Next Article in Journal
Correcting InSAR Topographically Correlated Tropospheric Delays Using a Power Law Model Based on ERA-Interim Reanalysis
Previous Article in Journal
Coastal Waveform Retracking for Jason-2 Altimeter Data Based on Along-Track Echograms around the Tsushima Islands in Japan
Article Menu
Issue 8 (August) cover image

Export Article

Open AccessArticle
Remote Sens. 2017, 9(8), 763; https://doi.org/10.3390/rs9080763

A Method to Obtain Orange Crop Geometry Information Using a Mobile Terrestrial Laser Scanner and 3D Modeling

1
Biosystems Engineering Department, Luiz de Queiroz College of Agriculture, University of São Paulo, 13418-900 Piracicaba, Brazil
2
Department of Agricultural and Forest Engineering, Research Group on AgroICT & Precision Agriculture, Agrotecnio Centre, School of Agrifood and Forestry Science and Engineering, University of Lleida, 25198 Lleida, Spain
Present address: CSIRO, Waite Campus, Locked Bag 2, Glen Osmond, SA 5064, Australia.
*
Author to whom correspondence should be addressed.
Received: 14 June 2017 / Revised: 13 July 2017 / Accepted: 19 July 2017 / Published: 25 July 2017
(This article belongs to the Section Remote Sensing in Agriculture and Vegetation)
View Full-Text   |   Download PDF [20217 KB, uploaded 27 July 2017]   |  

Abstract

LiDAR (Light Detection and Ranging) technology has been used to obtain geometrical attributes of tree crops in small field plots, sometimes using manual steps in data processing. The objective of this study was to develop a method for estimating canopy volume and height based on a mobile terrestrial laser scanner suited for large commercial orange groves. A 2D LiDAR sensor and a GNSS (Global Navigation Satellite System) receiver were mounted on a vehicle for data acquisition. A georeferenced point cloud representing the laser beam impacts on the crop was created and later classified into transversal sections along the row or into individual trees. The convex-hull and the alpha-shape reconstruction algorithms were used to reproduce the shape of the tree crowns. Maps of canopy volume and height were generated for a 25 ha orange grove. The different options of data processing resulted in different values of canopy volume. The alpha-shape algorithm was considered a good option to represent individual trees whereas the convex-hull was better when representing transversal sections of the row. Nevertheless, the canopy volume and height maps produced by those two methods were similar. The proposed system is useful for site-specific management in orange groves. View Full-Text
Keywords: LiDAR; TLS; canopy volume; 3D surface reconstruction; convex-hull; alpha-shape LiDAR; TLS; canopy volume; 3D surface reconstruction; convex-hull; alpha-shape
Figures

Graphical abstract

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Colaço, A.F.; Trevisan, R.G.; Molin, J.P.; Rosell-Polo, J.R.; Escolà, A. A Method to Obtain Orange Crop Geometry Information Using a Mobile Terrestrial Laser Scanner and 3D Modeling. Remote Sens. 2017, 9, 763.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Remote Sens. EISSN 2072-4292 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top