A Workflow to Minimize Shadows in UAV-based Orthomosaics

Simple item page
dc.contributor.authorRahman, Mir Mustafizur
dc.contributor.authorMcDermid, Gregory J.
dc.contributor.authorMckeeman, Taylor
dc.contributor.authorLovitt, Julie
dc.date.accessioned2019-01-15T21:41:57Z
dc.date.available2019-01-15T21:41:57Z
dc.date.issued2019-01-08
dc.description.abstractShadows from buildings, terrain, and other elevated features represent lost and/or impaired data values that hinder the quality of optical images acquired under all but the most diffuse illumination conditions. This is particularly problematic in high-spatial-resolution imagery acquired from unmanned aerial vehicles (UAVs), which generally operate very close to the ground. However, the flexibility and low cost of re-deployment of the platform also presents opportunities, which we capitalize on in a new workflow designed to eliminate shadows from UAV-based orthomosaics. Our straightforward, three-step procedure relies on images acquired from two different UAV flights, where illumination conditions produce diverging shadow orientations: one before solar noon and another after. From this multi-temporal image stack, we first identify and then eliminate shadows from individual orthophoto components, then construct the final orthomosaic using a feature-matching strategy with the commercial software package Photoscan. The utility of our strategy is demonstrated over a treed-wetland study site in northwestern Alberta, Canada: a complex scene containing wide variety of shadows, which our workflow effectively eliminated. While shadow-reduced orthomosaics are generally less useful for feature-identification tasks that rely on the shadow element of image interpretation, they create a superior foundation for most other image-processing routines, including classification and change-detection.en_US
dc.identifier.citationRahman, M. M., McDermid, G. J., Mckeeman, T., & Lovitt, J. (2019). A Workflow to Minimize Shadows in UAV-based Orthomosaics. Journal of Unmanned Vehicle Systems, (ja). https://doi.org/10.1139/juvs-2018-0012en_US
dc.identifier.doihttps://doi.org/10.1139/juvs-2018-0012en_US
dc.identifier.grantnumberBI40020en_US
dc.identifier.issn2291-3467
dc.identifier.urihttp://hdl.handle.net/1880/109470
dc.language.isoenen_US
dc.publisherJournal of Unmanned Vehicle Systems, NRC Research Pressen_US
dc.publisher.departmentGeographyen_US
dc.publisher.facultyArtsen_US
dc.publisher.institutionUniversity of Calgaryen_US
dc.publisher.institutionUniversity of Calgaryen_US
dc.rightsUnless otherwise indicated, this material is protected by copyright and has been made available with authorization from the copyright owner. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.en_US
dc.rights.urihttps://creativecommons.org/licenses/by-nc-sa/4.0en_US
dc.subjectUAVen_US
dc.subjectPhotogrammetryen_US
dc.subjectShadow Removalen_US
dc.subjectOrthophotoen_US
dc.subjectRemote Sensingen_US
dc.titleA Workflow to Minimize Shadows in UAV-based Orthomosaicsen_US
dc.typejournal articleen_US
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Paper_UAV-Orthophoto-Final.pdf
Size:
1.59 MB
Format:
Adobe Portable Document Format
Description:
Download
License bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
license.txt
Size:
1.92 KB
Format:
Item-specific license agreed upon to submission
Description:
Download
Collections
Arts Research & Publications