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Verfasst von:Klopfer, Florian [VerfasserIn]   i
 Hämmerle, Martin [VerfasserIn]   i
 Höfle, Bernhard [VerfasserIn]   i
Titel:Assessing the potential of a low-cost 3-D sensor in shallow-water bathymetry
Verf.angabe:Florian Klopfer, Martin Hämmerle, and Bernhard Höfle
Umfang:5 S.
Fussnoten:Gesehen am 16.02.2018
Titel Quelle:Enthalten in: Institute of Electrical and Electronics Engineers: IEEE geoscience and remote sensing letters
Jahr Quelle:2017
Band/Heft Quelle:14(2017), 8, S. 1388-1392
Abstract:Highly detailed 3-D geoinformation about bathymetry is crucial to understand a wide range of processes and conditions in the geosciences. Recently, low-cost sensors such as Microsoft's structured-light 3-D camera Kinect for Xbox 360 have been deployed to complement established sources of 3-D bathymetric data like light detection and ranging or sound navigation and ranging. In this letter, we assess the Kinect's applicability to capture the bathymetry of shallow waters. Therefore, the maximum capturing range through water, accuracy, and precision of Kinect measurements are examined. Additionally, we test a recording setup which allows for the mitigation of waves and which features advantages in terms of refraction correction on a scene containing submerged gravels. As a result, water depths of 30 cm (outdoors) and 40 cm (indoors) can be penetrated. The accomplished accuracy [mean standard deviation (SD) 7 mm] and precision values (mean SD 3.1 mm) are similar to the ones achieved by terrestrial laser scanning bathymetry. Derived gravel sizes highly correspond to the manual reference measurements. Overall, the findings show the Kinect's applicability in researching shallow natural water bodies.
DOI:doi:10.1109/LGRS.2017.2713991
URL:Bitte beachten Sie: Dies ist ein Bibliographieeintrag. Ein Volltextzugriff für Mitglieder der Universität besteht hier nur, falls für die entsprechende Zeitschrift/den entsprechenden Sammelband ein Abonnement besteht oder es sich um einen OpenAccess-Titel handelt.

DOI: https://doi.org/10.1109/LGRS.2017.2713991
Datenträger:Online-Ressource
Sprache:eng
K10plus-PPN:1569936749
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