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dc.contributor.author
Aasen, Helge
dc.contributor.author
Honkavaara, Eija
dc.contributor.author
Lucieer, Arko
dc.contributor.author
Zarco-Tejada, Pablo
dc.date.accessioned
2018-07-20T08:10:24Z
dc.date.available
2018-07-19T17:39:08Z
dc.date.available
2018-07-20T08:10:24Z
dc.date.issued
2018-07-09
dc.identifier.issn
2072-4292
dc.identifier.other
10.3390/rs10071091
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/277023
dc.identifier.doi
10.3929/ethz-b-000277023
dc.description.abstract
In the last 10 years, development in robotics, computer vision, and sensor technology has provided new spectral remote sensing tools to capture unprecedented ultra-high spatial and high spectral resolution with unmanned aerial vehicles (UAVs). This development has led to a revolution in geospatial data collection in which not only few specialist data providers collect and deliver remotely sensed data, but a whole diverse community is potentially able to gather geospatial data that fit their needs. However, the diversification of sensing systems and user applications challenges the common application of good practice procedures that ensure the quality of the data. This challenge can only be met by establishing and communicating common procedures that have had demonstrated success in scientific experiments and operational demonstrations. In this review, we evaluate the state-of-the-art methods in UAV spectral remote sensing and discuss sensor technology, measurement procedures, geometric processing, and radiometric calibration based on the literature and more than a decade of experimentation. We follow the ‘journey’ of the reflected energy from the particle in the environment to its representation as a pixel in a 2D or 2.5D map, or 3D spectral point cloud. Additionally, we reflect on the current revolution in remote sensing, and identify trends, potential opportunities, and limitations.
en_US
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
MDPI
en_US
dc.rights.uri
http://creativecommons.org/licenses/by/4.0/
dc.subject
Imaging spectroscopy
en_US
dc.subject
spectral
en_US
dc.subject
Unmanned aerial vehicles
en_US
dc.subject
unmanned aerial systems (UAS)
en_US
dc.subject
Remotely Piloted Aircraft Systems (RPAS)
en_US
dc.subject
Drone
en_US
dc.subject
calibration
en_US
dc.subject
Hyperspectral
en_US
dc.subject
Multispectral
en_US
dc.subject
low-altitude
en_US
dc.subject
remote sensing
en_US
dc.subject
sensors
en_US
dc.subject
2D imager
en_US
dc.subject
pushbroom
en_US
dc.subject
snapshot
en_US
dc.subject
spectroradiometers
en_US
dc.title
Quantitative Remote Sensing at Ultra-High Resolution with UAV Spectroscopy: A Review of Sensor Technology, Measurement Procedures, and Data Correction Workflows
en_US
dc.type
Review Article
dc.rights.license
Creative Commons Attribution 4.0 International
ethz.journal.title
Remote Sensing
ethz.journal.volume
10
en_US
ethz.journal.issue
7
en_US
ethz.journal.abbreviated
Remote Sens.
ethz.pages.start
1091
en_US
ethz.size
42 p.
en_US
ethz.version.deposit
publishedVersion
en_US
ethz.identifier.wos
ethz.identifier.scopus
ethz.publication.place
Basel
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02350 - Dep. Umweltsystemwissenschaften / Dep. of Environmental Systems Science::02703 - Institut für Agrarwissenschaften / Institute of Agricultural Sciences::03894 - Walter, Achim / Walter, Achim
en_US
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02350 - Dep. Umweltsystemwissenschaften / Dep. of Environmental Systems Science::02703 - Institut für Agrarwissenschaften / Institute of Agricultural Sciences::03894 - Walter, Achim / Walter, Achim
en_US
ethz.date.deposited
2018-07-19T17:39:10Z
ethz.source
FORM
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2018-07-20T08:10:30Z
ethz.rosetta.lastUpdated
2022-03-28T20:41:27Z
ethz.rosetta.versionExported
true
ethz.COinS
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