Universitat de Lleida
    • English
    • català
    • español
  • English 
    • English
    • català
    • español
  • Login
Repositori Obert UdL
View Item 
  •   Home
  • Recerca
  • Grup de Recerca en AgròTICa i Agricultura de Precisió
  • Articles publicats (Grup de Recerca en AgròTICa i Agricultura de Precisió)
  • View Item
  •   Home
  • Recerca
  • Grup de Recerca en AgròTICa i Agricultura de Precisió
  • Articles publicats (Grup de Recerca en AgròTICa i Agricultura de Precisió)
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

Leaf area index estimation in vineyards using a ground-based LiDAR scanner

Thumbnail
View/Open
Postprint (1.629Mb)
Issue date
2013
Author
Arnó Satorra, Jaume
Escolà i Agustí, Alexandre
Vallès Petit, Josep Maria
Llorens Calveras, Jordi
Sanz Cortiella, Ricardo
Masip Vilalta, Joan
Palacín Roca, Jordi
Rosell Polo, Joan Ramon
Suggested citation
Arnó Satorra, Jaume; Escolà i Agustí, Alexandre; Vallès Petit, Josep Maria; Llorens Calveras, Jordi; Sanz Cortiella, Ricardo; Masip Vilalta, Joan; ... Rosell Polo, Joan Ramon. (2013) . Leaf area index estimation in vineyards using a ground-based LiDAR scanner. Precision Agriculture, 2013, vol. 14, núm. 3, p. 290-306. https://doi.org/10.1007/s11119-012-9295-0.
Impact


Web of Science logo    citations in Web of Science

Scopus logo    citations in Scopus

Google Scholar logo  Google Scholar
Share
Export to Mendeley
Metadata
Show full item record
Abstract
Estimation of grapevine vigour using mobile proximal sensors can provide an indirect method for determining grape yield and quality. Of the various indexes related to the characteristics of grapevine foliage, the leaf area index (LAI) is probably the most widely used in viticulture. To assess the feasibility of using light detection and ranging (LiDAR) sensors for predicting the LAI, several field trials were performed using a tractor-mounted LiDAR system. This system measured the crop in a transverse direction along the rows of vines and geometric and structural parameters were computed. The parameters evaluated were the height of the vines (H), the cross-sectional area (A), the canopy volume (V) and the tree area index (TAI). This last parameter was formulated as the ratio of the crop estimated area per unit ground area, using a local Poisson distribution to approximate the laser beam transmission probability within vines. In order to compare the calculated indexes with the actual values of LAI, the scanned vines were defoliated to obtain LAI values for different row sections. Linear regression analysis showed a good correlation (R 2 = 0.81) between canopy volume and the measured values of LAI for 1 m long sections. Nevertheless, the best estimation of the LAI was given by the TAI (R 2 = 0.92) for the same length, confirming LiDAR sensors as an interesting option for foliage characterization of grapevines. However, current limitations exist related to the complexity of data process and to the need to accumulate a sufficient number of scans to adequately estimate the LAI.
URI
http://hdl.handle.net/10459.1/49362
DOI
https://doi.org/10.1007/s11119-012-9295-0
Is part of
Precision Agriculture, 2013, vol. 14, núm. 3, p. 290-306
European research projects
Collections
  • Articles publicats (Grup de Recerca en AgròTICa i Agricultura de Precisió) [116]
  • Articles publicats (Enginyeria Agroforestal) [384]
  • Articles publicats (Informàtica i Enginyeria Industrial) [990]
  • Publicacions de projectes de recerca del Plan Nacional [2958]
  • Articles publicats (Agrotecnio Center) [1330]

Contact Us | Send Feedback | Legal Notice
© 2023 BiD. Universitat de Lleida
Metadata subjected to 
 

 

Browse

All of the repositoryCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

Statistics

View Usage Statistics

D'interès

Política institucional d'accés obertDiposita les teves publicacionsDiposita dades de recercaSuport a la recerca

Contact Us | Send Feedback | Legal Notice
© 2023 BiD. Universitat de Lleida
Metadata subjected to