Remote sensing techniques have emerged as a highly efficient means for characterizing crop conditions and forecasting water needs. This study, conducted over 20 months, from January 2021 to October 2022, investigates the correlation between the Normalized Difference Vegetation Index (NDVI), derived from data captured by a MicaSense RedEdge multispectral camera mounted on an unmanned aerial vehicle, and two growth parameters such as Canopy Cover (CC) and the Leaf Area Index (LAI). The research was carried out in a 2000m2 plot in the northwest of Tenerife (Canary Islands, Spain), cultivated with bananas from the Cavendish group variety “Dwarf” local selection “Brier”. The leaf emission rate, leaf surface area and CC were determined throughout the crop cycle. The NDVI proved to be an effective tool for determining the CC, showing a correlation with an R2 value greater than 0.7. However, when considering the threedimensional aspect of the LAI, obtained weekly through manual measurements of all leaves (not solely those visible from a zenithal perspective), the correlation between LAI and NDVI was comparatively weaker, with an R2 value of about 0.2. The variations in the CC observed agree with the periods of development, harvest and plant cutting, although there is a moderate correlation between the CC and LAI (R2=0.40).
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