VOLUMETRIC MODELING OF Pinus taeda L. FROM ORBITAL IMAGES - Pertille, Carla Talita; Nicoletti, Marcos Felipe (Biofix Scientific Journal, 2022)
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.