Assessment of ICESat performance at the salar de Uyuni, Bolivia

Fricker, H. A.; Borsa, A. A.; Minster, B.; Carabajal, C. C.; Quinn, Katherine J.; Bills, B. G.

doi:10.1029/2005gl023423

Cited by 157 publications

(152 citation statements)

References 2 publications

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“…The aerophotogrammetric DEM and ICESat (DI ) resulted in the smallest shift vector (≈3 m) and an RMSE (3.6 m) of stable terrain after two iterations. We expect the aerophotogrammetric DEM to be of the highest quality and accuracy, thus the impressive coherence with ICESat further confirms previously published ICESat horizontal and vertical accuracies (Fricker et al, 2005;Luthcke et al, 2005;Magruder et al, 2005;Shuman et al, 2006;Brenner et al, 2007). For the other 5 comparisons, the SPOT5-HRS DEM compared better than the ASTER, with a shift vector Before After Fig.…”

Section: Universal Co-registration Correctionsupporting

confidence: 71%

“…Nonetheless, the GLAS lasers operated for the following five years, collecting nearly two billion elevation point measurements before the last laser failed in November 2009. The altimeter has proven to be accurate to within ±15 cm over flat deserts (Fricker et al, 2005), and crossover track differences over low sloped glaciers on the order of ±1 m (Brenner et al, 2007;Moholdt et al, 2010a). ICESat products are freely available from NSIDC (www.nsidc.org), and are the third global elevation product publicly available and tested in this study.…”

Section: Ices At Lidar Profilesmentioning

confidence: 99%

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Co-registration and bias corrections of satellite elevation data sets for quantifying glacier thickness change

2011

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Abstract.There are an increasing number of digital elevation models (DEMs) available worldwide for deriving elevation differences over time, including vertical changes on glaciers. Most of these DEMs are heavily post-processed or merged, so that physical error modelling becomes difficult and statistical error modelling is required instead. We propose a three-step methodological framework for assessing and correcting DEMs to quantify glacier elevation changes: (i) remove DEM shifts, (ii) check for elevation-dependent biases, and (iii) check for higher-order, sensor-specific biases. A simple, analytic and robust method to co-register elevation data is presented in regions where stable terrain is either plentiful (case study New Zealand) or limited (case study Svalbard). The method is demonstrated using the three global elevation data sets available to date, SRTM, ICESat and the ASTER GDEM, and with automatically generated DEMs from satellite stereo instruments of ASTER and SPOT5-HRS. After 3-D co-registration, significant biases related to elevation were found in some of the stereoscopic DEMs. Biases related to the satellite acquisition geometry (along/cross track) were detected at two frequencies in the automatically generated ASTER DEMs. The higher frequency bias seems to be related to satellite jitter, most apparent in the backlooking pass of the satellite. The origins of the more significant lower frequency bias is uncertain. ICESat-derived elevations are found to be the most consistent globally available elevation data set available so far. Before performing regional-scale glacier elevation change studies or mosaicking DEMs from multiple individual tiles (e.g. ASTER GDEM), we recommend to co-register all elevation data to ICESat as a global vertical reference system.

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Section: Universal Co-registration Correctionsupporting

confidence: 71%

Section: Ices At Lidar Profilesmentioning

confidence: 99%

Co-registration and bias corrections of satellite elevation data sets for quantifying glacier thickness change

2011

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“…Hence, surface elevation accuracies at the decimetre level can be achieved (Fricker et al, 2005;Shuman et al, 2006) which are almost comparable to our kinematic GNSS profiles. We use GLA12 elevation data (Zwally et al, 2014) from Release 34 (R34).…”

Section: Icesatsupporting

confidence: 56%

“…However, the Geoscience Laser Altimeter System (GLAS) altimeter was operated in several laser operation campaigns due to laser degradation. Between the campaigns systematic biases exist (Fricker et al, 2005;Gunter et al, 2009). If not accounted for carefully, any systematic biases between campaigns can corrupt the inference of temporal surface elevation changesḣ.…”

Section: Icesat Campaign Biasesmentioning

confidence: 99%

“…We use GLA12 elevation data (Zwally et al, 2014) from Release 34 (R34). We apply the saturation correction (Fricker et al, 2005) to the elevations and exclude all data where flags indicate off-nadir operation, orbit manoeuvres or any other factors degrading the orbit accuracy. We also remove data where the attitude flag indicates any problem with star trackers, gyro or the laser reference sensor.…”

Section: Icesatmentioning

confidence: 99%

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Validation of satellite altimetry by kinematic GNSS in central East Antarctica

Schröder

Richter

Fedorov³

et al. 2017

The Cryosphere

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Abstract. Ice-surface elevation profiles of more than 30 000 km in total length are derived from kinematic GNSS (GPS and the Russian GLONASS) observations on sledge convoy vehicles along traverses between Vostok Station and the East Antarctic coast. These profiles have accuracies between 4 and 9 cm. They are used to validate elevation data sets from both radar and laser satellite altimetry as well as four digital elevation models. A crossover analysis with three different processing versions of Envisat radar altimetry elevation profiles yields a clear preference for the relocation method over the direct method of slope correction and for threshold retrackers over functional fit algorithms. The validation of CryoSat-2 low-resolution mode and SARIn mode data sets documents the progress made from baseline B to C elevation products. ICESat laser altimetry data are demonstrated to be accurate to a few decimetres over a wide range of surface slopes. A crossover adjustment in the region of subglacial Lake Vostok combining ICESat elevation data with our GNSS profiles yields a new set of ICESat laser campaign biases and provides new, independent evidence for the stability of the ice-surface elevation above the lake. The evaluation of the digital elevation models reveals the benefits of combining laser and radar altimetry.

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Estimation of ICESat intercampaign elevation biases from comparison of lidar data in East Antarctica

Hofton

Luthcke

Blair

2013

Geophysical Research Letters

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The Ice, Cloud, and land Elevation Satellite (ICESat) laser campaign elevation biases are estimated from an analysis of ICESat and airborne Land, Vegetation, and Ice Sensor lidar intrasensor and intersensor elevation differences from two regions of the Antarctic ice sheet that experienced minimal surface elevation change. Elevation observations are corrected for a combination of accumulation, melting, and firn densification processes and glacial isostatic adjustment. ICESat elevations are adjusted for the saturation and Gaussian‐Centroid corrections. Relative to laser campaign L3I, biases are found to be less than ∼8 cm, except for campaign L2E at 14.72 cm corresponding to the time of a significant accumulation anomaly in East Antarctica. The intercampaign bias trend estimated from intersensor elevation differences computed over campaigns L2A to L2F (September 2003 to October 2009) excluding L2E is 1.04 ± 0.48 cm/yr. The intercampaign bias trend represents a correction to ICESat derived Antarctica mass balance of 117 ± 53 Gt/yr.

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Assessment of ICESat performance at the salar de Uyuni, Bolivia

Cited by 157 publications

References 2 publications

Co-registration and bias corrections of satellite elevation data sets for quantifying glacier thickness change

Co-registration and bias corrections of satellite elevation data sets for quantifying glacier thickness change

Validation of satellite altimetry by kinematic GNSS in central East Antarctica

Estimation of ICESat intercampaign elevation biases from comparison of lidar data in East Antarctica

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