TY - JOUR
T1 - Real-time approaches for characterization of fully and partially scanned canopies in groves
AU - Auat Cheein, Fernando A.
AU - Guivant, José
AU - Sanz, Ricardo
AU - Escolà, Alexandre
AU - Yandún, Francisco
AU - Torres-Torriti, Miguel
AU - Rosell-Polo, Joan R.
N1 - Funding Information:
The authors would like to thank to CONICYT (Chile): FONDECYT Grant 1140575 and Basal Grant FB0008 . Also, this research was partially funded by the Spanish Ministry of Science and Innovation and by the European Union through the FEDER funds (projects Optidosa-AGL2007-66093-C04-03 and Safespray-AGL2010-22304-C04-03).
Publisher Copyright:
© 2015 Elsevier B.V.
PY - 2015/10
Y1 - 2015/10
N2 - Efficient information management in orchard characterization leads to more efficient agricultural processes. In this brief, a set of computational geometry methods are presented and evaluated for orchard characterization; in particular, for the estimation of canopy volume and shape in groves and orchards using a LiDAR (Light Detection And Ranging) sensor mounted on an agricultural service unit. The proposed approaches were evaluated and validated in the field, showing they are convergent in the estimation process and that they are able to estimate the crown volume for fully scanned canopies in real time; for partially observed tree crowns, accuracy decreases up to 30% (the worst case). The latter is the major contribution of this brief since it implies that the automated service unit does not need to cover all alley-ways for an accurate modeling of the orchard, thus saving valuable resources.
AB - Efficient information management in orchard characterization leads to more efficient agricultural processes. In this brief, a set of computational geometry methods are presented and evaluated for orchard characterization; in particular, for the estimation of canopy volume and shape in groves and orchards using a LiDAR (Light Detection And Ranging) sensor mounted on an agricultural service unit. The proposed approaches were evaluated and validated in the field, showing they are convergent in the estimation process and that they are able to estimate the crown volume for fully scanned canopies in real time; for partially observed tree crowns, accuracy decreases up to 30% (the worst case). The latter is the major contribution of this brief since it implies that the automated service unit does not need to cover all alley-ways for an accurate modeling of the orchard, thus saving valuable resources.
KW - Agricultural robotics
KW - Crown volume
KW - LiDAR sensor
KW - Mobile terrestrial laser scanner
UR - http://www.scopus.com/inward/record.url?scp=84944043446&partnerID=8YFLogxK
U2 - 10.1016/j.compag.2015.09.017
DO - 10.1016/j.compag.2015.09.017
M3 - Article
AN - SCOPUS:84944043446
SN - 0168-1699
VL - 118
SP - 361
EP - 371
JO - Computers and Electronics in Agriculture
JF - Computers and Electronics in Agriculture
ER -
