NDVI from satellite images to estimate LiDAR-derived geometric and structural parameters in super-intensive almond orchards
The present work tries to bridge a gap about the estimation of geometric and structural orchard parameters (LiDAR-derived) from vegetation indices from satellites. The maximum height and width, the cross-sectional area and the porosity were measured along the rows in a super-intensive almond (Prunus dulcis) orchard every 0.5 m by means of a Velodyne VLP16 LiDAR sensor. These parameters were interpolated to the pixel centroids of PlanetScope and Sentinel-2 and correlated with the normalized difference vegetation index (NDVI) from both platforms. The highest correlations were obtained between the NDVI of PlanetScope images and the cross-sectional area of the almond trees (R=0.72) and with the maximum width of the cross-sections (R=0.71). The results can be useful to estimate important canopy geometric parameters for site-specific management of orchards.
Journal or Serie
Stafford, J.V. (ed.), Precision Agriculture’21. Wageningen Academic Publishers, Amsterdam (The Netherlands), pp 567-573. https://doi.org/10.3920/978-90-8686-916-9