Quality Assessment of Photogrammetric Methods—A Workflow for Reproducible UAS Orthomosaics

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2020-11-22
Author
Ludwig, Marvin
Runge, Christian M.
Friess, Nicolas
Koch, Tiziana L.
Richter, Sebastian
Seyfried, Simon
Wraase, Luise
Lobo, Agustin
Sebastià, Ma. T.
Reudenbach, Christoph
Nauss, Thomas
Suggested citation
Ludwig, Marvin; Runge, Christian M.; Friess, Nicolas; Koch, Tiziana L.; Richter, Sebastian; Seyfried, Simon; ... Nauss, Thomas. (2020) . Quality Assessment of Photogrammetric Methods—A Workflow for Reproducible UAS Orthomosaics. Remote Sensing, 2020, vol. 12, núm. 22, p. 3831. https://doi.org/10.3390/rs12223831.
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Abstract
Unmanned aerial systems (UAS) are cost-effective, flexible and offer a wide range of applications. If equipped with optical sensors, orthophotos with very high spatial resolution can be retrieved using photogrammetric processing. The use of these images in multi-temporal analysis and the combination with spatial data imposes high demands on their spatial accuracy. This georeferencing accuracy of UAS orthomosaics is generally expressed as the checkpoint error. However, the checkpoint error alone gives no information about the reproducibility of the photogrammetrical compilation of orthomosaics. This study optimizes the geolocation of UAS orthomosaics time series and evaluates their reproducibility. A correlation analysis of repeatedly computed orthomosaics with identical parameters revealed a reproducibility of 99% in a grassland and 75% in a forest area. Between time steps, the corresponding positional errors of digitized objects lie between 0.07 m in the grassland and 0.3 m in the forest canopy. The novel methods were integrated into a processing workflow to enhance the traceability and increase the quality of UAS remote sensing.
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http://hdl.handle.net/10459.1/70194
DOI
https://doi.org/10.3390/rs12223831
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Remote Sensing, 2020, vol. 12, núm. 22, p. 3831
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cc-by, (c) Ludwig et al., 2020
Except where otherwise noted, this item's license is described as cc-by, (c) Ludwig et al., 2020