais não-segmentados e das razões entre volumes para representar o perfil do tronco de Pinus taeda. Ciência Florestal, 11(1), 167–188.

Godoy, L. J. G. de, Yanagiwara, R. S., Villas Bôas, R. L., Backes, C., & Lima, C. P. de. (2007). Análise da imagem digital para estimativa da área foliar em plantas de laranja “Pêra.” Revista Brasileira de Fruticultura, 29(3), 420–424. https://doi.org/10.1590/S0100-29452007000300004

Hao, Y., Widagdo, F. R. A., Liu, X., Quan, Y., Dong, L., & Li, F. (2020). Individual Tree Diameter Estimation in Small-Scale Forest Inventory Using UAV Laser Scanning. Remote Sensing, 13(1), 24. https://doi.org/10.3390/rs13010024

Indústria Brasileira de Árvores, I. (2020). Relatório Anual 2020. https://iba.org/datafiles/publicacoes/relatorios/relatorio-iba-2020.pdf

Lucena, L. R. R., Leite, M. L. M. V., Cruz, M. G., & De Sá Júnior, E. H. (2018). Estimativa da área foliar em Urochloa mosambicensis por dimensões foliares e imagens digitais. Archivos de Zootecnia, 67(259), 408–413. https://doi.org/10.21071/az.v67i259.3798

Lumbres, R. I. C., Pyo, J. K., & Lee, Y. J. (2014). Development of stem taper equations for Pinus kesiya in Benguet province, Philippines. Forest Science and Technology, 10(1), 22–28. https://doi.org/10.1080/21580103.2013.821094

Mendonça, A. R., Silva, G. F., Oliveira, J. T. da S., & Assis, A. L. (2007). Avaliação de funções de afilamento visando a otimização de fustes de Eucalyptus sp. para multiprodutos. Cerne, 13(1), 71–82.

Oliveira, G. M. V., Mello, J. M. de, Altoé, T. F., Scalon, J. D., Scolforo, J. R. S., & Pires, J. V. (2015). Equações hipsométricas para Eucalyptus spp. não manejado em idade avançada com técnicas de inclusão de covariantes. CERNE, 21(3), 483–492. https://doi.org/10.1590/01047760201521031740

Özçelik, R., & Crecente-Campo, F. (2016). Stem Taper Equations for Estimating Merchantable Volume of Lebanon Cedar Trees in the Taurus Mountains, Southern Turkey. Forest Science, 62(1), 78–91. https://doi.org/10.5849/forsci.14-212

Rosenblatt, F. (1958). The perceptron: A probabilistic model for information storage and organization in the brain. Psychological Review, 65(6), 386–408. https://doi.org/10.1037/h0042519

Sabliov, C. M., Boldor, D., Keener, K. M., & Farkas, B. E. (2002). Image processing method to determine surface area and volume of axi-symmetric agricultural products. International Journal of Food Properties, 5(3), 641–653. https://doi.org/10.1081/JFP-120015498

Scolforo, J. R. S., & Thiersch, C. R. (2004). Biometria Florestal: medição, volumetria e gravimetria. UFLA/FAEPE.

Vieira Junior, P. A., Dourado Neto, D., Cicero, S. M., Jorge, L. A. C., Manfron, P. A., & Martin, T. N. (2006). Estimativa da Área Foliar em Milho Através de Análise de Imagens. Revista Brasileira de Milho e Sorgo, 5(1), 58–66. https://doi.org/10.18512/1980-6477/rbms.v5n1p58-66

Young, H. E. (1966). Forest measurement accuracy. The Forestry Chronicle, 42(4), 438–443. https://doi.org/10.5558/tfc42438-4

Published

06/12/2021

How to Cite

THIERSCH, C. R.; SANTOS, C. J.; BERNARDI, L. K. .; PÁDUA, F. A. de; THIERSCH, M. F. B. M. Use of digital photographs as an alternative to diameter tape and caliper in upper-stem diameter measurements. Research, Society and Development, [S. l.], v. 10, n. 16, p. e62101623153, 2021. DOI: 10.33448/rsd-v10i16.23153. Disponível em: https://rsdjournal.org/index.php/rsd/article/view/23153. Acesso em: 19 apr. 2024.

Issue

Section

Agrarian and Biological Sciences