Ground-based 3D LiDAR; Point clouds partition; Automatic partition; Canopy dimensions; Variable rate; Crop protection
Abstract :
[en] The 3D characterisation of individual vine canopies with a LiDAR sensor requires point
cloud classification. A Bayesian point cloud classification algorithm (BPCC) is proposed that
combines an automatic filtering method (AFM) and a classification method based on
clustering to process LiDAR data. Data were collected on several grape varieties with two
different modes of training. To evaluate the quality of the BPCC algorithm and its influence
on the estimation of canopy parameters (height and width), it was compared to an expert
manual method and to an established semi-automatic research method requiring interactive
pre-treatment (PROTOLIDAR). The results showed that the AFM filtering was similar
to the expert manual method and retained on average 9% more points than the PROTOLIDAR
method over the whole growing season. Estimates of vegetation height and width
that were obtained from classification of the AFM-filtered LiDAR data were strongly
correlated with estimates made by the PROTOLIDAR method (R2 ¼ 0.94 and 0.89, respectively).
The classification algorithm was most effective if its parameters were permitted to
be variable through the season. Optimal values for classification parameters were established
for both height and width at different phenological stages. On the whole, the results
demonstrated that although the BPCC algorithm operates at a higher level of automation
than PROTOLIDAR, the estimates of canopy dimensions in the vineyards were equivalent.
BPCC enables the possibility to adjust the spray rate according to local vegetative characteristics
in an automated way.
Lebeau, Frédéric ; Université de Liège - ULiège > Département GxABT > Biosystems Dynamics and Exchanges
Taylor, James
Language :
English
Title :
An algorithm to automate the filtering and classifying of 2D LiDAR data for site-specific estimations of canopy height and width in vineyards
Publication date :
2020
Journal title :
Biosystems Engineering
ISSN :
1537-5110
eISSN :
1537-5129
Publisher :
Elsevier, Atlanta, Georgia
Volume :
200
Pages :
450-465
Peer reviewed :
Peer Reviewed verified by ORBi
Name of the research project :
Experimental and statistical modeling of relations between morphological characteristics of grapevine and spraying deposits: application to precision agriculture
Funding text :
#DigitAg and French Vine and Wine Institute and Agricultural Technical Coordination Association
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