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

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.

Influence of Spatial Resolution for Vegetation Indices’ Extraction Using Visible Bands from Unmanned Aerial Vehicles’ Orthomosaics Datasets

“…Generally, these areas appeared as a constant source of reconstruction errors due to the low efficiency of SfM techniques in defining unambiguous points. The matching algorithms are weak in identifying stable tie points in vegetated areas, which generates artefacts and distortions that are challenging to resolve [13]. As shown in Table 4, this set off a loss of efficiency of extraction techniques in vegetated areas.…”

“…These points suffer from the methodology of radiometric calibration of the images, which, as set out in Section 2.4, is still a raw and not entirely effective method. At other points, distortions caused by the low quality of the sensors and/or artefacts generated by the SfM-MVS procedures result in fallacious reflectance values [13]. The vegetation indices for all points were thus estimated.…”

“…Despite this, the scientific community was still engaged in finding optimised methodologies to mitigate the various uncertainties from lens distortions in the inertial measurement unit and the sensor's interior and exterior orientation parameters. However, several recent works attested to the validity of these products according to the scientific community's accuracy standards [13,14].…”

Modern Technology in Geography Education—Attitudes of Pre-Service Teachers of Geography on Modern Technology

“…Geographical information systems (GIS) have mostly replaced the use of print media and maps in science and applied areas [13,14], even if they continue to be used in school education. Spatial (GPS) and remote sensing technologies, such as satellite-based or airborne surface scans at any scale [15].…”

Editorial for Special Issue “UAV Photogrammetry and Remote Sensing”

“…The quality assessment of UAV Photogrammetric products was the main concern of [4]. In this work, the geolocation procedure of UAV orthomosaics time series was optimized, obtaining a reproducibility of 99% in a grassland located in Germany and 75% in a forest area in the Spanish Pyreneess.…”