Inter-comparison of remote sensing platforms for height estimation of mango and avocado tree crowns

dc.contributor.authorWu, Dan
dc.contributor.authorJohansen, Kasper
dc.contributor.authorPhinn, Stuart
dc.contributor.authorRobson, Andrew
dc.contributor.authorTu, Yu-Hsuan
dc.contributor.departmentBiological and Environmental Science and Engineering (BESE) Division
dc.contributor.departmentWater Desalination and Reuse Research Center (WDRC)
dc.contributor.institutionSchool of Earth and Environmental Sciences, The University of Queensland, Australia.
dc.contributor.institutionThe Joint Remote Sensing Research Program, Australia.
dc.contributor.institutionDepartment of Environment and Science, GPO Box 2454, Brisbane, Queensland, 4001, Australia.
dc.contributor.institutionApplied Agricultural Remote Sensing Centre (AARSC), University of New England, Armidale, NSW, 2351, Australia.
dc.date.accepted2020-02-19
dc.date.accessioned2021-02-23T12:45:04Z
dc.date.available2021-02-23T12:45:04Z
dc.date.issued2020-07
dc.date.submitted2019-08-10
dc.description.abstractTo support the adoption of precision agricultural practices in horticultural tree crops, prior research has investigated the relationship between crop vigour (height, canopy density, health) as measured by remote sensing technologies, to fruit quality, yield and pruning requirements. However, few studies have compared the accuracy of different remote sensing technologies for the estimation of tree height. In this study, we evaluated the accuracy, flexibility, aerial coverage and limitations of five techniques to measure the height of two types of horticultural tree crops, mango and avocado trees. Canopy height estimates from Terrestrial Laser Scanning (TLS) were used as a reference dataset against height estimates from Airborne Laser Scanning (ALS) data, WorldView-3 (WV-3) stereo imagery, Unmanned Aerial Vehicle (UAV) based RGB and multi-spectral imagery, and field measurements. Overall, imagery obtained from the UAV platform were found to provide tree height measurement comparable to that from the TLS (R2 = 0.89, RMSE = 0.19 m and rRMSE = 5.37 % for mango trees; R2 = 0.81, RMSE = 0.42 m and rRMSE = 4.75 % for avocado trees), although coverage area is limited to 1–10 km2 due to battery life and line-of-sight flight regulations. The ALS data also achieved reasonable accuracy for both mango and avocado trees (R2 = 0.67, RMSE = 0.24 m and rRMSE = 7.39 % for mango trees; R2 = 0.63, RMSE = 0.43 m and rRMSE = 5.04 % for avocado trees), providing both optimal point density and flight altitude, and therefore offers an effective platform for large areas (10 km2–100 km2). However, cost and availability of ALS data is a consideration. WV-3 stereo imagery produced the lowest accuracies for both tree crops (R2 = 0.50, RMSE = 0.84 m and rRMSE = 32.64 % for mango trees; R2 = 0.45, RMSE = 0.74 m and rRMSE = 8.51 % for avocado trees) when compared to other remote sensing platforms, but may still present a viable option due to cost and commercial availability when large area coverage is required. This research provides industries and growers with valuable information on how to select the most appropriate approach and the optimal parameters for each remote sensing platform to assess canopy height for mango and avocado trees.
dc.description.sponsorshipThe authors acknowledge the Australian Federal Government ‘Rural R&D for Profit’ scheme and Horticulture Innovation Australia for funding this Research. The authors appreciate the support provided for this research by Dr Chris Searle and Simpson Farms Pty. Ltd. (Childers, QLD 4660, Australia), in particular, Chad Simpson. The authors would also like to thank Dr Peter Scarth for suggestions.
dc.eprint.versionPublisher's Version/PDF
dc.identifier.citationWu, D., Johansen, K., Phinn, S., Robson, A., & Tu, Y.-H. (2020). Inter-comparison of remote sensing platforms for height estimation of mango and avocado tree crowns. International Journal of Applied Earth Observation and Geoinformation, 89, 102091. doi:10.1016/j.jag.2020.102091
dc.identifier.doi10.1016/j.jag.2020.102091
dc.identifier.issn0303-2434
dc.identifier.journalInternational Journal of Applied Earth Observation and Geoinformation
dc.identifier.pages102091
dc.identifier.urihttp://hdl.handle.net/10754/667613
dc.identifier.volume89
dc.publisherElsevier BV
dc.relation.urlhttps://linkinghub.elsevier.com/retrieve/pii/S0303243419308608
dc.rightsThis is an open access article under the CC BY-NC-ND license.
