Hostname: page-component-cd9895bd7-dzt6s Total loading time: 0 Render date: 2024-12-22T23:07:34.337Z Has data issue: false hasContentIssue false

Accuracy assessment of a mobile terrestrial laser scanner for tree crops

Published online by Cambridge University Press:  01 June 2017

F. H. S. Karp*
Affiliation:
Biosystems Engineering Department, University of São Paulo. Av. Pádua Dias 11, 13418-900, Piracicaba, São Paulo, Brazil
A. F. Colaço
Affiliation:
Biosystems Engineering Department, University of São Paulo. Av. Pádua Dias 11, 13418-900, Piracicaba, São Paulo, Brazil
R. G. Trevisan
Affiliation:
Biosystems Engineering Department, University of São Paulo. Av. Pádua Dias 11, 13418-900, Piracicaba, São Paulo, Brazil
J. P. Molin
Affiliation:
Biosystems Engineering Department, University of São Paulo. Av. Pádua Dias 11, 13418-900, Piracicaba, São Paulo, Brazil
*
Get access

Abstract

LiDAR technology is one option to collect spatial data about canopy geometry in many crops. However, the method of data acquisition includes many errors related to the LiDAR sensor, the GNSS receiver and the data acquisition set up. Therefore, the objective of this study was to evaluate the errors involved in the data acquisition from a mobile terrestrial laser scanner (MTLS). Regular shaped objects were scanned with a developed MTLS in two different tests: i) with the system mounted on a vehicle and ii) with the system mounted on a platform running over a rail. The errors of area estimation varied between 0.001 and 0.071 m2 for the circle, square and triangle objects. The errors on volume estimations were between 0.0003 and 0.0017 m3, for cylinders and truncated cone.

Type
Crop Sensors and Sensing
Copyright
© The Animal Consortium 2017 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Arnó, J, Escolà, A, Vallès, JM, Llorens, J, Sanz, R, Masip, J, et al. 2013. Leaf area index estimation in vineyards using a ground-based LiDAR scanner. Precision Agriculture 14, 290306.Google Scholar
Auat Cheein, FA, Guivant, J, Sanz, R, Escolà, A, Yandún, F, Torres-Torriti, M, et al. 2015. Real-time approaches for characterization of fully and partially scanned canopies in groves. Computers and Electronics in Agriculture 118, 361371.CrossRefGoogle Scholar
Chen, Y, Zhu, H and Ozkan, HE 2012. Development of a variable-rate sprayer with laser scanning sensor to synchronize spray outputs to tree structures. Transactions of the ASABE 55, 773781.CrossRefGoogle Scholar
Del-Moral-Martínez, I, Rosell, JR, Company, J, Sanz, R, Escolà, A, Masip, J, et al. 2016. Mapping vineyard leaf area using mobile terrestrial laser scanners: should rows be scanned on-the-go or discontinuously sampled? Sensors 16 (1), 119; 113.Google Scholar
Escolà, A, Martínez-Casasnovas, J, Rufat, J, Arbonés, A, Arnó, J, Masip, J et al 2015. A mobile terrestrial laser scanner for tree crops: point cloud generation, information extraction and validation in an intensive olive orchard. In Precision Agriculture’15: Proceedings of the 10th European Conference on Precision Agriculture, edited by JV Stafford, Wageningen Academic Publishers, The Netherlands. pp. 337344.Google Scholar
Escolà, A, Martínez-Casasnovas, J, Rufat, J, Arnó, J, Arbonés, A, Sebé, F, et al. 2016. Mobile terrestrial laser scanner applications in precision fruticulture/horticulture and tools to extract information from canopy point clouds. Precision Agriculture 17, 122.Google Scholar
Escolà, A, Rosell, JR, Planas, S, Gil, E, Pomar, J, Camp, F, et al. 2013. Variable rate sprayer. Part 1 – Orchard prototype: design, implementation and validation. Computers and Electronics in Agriculture 95, 122135.Google Scholar
Lee, KH and Ehsani, RA 2009. A laser scanner based measurement system for quantification of citrus tree geometric. Applied Engineering in Agriculture 25 (5), 777788.Google Scholar
Llorens, J, Gil, E, Llop, J and Escolà, A 2011. Ultrasonic and lidar sensors for electronic canopy characterization in vineyards: advances to improve pesticide application methods. Sensors 11, 21772194.Google Scholar
Miranda-Fuentes, A, Llorens, J, Gamarra-Diezma, JL, Gil-Ribes, JA and Gil, E 2015. Towards an optimized method of olive tree crown volume measurement. Sensors 15, 36713687.CrossRefGoogle ScholarPubMed
Moorthy, I, Miller, JR, Berni, JAJ, Zarco-Tejada, P, Hu, B and Chen, J 2011. Field characterization of olive (olea europea l.) tree crown architecture using terrestrial laser scanning data. Agricultural and Forest Meteorology 151, 204214.Google Scholar
Pallejà, T, Tresanchez, M, Teixido, M et al 2010. Sensitivity of tree volume measurement to trajectory errors from a terrestrial lidar scanner. Agricultural and Forest Meteorology 150, 14201427.Google Scholar
Rinaldi, M, Llorens, J and Gil, E 2013. Electronic characterization of the phenological stages of grapevine using a lidar sensor. In Precision Agriculture’13: Proceedings of the 9th European Conference on Precision Agriculture, edited by JV Stafford, Wageningen Academic Publishers, The Netherlands. pp. 603609.Google Scholar
Rosell, JR, Llorens, J, Sanz, R, Arnó, J, Ribes-Dasi, M, Masip, J, et al. 2009. Obtaining the three-dimensional of tree orchards from remote 2d terrestrial lidar scanning. Agricultural and Forest Meteorology 149, 15051515.CrossRefGoogle Scholar
Sanz, R, Llorens, J, Rosell, JR, Gregorio, E and Palacín, J 2011. Characterisation of the LMS200 laser beam under the influence of blockage surfaces. Influence on 3D scanning of tree orchards. Sensors 11 (3), 27512772.Google Scholar
Tumbo, SD, Salyani, M, Whitney, JD, Wheaton, TA and Miller, WM 2002. Investigation of laser and ultrasonic ranging sensors for measurements of citrus canopy volume. Applied Engineering in Agriculture 18 (3), 367372.Google Scholar