NDVI from satellite images to estimate LiDAR-derived geometric and structural parameters in super-intensive almond orchards
2021
Martínez Casasnovas, José Antonio | Llorens Calveras, Jordi | Sandonís Pozo, Leire | Escolà i Agustí, Alexandre | Arnó Satorra, Jaume
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.
Показать больше [+] Меньше [-]This work was funded by the Spanish Ministry of Science, Innovation and Universities through the project PAgFRUIT (RTI2018-094222-B-I00). The authors thank the Copernicus program for the use of Sentinel-2 images and Planet Labs Inc. for the use of PlanetScope images under the Educational and Research License agreement with the Universitat de Lleida.
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Эту запись предоставил Universitat de Lleida