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Quality assessment of photogrammetric methods - A workflow for reproducible UAS orthomosaics / Marvin Ludwig in Remote sensing, vol 12 n° 22 (December-1 2020)  

Public [article]  inRemote sensing > vol 12 n° 22 (December-1 2020) . - n° 3831 Titre : Quality assessment of photogrammetric methods - A workflow for reproducible UAS orthomosaics Type de document : Article/Communication Auteurs : Marvin Ludwig, Auteur ; Christian M. Runge, Auteur ; Nicolas Friess, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : n° 3831 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique [Termes IGN] analyse diachronique [Termes IGN] capteur optique [Termes IGN] chaîne de traitement [Termes IGN] image à très haute résolution [Termes IGN] image captée par drone [Termes IGN] orthoimage [Termes IGN] orthoimage géoréférencée [Termes IGN] orthophotoplan numérique [Termes IGN] photogrammétrie aérienne [Termes IGN] point de vérification [Termes IGN] reproductibilité [Termes IGN] série temporelle Résumé : (auteur) 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. Numéro de notice : A2020-794 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/rs12223831 Date de publication en ligne : 22/11/2020 En ligne : https://doi.org/10.3390/rs12223831 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96573 [article]