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Titel |
Deploying four optical UAV-based sensors over grassland: challenges and limitations |
VerfasserIn |
S. K. von Bueren, A. Burkart, A. Hueni, U. Rascher, M. P. Tuohy, I. J. Yule |
Medientyp |
Artikel
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Sprache |
Englisch
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ISSN |
1726-4170
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Digitales Dokument |
URL |
Erschienen |
In: Biogeosciences ; 12, no. 1 ; Nr. 12, no. 1 (2015-01-09), S.163-175 |
Datensatznummer |
250117764
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Publikation (Nr.) |
copernicus.org/bg-12-163-2015.pdf |
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Zusammenfassung |
Unmanned aerial vehicles (UAVs) equipped with lightweight spectral sensors
facilitate non-destructive, near-real-time vegetation analysis. In order to
guarantee robust scientific analysis, data acquisition protocols and
processing methodologies need to be developed and new sensors must be
compared with state-of-the-art instruments. Four different types of optical
UAV-based sensors (RGB camera, converted near-infrared camera, six-band
multispectral camera and high spectral resolution spectrometer) were
deployed and compared in order to evaluate their applicability for
vegetation monitoring with a focus on precision agricultural applications.
Data were collected in New Zealand over ryegrass pastures of various
conditions and compared to ground spectral measurements. The UAV STS
spectrometer and the multispectral camera MCA6 (Multiple Camera Array) were found to deliver
spectral data that can match the spectral measurements of an ASD at ground
level when compared over all waypoints (UAV STS: R2=0.98; MCA6:
R2=0.92). Variability was highest in the near-infrared bands for both
sensors while the band multispectral camera also overestimated the green
peak reflectance. Reflectance factors derived from the RGB (R2=0.63)
and converted near-infrared (R2=0.65) cameras resulted in lower
accordance with reference measurements. The UAV spectrometer system is
capable of providing narrow-band information for crop and pasture
management. The six-band multispectral camera has the potential to be
deployed to target specific broad wavebands if shortcomings in radiometric
limitations can be addressed. Large-scale imaging of pasture variability can
be achieved by either using a true colour or a modified near-infrared camera.
Data quality from UAV-based sensors can only be assured, if field protocols
are followed and environmental conditions allow for stable platform
behaviour and illumination. |
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