Exploring 3D Reconstruction Methods for Assessing Biometric Parameters in Avocado Trees
[EN] Within the framework of the current Common Agricultural Policy, resource reduction is pivotal for achieving the goal outlined in the Farm to Fork Strategy by the European Commission. Adequate fertilisation plans are necessary to fulfil these objectives, adapting to plant needs throughout their...
| Autores: | , , , , , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2025 |
| País: | España |
| Institución: | Universitat Politècnica de València (UPV) |
| Repositorio: | RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia |
| Idioma: | inglés |
| OAI Identifier: | oai:riunet.upv.es:10251/230002 |
| Acceso en línea: | https://riunet.upv.es/handle/10251/230002 |
| Access Level: | acceso abierto |
| Palabra clave: | LiDAR Photogrammetry Point clouds Precision agriculture |
| Sumario: | [EN] Within the framework of the current Common Agricultural Policy, resource reduction is pivotal for achieving the goal outlined in the Farm to Fork Strategy by the European Commission. Adequate fertilisation plans are necessary to fulfil these objectives, adapting to plant needs throughout their growth cycle. To establish these needs, quantifying vegetative growth, based on biometric parameters, between key phenological stages is crucial. These parameters can be derived from 3D point clouds acquired via technological systems such as LiDAR or photogrammetry, enabling precise measurements. This work aimed to develop automated and non-destructive methods to assess these biometric parameters in avocado trees at different growth stages from point clouds obtained using two 3D techniques: a LiDAR sensor and photogrammetry. Measurements were conducted in an experimental avocado orchard in Moncada (Valencia), Spain, across three phenological stages from June to November 2023. Automatic measurements were taken using sensors integrated into a scouting robot, and traditional statistical methods were employed to compare manually obtained data with scanned data. Preliminary results demonstrated the progression of biometric parameters measured by LiDAR and photogrammetry across different developmental stages, showing a significant correlation between manual measures and scanned data. Both technologies performed similarly, particularly in measuring tree volume from point clouds. These findings highlight the potential of LiDAR and photogrammetry in accurately assessing biometric parameters in agricultural settings, supporting sustainable farming practices. |
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