Estimation of geometric and structural parameters in a super-intensive almond (Prunus dulcis) orchard from multispectral vegetation indices derived from UAV-based imagery
Loading...
Date
2021
Authors
Llorens Calveras, Jordi
Escolà i Agustí, Alexandre
Casañas, E.
Rosell Polo, Joan Ramon
Arnó Satorra, Jaume
Martínez Casasnovas, José Antonio
Other authors
Impact
Export
Share
Journal Title
Journal ISSN
Volume Title
Abstract
Canopy geometric and structural parameters in a super-intensive almond (Prunus dulcis) orchard were estimated from multispectral vegetation indices from very high-resolution UAV images (0.07 m/pixel). As ground truth data, the canopy geometric and structural parameters were extracted from a 3D LiDAR point cloud. These data were summarized every 0.5 m along the tree rows. The vegetation indices CCCI, NDRE, NDVI, GNDVI and WDRVI were calculated and summarized at the same points as the LiDAR data. The highest correlations (R>0.70) were obtained between the NDVI and the maximum width and the cross-sectional area. The porosity was negatively correlated (R=-0.59) with the NDVI. This research opens the opportunity of using remotely sensed vegetation indices to estimate canopy geometric and structural parameters in addition to vigour for precise canopy management.
Citation
Journal or Serie
Stafford, J.V. (ed.), Precision Agriculture’21. Wageningen Academic Publishers, Amsterdam (The Netherlands), pp 129-135. https://doi.org/10.3920/978-90-8686-916-9