TY - JOUR
T1 - Methodology for measuring dendrometric parameters in a mediterranean forest with UAVs flying inside forest
AU - Greco, Roberto
AU - Barca, Emanuele
AU - Raumonen, Pasi
AU - Persia, Manuela
AU - Tartarino, Patrizia
N1 - Funding Information:
The present study has been funded by the following projects: 1.“Studio sperimentale della pianificazione assestamentale avanzata relativa ai complessi forestali di proprietà della Regione Puglia” managed and funded by A.R.I.F. Apulia Region (Regional Agency for Irrigation and Forestry activities of the Apulia Region). 2.“Metodi innovativi per la stima del volume legnoso ritraibile dai tagli boschivi in Puglia” managed and funded by Regione Puglia - Sezione Gestione Sostenibile e Tutela delle Risorse Forestali e Naturali. Dipartimento Agricoltura, Sviluppo Rurale e Ambientale Dipartimento di Scienze Agro-Ambientali e Territoriali dell'Università degli Studi di Bari Aldo Moro (DiSAAT)
Publisher Copyright:
© 2023 The Author(s)
PY - 2023/8
Y1 - 2023/8
N2 - Accurate field measurements of tree morphological features are essential for effective forest inventory and the sustainable management of forest resources. Traditional methods involve time-consuming and expensive tree-by-tree measurements conducted by specialized technicians, which can lead to subjective measurement errors. To address these limitations, advanced sensor technologies have garnered attention in recent years. Terrestrial laser scanning (TLS) has been widely employed due to its high precision in deriving tree attributes at the plot level. However, TLS has certain drawbacks, including high acquisition costs, limited portability, and the requirement for specialized software and expertise. As alternatives, aerial photogrammetry and computer vision algorithms have emerged to obtain high-resolution 3D measurements of forest vegetation. This study proposes a novel approach utilizing a small drone under the forest canopy to estimate biometric parameters such as trunk diameter at various heights and circumference. By joining the capabilities of drones with the structure-from-motion approach, this study presents a promising solution for cost-effective and accurate estimation of biometric parameters in forest inventories. Moreover, the results demonstrate superior accuracy compared to those reported in previous studies with improvements up to one order of magnitude.
AB - Accurate field measurements of tree morphological features are essential for effective forest inventory and the sustainable management of forest resources. Traditional methods involve time-consuming and expensive tree-by-tree measurements conducted by specialized technicians, which can lead to subjective measurement errors. To address these limitations, advanced sensor technologies have garnered attention in recent years. Terrestrial laser scanning (TLS) has been widely employed due to its high precision in deriving tree attributes at the plot level. However, TLS has certain drawbacks, including high acquisition costs, limited portability, and the requirement for specialized software and expertise. As alternatives, aerial photogrammetry and computer vision algorithms have emerged to obtain high-resolution 3D measurements of forest vegetation. This study proposes a novel approach utilizing a small drone under the forest canopy to estimate biometric parameters such as trunk diameter at various heights and circumference. By joining the capabilities of drones with the structure-from-motion approach, this study presents a promising solution for cost-effective and accurate estimation of biometric parameters in forest inventories. Moreover, the results demonstrate superior accuracy compared to those reported in previous studies with improvements up to one order of magnitude.
KW - Accuracy analysis
KW - Dendrometric parameters
KW - Pix4D
KW - Terrestrial laser scanner
KW - Terrestrial structure from motion photogrammetry
KW - UAV
U2 - 10.1016/j.jag.2023.103426
DO - 10.1016/j.jag.2023.103426
M3 - Article
AN - SCOPUS:85165250909
SN - 1569-8432
VL - 122
JO - International Journal of Applied Earth Observation and Geoinformation
JF - International Journal of Applied Earth Observation and Geoinformation
M1 - 103426
ER -