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.titleInter-comparison of remote sensing platforms for height estimation of mango and avocado tree crowns
dc.typeArticle
display.details.left<span><h5>License</h5>http://creativecommons.org/licenses/by-nc-nd/4.0/<br><br><h5>Type</h5>Article<br><br><h5>Authors</h5><a href="https://repository.kaust.edu.sa/search?spc.sf=dc.date.issued&spc.sd=DESC&f.author=Wu, Dan,equals">Wu, Dan</a><br><a href="https://repository.kaust.edu.sa/search?spc.sf=dc.date.issued&spc.sd=DESC&f.author=Johansen, Kasper,equals">Johansen, Kasper</a><br><a href="https://repository.kaust.edu.sa/search?spc.sf=dc.date.issued&spc.sd=DESC&f.author=Phinn, Stuart,equals">Phinn, Stuart</a><br><a href="https://repository.kaust.edu.sa/search?spc.sf=dc.date.issued&spc.sd=DESC&f.author=Robson, Andrew,equals">Robson, Andrew</a><br><a href="https://repository.kaust.edu.sa/search?query=orcid.id:0000-0002-7726-1159&spc.sf=dc.date.issued&spc.sd=DESC">Tu, Yu-Hsuan</a> <a href="https://orcid.org/0000-0002-7726-1159" target="_blank"><img src="https://repository.kaust.edu.sa/server/api/core/bitstreams/82a625b4-ed4b-40c8-865a-d6a5225a26a4/content" width="16" height="16"/></a><br><br><h5>KAUST Department</h5><a href="https://repository.kaust.edu.sa/search?spc.sf=dc.date.issued&spc.sd=DESC&f.department=Biological and Environmental Science and Engineering (BESE) Division,equals">Biological and Environmental Science and Engineering (BESE) Division</a><br><a href="https://repository.kaust.edu.sa/search?spc.sf=dc.date.issued&spc.sd=DESC&f.department=Water Desalination and Reuse Research Center (WDRC),equals">Water Desalination and Reuse Research Center (WDRC)</a><br><br><h5>Date</h5>2020-07<br><br><h5>Submitted Date</h5>2019-08-10</span>
display.details.right<span><h5>Abstract</h5>To support the adoption of precision agricultural practices in horticultural tree crops, prior research has investigated the relationship between crop vigour (height, canopy density, health) as measured by remote sensing technologies, to fruit quality, yield and pruning requirements. However, few studies have compared the accuracy of different remote sensing technologies for the estimation of tree height. In this study, we evaluated the accuracy, flexibility, aerial coverage and limitations of five techniques to measure the height of two types of horticultural tree crops, mango and avocado trees. Canopy height estimates from Terrestrial Laser Scanning (TLS) were used as a reference dataset against height estimates from Airborne Laser Scanning (ALS) data, WorldView-3 (WV-3) stereo imagery, Unmanned Aerial Vehicle (UAV) based RGB and multi-spectral imagery, and field measurements. Overall, imagery obtained from the UAV platform were found to provide tree height measurement comparable to that from the TLS (R2 = 0.89, RMSE = 0.19 m and rRMSE = 5.37 % for mango trees; R2 = 0.81, RMSE = 0.42 m and rRMSE = 4.75 % for avocado trees), although coverage area is limited to 1–10 km2 due to battery life and line-of-sight flight regulations. The ALS data also achieved reasonable accuracy for both mango and avocado trees (R2 = 0.67, RMSE = 0.24 m and rRMSE = 7.39 % for mango trees; R2 = 0.63, RMSE = 0.43 m and rRMSE = 5.04 % for avocado trees), providing both optimal point density and flight altitude, and therefore offers an effective platform for large areas (10 km2–100 km2). However, cost and availability of ALS data is a consideration. WV-3 stereo imagery produced the lowest accuracies for both tree crops (R2 = 0.50, RMSE = 0.84 m and rRMSE = 32.64 % for mango trees; R2 = 0.45, RMSE = 0.74 m and rRMSE = 8.51 % for avocado trees) when compared to other remote sensing platforms, but may still present a viable option due to cost and commercial availability when large area coverage is required. This research provides industries and growers with valuable information on how to select the most appropriate approach and the optimal parameters for each remote sensing platform to assess canopy height for mango and avocado trees.<br><br><h5>Citation</h5>Wu, D., Johansen, K., Phinn, S., Robson, A., & Tu, Y.-H. (2020). Inter-comparison of remote sensing platforms for height estimation of mango and avocado tree crowns. International Journal of Applied Earth Observation and Geoinformation, 89, 102091. doi:10.1016/j.jag.2020.102091<br><br><h5>Acknowledgements</h5>The authors acknowledge the Australian Federal Government ‘Rural R&D for Profit’ scheme and Horticulture Innovation Australia for funding this Research. The authors appreciate the support provided for this research by Dr Chris Searle and Simpson Farms Pty. Ltd. (Childers, QLD 4660, Australia), in particular, Chad Simpson. The authors would also like to thank Dr Peter Scarth for suggestions.<br><br><h5>Publisher</h5><a href="https://repository.kaust.edu.sa/search?spc.sf=dc.date.issued&spc.sd=DESC&f.publisher=Elsevier BV,equals">Elsevier BV</a><br><br><h5>Journal</h5><a href="https://repository.kaust.edu.sa/search?spc.sf=dc.date.issued&spc.sd=DESC&f.journal=International Journal of Applied Earth Observation and Geoinformation,equals">International Journal of Applied Earth Observation and Geoinformation</a><br><br><h5>DOI</h5><a href="https://doi.org/10.1016/j.jag.2020.102091">10.1016/j.jag.2020.102091</a><br><br><h5>Additional Links</h5>https://linkinghub.elsevier.com/retrieve/pii/S0303243419308608</span>
kaust.personJohansen, Kasper
kaust.personTu, Yu-Hsuan
orcid.authorWu, Dan
orcid.authorJohansen, Kasper
orcid.authorPhinn, Stuart
orcid.authorRobson, Andrew
orcid.authorTu, Yu-Hsuan::0000-0002-7726-1159
orcid.id0000-0002-7726-1159
refterms.dateFOA2021-02-23T12:46:45Z
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