Drones como ferramenta de gestão florestal: desempenho dos índices IRAV (Índice Resistente à Atmosfera na Região Visível) e ITV (Índice Triangular Verde) na estimativa de volume de Eucalyptus.
This work aimed to associate reflectance data of RGB aerial photographs captured by drone and to comcant them with wood volume values using two vegetation indices (IRAV and ITV). The study was conducted in Macaíba-RN in the experimental eucalyptus plantation that is part of the TECHS-UFRN researc...
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| Formato: | bachelorThesis |
| Idioma: | pt_BR |
| Publicado em: |
Universidade Federal do Rio Grande do Norte
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| Endereço do item: | https://repositorio.ufrn.br/handle/123456789/48758 |
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| Resumo: | This work aimed to associate reflectance data of RGB aerial photographs
captured by drone and to comcant them with wood volume values using two vegetation
indices (IRAV and ITV). The study was conducted in Macaíba-RN in the experimental
eucalyptus plantation that is part of the TECHS-UFRN research program. The captured
photographs were processed using the QGIS software, generating a map for each
index evaluated. To compare with the volume values of the trees of each plot, a value
of the index of the average of the pixels in the radius of 1.5 m of each tree was
generated, which, after the flight, were felled for cubation. The correlation analysis was
performed by multivariable linear regression, with the index value being the dependent
variable, and the volume value being the independent variable. The IRAV index
showed the highest correlation with the volume values of the trees, accounting better
statistically than the ITV index, especially the C3 plot (E. grandis x E. camaldulensis),
was the one that presented the best correlation with volume (m³), with a value of r =
0.60. The ITV index showed lower correlation with the volume of the trees, obtaining a
significant difference between the two indexes evaluated. Nonlinear regression
analysis was performed where regression models that best represented the indices in
each genotype were chosen by comparison by comparison via AIC. The chosen
regressions were applied to the index map for comparison with the volumetric
production values (m³/ago) through the segmentation process. The two indices
showed a positive relationship with the values estimated by the direct method, showing
the highest volumetric production in the most densespacings. The results obtained with
this study show the potential of the use of drones monitoring tool to estimate forest
productivity, through regression analysis of vegetation indices obtained by aerophotos. |
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