NDVI from satellite images to estimate LiDAR-derived geometric and structural parameters in super-intensive almond orchards
dc.contributor.author | Martínez Casasnovas, José Antonio | |
dc.contributor.author | Llorens Calveras, Jordi | |
dc.contributor.author | Sandonís Pozo, Leire | |
dc.contributor.author | Escolà i Agustí, Alexandre | |
dc.contributor.author | Arnó Satorra, Jaume | |
dc.date.accessioned | 2022-11-03T09:35:14Z | |
dc.date.available | 2022-11-03T09:35:14Z | |
dc.date.issued | 2021 | |
dc.description.abstract | 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. | ca_ES |
dc.description.sponsorship | 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. | ca_ES |
dc.identifier.doi | https://doi.org/10.3920/978-90-8686-916-9_68 | |
dc.identifier.uri | http://hdl.handle.net/10459.1/84063 | |
dc.language.iso | eng | ca_ES |
dc.relation | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-094222-B-I00/ES/TECNOLOGIAS DE AGRICULTURA DE PRECISION PARA OPTIMIZAR EL MANEJO DEL DOSEL FOLIAR Y LA PROTECCION FITOSANITARIA SOSTENIBLE EN PLANTACIONES FRUTALES/ | ca_ES |
dc.relation.haspart | 13th European Conference on Precision Agriculture, July 19-22, 2021, Budapest, Hungary | |
dc.relation.isformatof | Versió preprint del document publicat a https://doi.org/10.3920/978-90-8686-916-9_68 | ca_ES |
dc.relation.ispartof | 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 | ca_ES |
dc.rights | © José Antonio Martínez Casasnovas et al., 2021 | ca_ES |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | ca_ES |
dc.subject | LiDAR | ca_ES |
dc.subject | Geometric parameters | ca_ES |
dc.subject | Almond orchards | ca_ES |
dc.subject | NDVI | ca_ES |
dc.subject | Sentinel-2 | ca_ES |
dc.subject | PlanetScope | ca_ES |
dc.title | NDVI from satellite images to estimate LiDAR-derived geometric and structural parameters in super-intensive almond orchards | ca_ES |
dc.type | info:eu-repo/semantics/conferenceObject | ca_ES |
dc.type.version | info:eu-repo/semantics/submittedVersion | ca_ES |