Measurement and calibration of plant-height from fixed-wing UAV images

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dc.contributor.authorHan, Xiongzhe
dc.contributor.authorThomasson, J. Alex
dc.contributor.authorBagnall, G. Cody
dc.contributor.authorPugh, N. Ace
dc.contributor.authorHorne, David W.
dc.contributor.authorRooney, William L.
dc.contributor.authorJung, Jinha
dc.contributor.authorChang, Anjin
dc.contributor.authorMalambo, Lonesome
dc.contributor.authorPopescu, Sorin C.
dc.contributor.authorGates, Ian T.
dc.contributor.authorCope, Dale A.
dc.creator.orcidhttps://orcid.org/0000-0001-6670-9256en_US
dc.creator.orcidhttps://orcid.org/0000-0002-8102-3700en_US
dc.creator.orcidhttps://orcid.org/0000-0001-6670-9256
dc.creator.orcidhttps://orcid.org/0000-0002-8102-3700
dc.creator.orcidhttps://orcid.org/0000-0001-6670-9256
dc.creator.orcidhttps://orcid.org/0000-0002-8102-3700https://orcid.org/0000-0001-6670-9256
dc.creator.orcidhttps://orcid.org/0000-0002-8102-3700
dc.date.accessioned2021-10-28T18:11:09Z
dc.date.available2021-10-28T18:11:09Z
dc.date.issued2018-11-22
dc.description.abstractContinuing population growth will result in increasing global demand for food and fiber for the foreseeable future. During the growing season, variability in the height of crops provides important information on plant health, growth, and response to environmental effects. This paper indicates the feasibility of using structure from motion (SfM) on images collected from 120 m above ground level (AGL) with a fixed-wing unmanned aerial vehicle (UAV) to estimate sorghum plant height with reasonable accuracy on a relatively large farm field. Correlations between UAV-based estimates and ground truth were strong on all dates (R2 > 0.80) but are clearly better on some dates than others. Furthermore, a new method for improving UAV-based plant height estimates with multi-level ground control points (GCPs) was found to lower the root mean square error (RMSE) by about 20%. These results indicate that GCP-based height calibration has a potential for future application where accuracy is particularly important. Lastly, the image blur appeared to have a significant impact on the accuracy of plant height estimation. A strong correlation (R2 = 0.85) was observed between image quality and plant height RMSE and the influence of wind was a challenge in obtaining high-quality plant height data. A strong relationship (R2 = 0.99) existed between wind speed and image blurriness.en_US
dc.description.abstractContinuing population growth will result in increasing global demand for food and fiber for the foreseeable future. During the growing season, variability in the height of crops provides important information on plant health, growth, and response to environmental effects. This paper indicates the feasibility of using structure from motion (SfM) on images collected from 120 m above ground level (AGL) with a fixed-wing unmanned aerial vehicle (UAV) to estimate sorghum plant height with reasonable accuracy on a relatively large farm field. Correlations between UAV-based estimates and ground truth were strong on all dates (R2 > 0.80) but are clearly better on some dates than others. Furthermore, a new method for improving UAV-based plant height estimates with multi-level ground control points (GCPs) was found to lower the root mean square error (RMSE) by about 20%. These results indicate that GCP-based height calibration has a potential for future application where accuracy is particularly important. Lastly, the image blur appeared to have a significant impact on the accuracy of plant height estimation. A strong correlation (R2 = 0.85) was observed between image quality and plant height RMSE and the influence of wind was a challenge in obtaining high-quality plant height data. A strong relationship (R2 = 0.99) existed between wind speed and image blurriness.
dc.identifier.citationHan, X., Thomasson, J.A., Bagnall, G.C., Pugh, N., Horne, D.W., Rooney, W.L., Jung, J., Chang, A., Malambo, L., Popescu, S.C. and Gates, I.T., 2018. Measurement and calibration of plant-height from fixed-wing UAV images. Sensors, 18(12), p.4092.en_US
dc.identifier.citationHan, X., Thomasson, J.A., Bagnall, G.C., Pugh, N., Horne, D.W., Rooney, W.L., Jung, J., Chang, A., Malambo, L., Popescu, S.C. and Gates, I.T., 2018. Measurement and calibration of plant-height from fixed-wing UAV images. Sensors, 18(12), p.4092.
dc.identifier.doihttps://doi.org/10.3390/s18124092
dc.identifier.urihttps://hdl.handle.net/1969.6/89911
dc.language.isoen_USen_US
dc.language.isoen_US
dc.publisherMDPIen_US
dc.publisherMDPI
dc.rightsAttribution 4.0 International*
dc.rightsAttribution 4.0 International
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectfixed-wing uaven_US
dc.subjectsorghum plant heighten_US
dc.subjectstructure from motionen_US
dc.subjectmulti -level gcp'sen_US
dc.subjectgcp-based height calibrationen_US
dc.subjectimage blurrinessen_US
dc.subjectwind speeden_US
dc.subjectfixed-wing uav
dc.subjectsorghum plant height
dc.subjectstructure from motion
dc.subjectmulti -level gcp's
dc.subjectgcp-based height calibration
dc.subjectimage blurriness
dc.subjectwind speed
dc.titleMeasurement and calibration of plant-height from fixed-wing UAV imagesen_US
dc.titleMeasurement and calibration of plant-height from fixed-wing UAV images
dc.typeArticleen_US
dc.typeArticle

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