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

Remote Sensing

卷:12

Nicolas Friess¹  Thomas Nauss¹  Marvin Ludwig¹  Sebastian Richter¹  Simon Seyfried¹  Luise Wraase¹  Christoph Reudenbach¹  Christian M. Runge²  M.-Teresa Sebastiಠ Agustin Lobo³  TizianaL. Koch⁴ 

[1] Department of Geography, Philipps-University Marburg, Deutschhausstr. 10, 35037 Marburg, Germany;

[2] GAMES Group, Department of Horticulture, Fruit, Growing Botany and Gardening, University of Lleida, 25198 Lleida, Spain;

[3] Geoscience Barcelona (GEO3BCN—CSIC), 08028 Barcelona, Spain;

[4] Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Zürcherstr. 111, 8903 Birmensdorf, Switzerland;

关键词: unmanned aerial systems;    unmanned aerial vehicle;    time series;    accuracy;    reproducibility;    orthomosaic;   

DOI  :  10.3390/rs12223831

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown