VOLUMETRIC MODELING OF Pinus taeda L. FROM ORBITAL IMAGES

Authors

  • Carla Talita Pertille Universidade do Estado de Santa Catarina - UDESC. Centro de Ciências Agroveterinárias - CAV. Programa de Pós Graduação em Engenharia Florestal - PPGEF. https://orcid.org/0000-0003-0063-9819
  • Marcos Felipe Nicoletti Universidade do Estado de Santa Catarina - UDESC. Centro de Ciências Agroveterinárias - CAV. Programa de Pós Graduação em Engenharia Florestal - PPGEF. https://orcid.org/0000-0003-4732-0119

DOI:

https://doi.org/10.5380/biofix.v7i1.82066

Keywords:

Remote sensing, Stepwise, Vegetation index

Abstract

This work aimed to investigate the potential of image-derived indices derived from Sentinel-2/MSI images in the volumetric modeling of a stand of Pinus taeda L. located in Bom Retiro, State of Santa Catarina. For this purpose, field data derived from a forest inventory were used, by the fixed area method and simple random sampling with an allocation of 18 circular plots of 400 m². The remotely located data comprised an orbital image from the Sentinel-2/MSI sensor. From this image, 14 average vegetation indices per plot were calculated. These indices were correlated with the volume by plot (m³ 0.04 ha-1) derived from the inventory. The indices with the best correlation for volume by plot (m³ 0.04 ha-1) were the Generalized Difference Vegetation Index (GDVI) and Adjusted Soil Vegetation Index (SAVI) with 0.39 and 0.36, respectively. The best regression model completed using these VIs estimated the volume by plot with R² controls of 0.9402 and Syx of 1.44%. The use of spectral indices generated from Sentinel-2/MSI sensor data enabled the volumetric estimate of the Pinus taeda L. stand, not revealing differences between the volume accumulated by forest inventory and by orbital images. However, it is worth pointing out that new tests be carried out on other forest species and with medium to high spatial resolution sensors.

Author Biographies

Carla Talita Pertille, Universidade do Estado de Santa Catarina - UDESC. Centro de Ciências Agroveterinárias - CAV. Programa de Pós Graduação em Engenharia Florestal - PPGEF.

Cursando MBA em Tecnologia para Negócios: AI, Data Science e Big Data afim de aplicar tais tecnologias às florestas visando garantir produtividade e melhor utilização dos recursos florestais. Mestra em Engenharia Florestal com ênfase em Sensoriamento Remoto e Geoprocessamento pela Universidade do Estado de Santa Catarina - UDESC, especialista em MBA em Gestão Florestal pela Universidade Federal do Paraná (UFPR) e graduada em Engenharia Florestal na Universidade Tecnológica Federal do Paraná (UTFPR).

Marcos Felipe Nicoletti, Universidade do Estado de Santa Catarina - UDESC. Centro de Ciências Agroveterinárias - CAV. Programa de Pós Graduação em Engenharia Florestal - PPGEF.

Atualmente é Professor Adjunto da Universidade do Estado de Santa Catarina. Possui graduação em Engenharia Florestal pela Universidade do Estado de Santa Catarina - UDESC. Possui Mestrado em Recursos Florestais, na área de Silvicultura e Manejo Florestal, na Escola Superior de Agricultura "Luiz de Queiroz" (ESALQ), pertencente à Universidade de São Paulo (USP). Possui Doutorado em Engenharia Florestal, na área de Manejo Florestal, por meio da Universidade Federal do Paraná (UFPR). Atua na área de Recursos Florestais, com ênfase Manejo de Florestas Plantadas, sob os temas: Determinação da Biomassa Florestal, Modelagem Mista, Funções de Afilamento e Sortimento Florestal.

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Published

2022-01-03

How to Cite

Pertille, C. T., & Nicoletti, M. F. (2022). VOLUMETRIC MODELING OF Pinus taeda L. FROM ORBITAL IMAGES. BIOFIX Scientific Journal, 7(1), 53–60. https://doi.org/10.5380/biofix.v7i1.82066

Issue

Vol. 7 No. 1 (2022)

Section

Artigos

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