Show simple item record

dc.contributor.authorWu, Dan
dc.contributor.authorJohansen, Kasper
dc.contributor.authorPhinn, Stuart
dc.contributor.authorRobson, Andrew
dc.date.accessioned2020-06-07T13:37:40Z
dc.date.available2020-06-07T13:37:40Z
dc.date.issued2020-05-21
dc.date.submitted2020-04-08
dc.identifier.citationWu, D., Johansen, K., Phinn, S., & Robson, A. (2020). Suitability of Airborne and Terrestrial Laser Scanning for Mapping Tree Crop Structural Metrics for Improved Orchard Management. Remote Sensing, 12(10), 1647. doi:10.3390/rs12101647
dc.identifier.issn2072-4292
dc.identifier.doi10.3390/rs12101647
dc.identifier.urihttp://hdl.handle.net/10754/663256
dc.description.abstractAirborne Laser Scanning (ALS) and Terrestrial Laser Scanning (TLS) systems are useful tools for deriving horticultural tree structure estimates. However, there are limited studies to guide growers and agronomists on different applications of the two technologies for horticultural tree crops, despite the importance of measuring tree structure for pruning practices, yield forecasting, tree condition assessment, irrigation and fertilization optimization. Here, we evaluated ALS data against near coincident TLS data in avocado, macadamia and mango orchards to demonstrate and assess their accuracies and potential application for mapping crown area, fractional cover, maximum crown height, and crown volume. ALS and TLS measurements were similar for crown area, fractional cover and maximum crown height (coefficient of determination (R2) ≥ 0.94, relative root mean square error (rRMSE) ≤ 4.47%). Due to the limited ability of ALS data to measure lower branches and within crown structure, crown volume estimates from ALS and TLS data were less correlated (R2 = 0.81, rRMSE = 42.66%) with the ALS data found to consistently underestimate crown volume. To illustrate the effects of different spatial resolution, capacity and coverage of ALS and TLS data, we also calculated leaf area, leaf area density and vertical leaf area profile from the TLS data, while canopy height, tree row dimensions and tree counts) at the orchard level were calculated from ALS data. Our results showed that ALS data have the ability to accurately measure horticultural crown structural parameters, which mainly rely on top of crown information, and measurements of hedgerow width, length and tree counts at the orchard scale is also achievable. While the use of TLS data to map crown structure can only cover a limited number of trees, the assessment of all crown strata is achievable, allowing measurements of crown volume, leaf area density and vertical leaf area profile to be derived for individual trees. This study provides information for growers and horticultural industries on the capacities and achievable mapping accuracies of standard ALS data for calculating crown structural attributes of horticultural tree crops.
dc.description.sponsorshipThis research was funded by Department of Agriculture and Water Resources, Australian Government as part of its Rural R&D for Profit Program's subproject, titled "Multi-Scale Monitoring Tools for Managing Australian Tree Crops-Industry Meets Innovation", grant number RnD4Profit-14-01-008. The authors acknowledge the Australian Federal Government "Rural R and D for Profit" scheme and Horticulture Innovation Australia for funding this research. The authors appreciate the support, especially during field trips, provided for this research by Chris Searle from MacAvo Consulting, by Simpson Farms Pty. Ltd. (Childers, QLD 4660, Australia), in particular, Chad Simpson, Bundaberg Research Facility, and by the Queensland Government's Department of Agriculture and Fisheries, in particular JohnWilkie and Helen Hofman. We thank Martin Béland for sharing the MATLAB code to calculate the leaf area density, Peter Scarth for MATLAB assistance and Nicholas Goodwin for assisting with data registration. We also thank Aaron Aeberli and Yu-Hsuan Tu for their assistance with fieldwork.
dc.publisherMDPI AG
dc.relation.urlhttps://www.mdpi.com/2072-4292/12/10/1647
dc.rightsThis 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.
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.titleSuitability of airborne and terrestrial laser scanning for mapping tree crop structural metrics for improved orchard management
dc.typeArticle
dc.contributor.departmentBiological and Environmental Sciences and Engineering (BESE) Division
dc.contributor.departmentWater Desalination and Reuse Research Center (WDRC)
dc.identifier.journalRemote Sensing
dc.eprint.versionPublisher's Version/PDF
dc.contributor.institutionRemote Sensing Research Centre, School of Earth and Environmental Sciences, The University of Queensland, St Lucia, QLD 4072, Australia
dc.contributor.institutionApplied Agricultural Remote Sensing Centre, School of Science and Technology, University of New England, Armidale, NSW 2351, Australia
dc.identifier.volume12
dc.identifier.issue10
dc.identifier.pages1647
kaust.personJohansen, Kasper
dc.date.accepted2020-05-18
dc.identifier.eid2-s2.0-85085556758
refterms.dateFOA2020-06-07T13:38:01Z


Files in this item

Thumbnail
Name:
remotesensing-12-01647.pdf
Size:
9.166Mb
Format:
PDF
Description:
Published version

This item appears in the following Collection(s)

Show simple item record

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.
Except where otherwise noted, this item's license is described as 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.