Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/182147
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dc.contributor.authorPak, Hui Yingen_US
dc.contributor.authorLin, Weisien_US
dc.contributor.authorLaw, Adrian Wing-Keungen_US
dc.date.accessioned2025-01-10T08:02:51Z-
dc.date.available2025-01-10T08:02:51Z-
dc.date.issued2024-
dc.identifier.citationPak, H. Y., Lin, W. & Law, A. W. (2024). Correction of systematic image misalignment in direct georeferencing of UAV multispectral imagery. International Journal of Remote Sensing. https://dx.doi.org/10.1080/01431161.2024.2440944en_US
dc.identifier.issn0143-1161en_US
dc.identifier.urihttps://hdl.handle.net/10356/182147-
dc.description.abstractMosaicking of Unmanned Aerial Vehicles (UAV) imagery over featureless water bodies has been known to be challenging, and poses a significant impediment to water monitoring applications. Techniques such as Structure-from-motion typically fail under such conditions due to the lack of distinctive features in the scene, and direct georeferencing is currently the only practical solution, albeit lower georeferencing accuracy is expected. However, hardware issues, particularly the typical time delay between the GPS unit and the image capture, can lead to systematic image misalignment and further reducing the accuracy. The systematic image misalignment arises as the recording of the geographical coordinates by the GPS unit may not precisely correspond to the exact moment of image exposure, and the image exposure may not always occur at the mid-exposure time. Hardware solutions can mitigate this issue but require technical expertise and resources. Alternatively, software solutions can address the problem without necessitating any hardware modifications. This study introduces an open-source solution for the correction of the systematic image alignment by accounting for the time delay and distance discrepancy between the measurements of the GPS coordinates and the image capture. The method was validated with field UAV surveys conducted in this study under various flight configurations (different flight altitudes and overlap ratios), and effective image alignment was obtained using the proposed open-source solution which reduced the georeferencing error by around 67.7%. Specifically, a georeferencing error of RMSE = 1.409 m and (Formula presented.) = 0.6356 m was achieved without the use of any ground control points (GCPs). Finally, as demonstrated in this study, low flight altitudes (e.g. 15 m) should be discouraged for such conditions as georeferencing errors could amplify due to the limited accuracy of the GPS, resulting in visual artefacts.en_US
dc.description.sponsorshipNational Research Foundation (NRF)en_US
dc.description.sponsorshipPublic Utilities Board (PUB)en_US
dc.language.isoenen_US
dc.relation.ispartofInternational Journal of Remote Sensingen_US
dc.rights© 2024 Informa UK Limited, trading as Taylor & Francis Group. All rights reserved. This article may be downloaded for personal use only. Any other use requires prior permission of the copyright holder. The Version of Record is available online at http://doi.org/10.1080/01431161.2024.2440944.en_US
dc.subjectEngineeringen_US
dc.titleCorrection of systematic image misalignment in direct georeferencing of UAV multispectral imageryen_US
dc.typeJournal Articleen
dc.contributor.schoolSchool of Civil and Environmental Engineeringen_US
dc.contributor.schoolInterdisciplinary Graduate School (IGS)en_US
dc.contributor.schoolSchool of Computer Science and Engineeringen_US
dc.contributor.researchEnvironmental Process Modelling Centreen_US
dc.contributor.researchNanyang Environment and Water Research Instituteen_US
dc.identifier.doi10.1080/01431161.2024.2440944-
dc.description.versionSubmitted/Accepted versionen_US
dc.identifier.scopus2-s2.0-85213060085-
dc.subject.keywordsAerial vehicleen_US
dc.subject.keywordsAltitude controlen_US
dc.description.acknowledgementThis research/project is supported by the National Research Foundation, Singapore, and PUB,Singapore’s National Water Agency under its RIE2025 Urban Solutions and Sustainability (USS)(Water) Centre of Excellence (CoE) Programme, awarded to Nanyang Environment & WaterResearch Institute (NEWRI), Nanyang Technological University, Singapore (NTU).en_US
item.fulltextWith Fulltext-
item.grantfulltextembargo_20260103-
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Correction of systematic image misalignment in direct georeferencing of UAV multispectral imagery APPENDIX.pdf
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