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Título
A Handheld Laser-Scanning-Based Methodology for Monitoring Tree Growth in Chestnut Orchards
Autor
Facultad/Centro
Área de conocimiento
Título de la revista
Sensors
Número de la revista
6
Datos de la obra
Pereira-Obaya, D.; Cabo, C.; Ordóñez, C.; Rodríguez-Pérez, J.R. A Handheld Laser-Scanning-Based Methodology for Monitoring Tree Growth in Chestnut Orchards. Sensors 2024, 24, 1717. https://doi.org/10.3390/s24061717
Editor
MDPI
Fecha
2024
ISSN
1424-8220
Zusammenfassung
[EN] Chestnut and chestnut byproducts are of worldwide interest, so there is a constant need to develop faster and more accurate monitoring techniques. Recent advances in simultaneous localization and mapping (SLAM) algorithms and user accessibility have led to increased use of handheld mobile laser scanning (HHLS) in precision agriculture. We propose a tree growth monitoring methodology, based on HHLS point cloud processing, that calculates the length of branches through spatial discretization of the point cloud for each tree. The methodology was tested by comparing two point clouds collected almost simultaneously for each of a set of sweet chestnut trees. The results obtained indicated that our HHLS method was reliable and accurate in efficiently monitoring sweet chestnut tree growth. The same methodology was used to calculate the growth of the same set of trees over 37 weeks (from spring to winter). Differences in week 0 and week 37 scans showed an approximate mean growth of 0.22 m, with a standard deviation of around 0.16 m reflecting heterogeneous tree growth.
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SI
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Versión CC 4.0 del artículo https://doi.org/10.3390/s24061717