High-Throughput 3-D Monitoring of Agricultural-Tree Plantations with Unmanned Aerial Vehicle (UAV) Technology

The geometric features of agricultural trees such as canopy area, tree height and crown volume provide useful information about plantation status and crop production. However, these variables are mostly estimated after a time-consuming and hard field work and applying equations that treat the trees...

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Bibliographic Details
Published in:PloS one 2015-06, Vol.10 (6), p.e0130479-e0130479
Main Authors: Torres-Sánchez, Jorge, López-Granados, Francisca, Serrano, Nicolás, Arquero, Octavio, Peña, José M
Format: Article
Language:English
Subjects:
Agricultural management
Agricultural production
Agricultural vehicles
Agriculture
Crop management
Crop production
Crops
Environmental management
High-Throughput Screening Assays
Image analysis
Image processing
Land use
Mathematical models
Plantations
Precision farming
Remote Sensing Technology
Remotely piloted vehicles
Technology
Trees
Unmanned aerial vehicles
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Summary:The geometric features of agricultural trees such as canopy area, tree height and crown volume provide useful information about plantation status and crop production. However, these variables are mostly estimated after a time-consuming and hard field work and applying equations that treat the trees as geometric solids, which produce inconsistent results. As an alternative, this work presents an innovative procedure for computing the 3-dimensional geometric features of individual trees and tree-rows by applying two consecutive phases: 1) generation of Digital Surface Models with Unmanned Aerial Vehicle (UAV) technology and 2) use of object-based image analysis techniques. Our UAV-based procedure produced successful results both in single-tree and in tree-row plantations, reporting up to 97% accuracy on area quantification and minimal deviations compared to in-field estimations of tree heights and crown volumes. The maps generated could be used to understand the linkages between tree grown and field-related factors or to optimize crop management operations in the context of precision agriculture with relevant agro-environmental implications.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0130479