UAV Flight Orientation and Height Influence on Tree Crown Segmentation in Agroforestry Systems
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...
| Autores principales: | , , , , , , , , , , , |
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| Formato: | Artículo |
| Lenguaje: | Inglés |
| Publicado: |
Forests
2026
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| Acceso en línea: | http://hdl.handle.net/20.500.12955/2994 https://doi.org/10.3390/f17010087 |
| _version_ | 1855490128115400704 |
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| author | Baselly Villanueva, Juan Rodrigo Fernández Sandoval, Andrés Pinedo Freyre, Sergio Fernando Salazar Hinostroza, Evelin Judith Cárdenas Rengifo, Gloria Patricia Puerta, Ronald Huanca Diaz, José Ricardo Tuesta Cometivos, Gino Anthony Vallejos Torres, Geomar Goycochea Casas, Gianmarco Álvarez Álvarez, Pedro Ismail, Zool Hilmi |
| author_browse | Baselly Villanueva, Juan Rodrigo Cárdenas Rengifo, Gloria Patricia Fernández Sandoval, Andrés Goycochea Casas, Gianmarco Huanca Diaz, José Ricardo Ismail, Zool Hilmi Pinedo Freyre, Sergio Fernando Puerta, Ronald Salazar Hinostroza, Evelin Judith Tuesta Cometivos, Gino Anthony Vallejos Torres, Geomar Álvarez Álvarez, Pedro |
| author_facet | Baselly Villanueva, Juan Rodrigo Fernández Sandoval, Andrés Pinedo Freyre, Sergio Fernando Salazar Hinostroza, Evelin Judith Cárdenas Rengifo, Gloria Patricia Puerta, Ronald Huanca Diaz, José Ricardo Tuesta Cometivos, Gino Anthony Vallejos Torres, Geomar Goycochea Casas, Gianmarco Álvarez Álvarez, Pedro Ismail, Zool Hilmi |
| author_sort | Baselly Villanueva, Juan Rodrigo |
| collection | Repositorio INIA |
| description | 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. |
| format | Artículo |
| id | INIA2994 |
| institution | Institucional Nacional de Innovación Agraria |
| language | Inglés |
| publishDate | 2026 |
| publishDateRange | 2026 |
| publishDateSort | 2026 |
| publisher | Forests |
| publisherStr | Forests |
| record_format | dspace |
| spelling | INIA29942026-01-16T15:51:15Z UAV Flight Orientation and Height Influence on Tree Crown Segmentation in Agroforestry Systems Baselly Villanueva, Juan Rodrigo Fernández Sandoval, Andrés Pinedo Freyre, Sergio Fernando Salazar Hinostroza, Evelin Judith Cárdenas Rengifo, Gloria Patricia Puerta, Ronald Huanca Diaz, José Ricardo Tuesta Cometivos, Gino Anthony Vallejos Torres, Geomar Goycochea Casas, Gianmarco Álvarez Álvarez, Pedro Ismail, Zool Hilmi Calycophyllum spruceanum Cedrelinga cateniformis Virola pavonis crown forest monitoring Remote sensing YOLO Corona Monitoreo forestal Teledetección https://purl.org/pe-repo/ocde/ford#4.01.06 Sistema agroforestal; Agroforestry systems; Teledetección; Remote sensing; Vehículo aéreo no tripulado; Unmanned aerial vehicles; Árbol forestal; Forest tres; Detección; Detection 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. This research was financed by the National Forestry Program of the National Institute for Agrarian Innovation and the “Programa Presupuestal 121—Mejora de la articulación de los pequeños productores a los mercados”. 2026-01-15T22:20:47Z 2026-01-15T22:20:47Z 2026-01-09 info:eu-repo/semantics/article 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., Goycochea Casas, 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 1999-4907 http://hdl.handle.net/20.500.12955/2994 https://doi.org/10.3390/f17010087 eng urn:issn: 1999-4907 MDPI info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by/4.0/ application/pdf application/pdf Forests CH Instituto Nacional de Innovación Agraria Repositorio Institucional - INIA |
| spellingShingle | Calycophyllum spruceanum Cedrelinga cateniformis Virola pavonis crown forest monitoring Remote sensing YOLO Corona Monitoreo forestal Teledetección https://purl.org/pe-repo/ocde/ford#4.01.06 Sistema agroforestal; Agroforestry systems; Teledetección; Remote sensing; Vehículo aéreo no tripulado; Unmanned aerial vehicles; Árbol forestal; Forest tres; Detección; Detection Baselly Villanueva, Juan Rodrigo Fernández Sandoval, Andrés Pinedo Freyre, Sergio Fernando Salazar Hinostroza, Evelin Judith Cárdenas Rengifo, Gloria Patricia Puerta, Ronald Huanca Diaz, José Ricardo Tuesta Cometivos, Gino Anthony Vallejos Torres, Geomar Goycochea Casas, Gianmarco Álvarez Álvarez, Pedro Ismail, Zool Hilmi UAV Flight Orientation and Height Influence on Tree Crown Segmentation in Agroforestry Systems |
| title | UAV Flight Orientation and Height Influence on Tree Crown Segmentation in Agroforestry Systems |
| title_full | UAV Flight Orientation and Height Influence on Tree Crown Segmentation in Agroforestry Systems |
| title_fullStr | UAV Flight Orientation and Height Influence on Tree Crown Segmentation in Agroforestry Systems |
| title_full_unstemmed | UAV Flight Orientation and Height Influence on Tree Crown Segmentation in Agroforestry Systems |
| title_short | UAV Flight Orientation and Height Influence on Tree Crown Segmentation in Agroforestry Systems |
| title_sort | uav flight orientation and height influence on tree crown segmentation in agroforestry systems |
| topic | Calycophyllum spruceanum Cedrelinga cateniformis Virola pavonis crown forest monitoring Remote sensing YOLO Corona Monitoreo forestal Teledetección https://purl.org/pe-repo/ocde/ford#4.01.06 Sistema agroforestal; Agroforestry systems; Teledetección; Remote sensing; Vehículo aéreo no tripulado; Unmanned aerial vehicles; Árbol forestal; Forest tres; Detección; Detection |
| url | http://hdl.handle.net/20.500.12955/2994 https://doi.org/10.3390/f17010087 |
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