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Volume 17
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10.3390/f17010087
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This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

UAV Flight Orientation and Height Influence on Tree Crown Segmentation in Agroforestry Systems

by
Juan Rodrigo Baselly-Villanueva
1,*,
Andrés Fernández-Sandoval
1,
Sergio Fernando Pinedo Freyre
1,
Evelin Judith Salazar-Hinostroza
2,
Gloria Patricia Cárdenas-Rengifo
3,
Ronald Puerta
4,
José Ricardo Huanca Diaz
5,
Gino Anthony Tuesta Cometivos
5,
Geomar Vallejos-Torres
6,
Gianmarco Goycochea Casas
7,
Pedro Álvarez-Álvarez
8,* and
Zool Hilmi Ismail
9
1
Estación Experimental Agraria San Roque, Instituto Nacional de Innovación Agraria (INIA), Calle San Roque 209, Loreto 16430, Peru
2
Dirección de Desarrollo Tecnológico Agrario, Instituto Nacional de Innovación Agraria (INIA), Av. La Molina 1981, Lima 15024, Peru
3
Estación Experimental Agraria Pucallpa, Instituto Nacional de Innovación Agraria (INIA), Carretera Federico Basadre Km 4200, Pucallpa 25004, Peru
4
Universidad Nacional Agraria de la Selva, Tingo Maria, Huánuco 100601, Peru
5
Universidad Nacional de la Amazonía Peruana (UNAP), Calle Pevas N° 548, Iquitos 16002, Peru
6
Universidad Nacional de San Martín, Jr. Maynas No 177, Tarapoto 22200, Peru
7
Department of Forest Engineering, Federal University of Viçosa, Viçosa 36570-900, MG, Brazil
8
Department of Organisms and Systems Biology, Polytechnic School of Mieres, University of Oviedo, E-33600 Mieres, Asturias, Spain
9
Center for Artificial Intelligence and Robotics, Universiti Teknologi Malaysia, Jalan Sultan Yahya Petra, Kuala Lumpur 54100, Malaysia
*
Authors to whom correspondence should be addressed.
Forests 2026, 17(1), 87; https://doi.org/10.3390/f17010087
Submission received: 10 November 2025 / Revised: 4 January 2026 / Accepted: 7 January 2026 / Published: 9 January 2026
(This article belongs to the Special Issue Smart Forest Inventory, Management and Planning: Intelligent Technologies and Their Applications)
Versions Notes

Abstract

Precise crown segmentation is essential for assessing structure, competition, and productivity in agroforestry systems, but delineation is challenging due to canopy heterogeneity and variability in aerial imagery. This study analyzes how flight height and orientation affect segmentation accuracy in an agroforestry system of the Peruvian Amazon, using RGB images acquired with a DJI Mavic Mini 3 Pro UAV and the instance-segmentation models YOLOv8 and YOLOv11. Four flight heights (40, 50, 60, and 70 m) and two orientations (parallel and transversal) were analyzed in an agroforestry system composed of Cedrelinga cateniformis (Ducke) Ducke, Calycophyllum spruceanum (Benth.) Hook.f. ex K.Schum., and Virola pavonis (A.DC.) A.C. Sm. Results showed that a flight height of 60 m provided the highest delineation accuracy (F1 ≈ 0.88 for YOLOv8 and 0.84 for YOLOv11), indicating an optimal balance between resolution and canopy coverage. Although YOLOv8 achieved the highest precision under optimal conditions, it exhibited greater variability with changes in flight geometry. In contrast, YOLOv11 showed a more stable and robust performance, with generalization gaps below 0.02, reflecting a stronger adaptability to different acquisition conditions. At the species level, vertical position and crown morphological differences (Such as symmetry, branching angle, and bifurcation level) directly influenced detection accuracy. Cedrelinga cateniformis displayed dominant and asymmetric crowns; Calycophyllum spruceanum had narrow, co-dominant crowns; and Virola pavonis exhibited symmetrical and intermediate crowns. These traits were associated with the detection and confusion patterns observed across the models, highlighting the importance of crown architecture in automated segmentation and the potential of UAVs combined with YOLO algorithms for the efficient monitoring of tropical agroforestry systems.
Keywords: Calycophyllum spruceanum; Cedrelinga cateniformis; Virola pavonis; crown; forest monitoring; remote sensing; YOLO Calycophyllum spruceanum; Cedrelinga cateniformis; Virola pavonis; crown; forest monitoring; remote sensing; YOLO

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MDPI and ACS Style

Baselly-Villanueva, J.R.; Fernández-Sandoval, A.; Pinedo Freyre, S.F.; Salazar-Hinostroza, E.J.; Cárdenas-Rengifo, G.P.; Puerta, R.; Huanca Diaz, J.R.; Tuesta Cometivos, G.A.; Vallejos-Torres, G.; Casas, G.G.; et al. UAV Flight Orientation and Height Influence on Tree Crown Segmentation in Agroforestry Systems. Forests 2026, 17, 87. https://doi.org/10.3390/f17010087

AMA Style

Baselly-Villanueva JR, Fernández-Sandoval A, Pinedo Freyre SF, Salazar-Hinostroza EJ, Cárdenas-Rengifo GP, Puerta R, Huanca Diaz JR, Tuesta Cometivos GA, Vallejos-Torres G, Casas GG, et al. UAV Flight Orientation and Height Influence on Tree Crown Segmentation in Agroforestry Systems. Forests. 2026; 17(1):87. https://doi.org/10.3390/f17010087

Chicago/Turabian Style

Baselly-Villanueva, Juan Rodrigo, Andrés Fernández-Sandoval, Sergio Fernando Pinedo Freyre, Evelin Judith Salazar-Hinostroza, Gloria Patricia Cárdenas-Rengifo, Ronald Puerta, José Ricardo Huanca Diaz, Gino Anthony Tuesta Cometivos, Geomar Vallejos-Torres, Gianmarco Goycochea Casas, and et al. 2026. "UAV Flight Orientation and Height Influence on Tree Crown Segmentation in Agroforestry Systems" Forests 17, no. 1: 87. https://doi.org/10.3390/f17010087

APA Style

Baselly-Villanueva, J. R., Fernández-Sandoval, A., Pinedo Freyre, S. F., Salazar-Hinostroza, E. J., Cárdenas-Rengifo, G. P., Puerta, R., Huanca Diaz, J. R., Tuesta Cometivos, G. A., Vallejos-Torres, G., Casas, G. G., Álvarez-Álvarez, P., & Ismail, Z. H. (2026). UAV Flight Orientation and Height Influence on Tree Crown Segmentation in Agroforestry Systems. Forests, 17(1), 87. https://doi.org/10.3390/f17010087

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