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| Naji, M. |
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| Motta, Antonella |
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| Aletan, Dirar |
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| Mohamed, Tarek |
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| Ertürk, Emre |
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| Taccardi, Nicola |
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| Kononenko, Denys |
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| Petrov, R. H. | Madrid |
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| Alshaaer, Mazen | Brussels |
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| Bih, L. |
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| Casati, R. |
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| Muller, Hermance |
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| Kočí, Jan | Prague |
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| Šuljagić, Marija |
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| Kalteremidou, Kalliopi-Artemi | Brussels |
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| Azam, Siraj |
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| Ospanova, Alyiya |
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| Blanpain, Bart |
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| Ali, M. A. |
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| Popa, V. |
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| Rančić, M. |
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| Ollier, Nadège |
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| Azevedo, Nuno Monteiro |
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| Landes, Michael |
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| Rignanese, Gian-Marco |
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Nilsson, Johan
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (26/26 displayed)
- 2024Amplification at 2.3-µm in 1.9-µm thulium-doped silica fiber laser
- 2021Binary acoustic trapping in a glass capillarycitations
- 2019An acoustofluidic platform for non-contact trapping of cell-laden hydrogel droplets compatible with optical microscopycitations
- 2018Validation of CryoSat-2 SARIn Data over Austfonna Ice Cap Using Airborne Laser Scanner Measurementscitations
- 2016Numerical methods for load and response prediction for use in acoustic fatigue
- 2014Numerical methods for load prediction in acoustic fatigue
- 2012Acoustic trapping with seed-particles for submicron particle enrichment.
- 2010100W CW cladding-pumped Raman fiber last at 1120nmcitations
- 2010Rare earth doped optical fiber fabrication using novel gas phase deposition techniquecitations
- 2010Bend-effects on Brillouin gain in large mode area fiber amplifiers with acoustic antiguide
- 2009Fiber design for high power fiber laserscitations
- 2009Ytterbium doped nanostructured optical fibers for high power fiber lasers
- 2008Reply to comment on “Photodarkening in Yb-doped aluminosilicate fibers induced by 488 nm irradiation”citations
- 2007Noninvasive acoustic cell trapping in a microfluidic perfusion system for online bioassayscitations
- 2007RGB generation by four-wave mixing in small-core holey fibers
- 2006Spectral control of optical gain in a rare earth-doped optical fiber using novel triple layered structurescitations
- 2006New Yb:Hf-doped silica fiber for high-power fiber laserscitations
- 2006Acoustic Trapping: System Design, Optimization and Applications
- 2006Temperature-dependent fluorescence characteristics of an ytterbium-sensitized erbium-doped silica fiber for sensor applicationscitations
- 2006Using Acoustic Differential Extraction to enhance analysis of sexual assualt evidence on a valveless glass microdevice
- 2004High-power wavelength-tunable cladding-pumped rare-earth-doped silica fiber laserscitations
- 2004Recent advances in high power fiber lasers
- 2004Passively Q-switched thulium-doped silica fiber laser
- 2004Thulium-ytterbium co-doped fiber laser with 32W of output power in the 2 micron wavelength range
- 2003Fiber lasers: flexible and functional solutions for today and the future
- 2002Synchronously pumped optical parametric oscillator driven by a femtosecond mode-locked fibre lasercitations
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article
Validation of CryoSat-2 SARIn Data over Austfonna Ice Cap Using Airborne Laser Scanner Measurements
Abstract
The study presented here is focused on the assessment of surface elevations derived from CryoSat-2 SARIn level 1b data over the Austfonna ice cap, Svalbard, in 2016. The processing chain that must be applied to the CryoSat-2 waveforms to derive heights is non-trivial, and consists of multiple steps, all requiring subjective choices of methods such as the choice of retracker, geo-relocation, and outlier rejection. Here, we compare six CryoSat-2 level-2 type data sets of surface elevations derived using different SARIn processing chains. These data sets are validated against surface elevation data collected from an airborne laser scanner, during a dedicated CryoSat validation experiment field campaign carried out in April 2016. The flight pattern of the airborne campaign was designed so that elevations were measured in a grid pattern rather than along single lines, as has previously been the standard procedure. The flight grid pattern was chosen to optimize the comparison with the CryoSat-2 SARIn elevation data, the location of which can deviate from nadir by several kilometers due to topography within the satellite footprint. The processing chains behind the six data sets include different outlier/error rejection approaches, and do not produce the same number of data points in our region of interest. To make a consistent analysis, we provide statistics from the validation of both the full data sets from each processing chain, and on only those data that all the six data sets provide a geo-located elevation estimate for. We find that the CryoSat-2 data sets that agree best with the validation data are those derived from dedicated land ice processing schemes. This study may serve as a benchmark for future CryoSat-2 retracker developments, and the evaluation software and data set are made publicly available.