• 한국지구물리탐사학회:학술대회논문집
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• 2008.10a
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• pp.145-148
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• 2008

ICESat launched in Jan. 2003 has a capability to monitor polar regions with its inclination of 94 degree. ICESat carries GLAS (Geosciences Laser Altimetry System) to measure Earth's topography in unprecedented accuracy, and thus it can be applied for glacier variation due to recent climate changes. Here we present a new method to estimate velocity structure of Amery Ice-Shelf using ICESat altimtery data. ICESat data shows horizontal displacement of Amery Ice-Shelf, which can be directly used for velocity estimation. This method is expected to extend to other ice-shelves in Antarctica.

• Korean Journal of Remote Sensing
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• v.21 no.1
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• pp.73-81
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• 2005

We construct improved geocentric digital elevation model (DEM), estimate tidal dynamics and ice stream velocity over Sulzberger Ice Shelf, West Antarctica employing differential interferograms from 12 ERS tandem mission Synthetic Aperture Radar (SAR) images acquired in austral fall of 1996. Ice, Cloud, and land Elevation Satellite (ICESat) laser altimetry profiles acquired in the same season as the SAR scenes in 2004 are used as ground control points (GCPs) for Interferometric SAR (InSAR) DEM generation. 20 additional ICESat profiles acquired in 2003-2004 are then used to assess the accuracy of the DEM. The vertical accuracy of the OEM is estimated by comparing elevations with laser altimetry data from ICESat. The mean height difference between all ICESat data and DEM is -0.57m with a standard deviation of 5.88m. We demonstrate that ICESat elevations can be successfully used as GCPs to improve the accuracy of an InSAR derived DEM. In addition, the magnitude and the direction of tidal changes estimated from interferogram are compared with those predicted tidal differences from four ocean tide models. Tidal deformation measured in InSAR is -16.7cm and it agrees well within 3cm with predicted ones from tide models. Lastly, ice surface velocity is estimated by combining speckle matching technique and InSAR line-of-sight measurement. This study shows that the maximum speed and mean speed are 509 m/yr and 131 m/yr, respectively. Our results can be useful for the mass balance study in this area and sea level change.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.1177-1186
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• 2021

As the Arctic melt ponds play an important role in determining the interannual variation of the sea ice extent and changes in the Arctic environment, it is crucial to monitor the Arctic melt ponds with high accuracy. Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2), which is the NASA's latest altimeter satellite based on the green laser (532 nm), observes the global surface elevation. When compared to the CryoSat-2 altimetry satellite whose along-track resolution is 250 m, ICESat-2 is highly expected to provide much more detailed information about Arctic melt ponds thanks to its high along-track resolution of 70 cm. The basic products of ICESat-2 are the surface height and the number of reflected photons. To aggregate the neighboring information of a specific ICESat-2 photon, the segments of photons with 10 m length were used. The standard deviation of the height and the total number of photons were calculated for each segment. As the melt ponds have the smoother surface than the sea ice, the lower variation of the height over melt ponds can make the melt ponds distinguished from the sea ice. When the melt ponds were extracted, the number of photons per segment was used to classify the melt ponds covered with open-water and specular ice. As photons are much more absorbed in the water-covered melt pondsthan the melt ponds with the specular ice, the number of photons persegment can distinguish the water- and ice-covered ponds. As a result, the suggested melt pond detection method was able to classify the sea ice, water-covered melt ponds, and ice-covered melt ponds. A qualitative analysis was conducted using the Sentinel-2 optical imagery. The suggested method successfully classified the water- and ice-covered ponds which were difficult to distinguish with Sentinel-2 optical images. Lastly, the pros and cons of the melt pond detection using satellite altimetry and optical images were discussed.

• 한국지구물리탐사학회:학술대회논문집
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• 2011.10a
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• pp.145-146
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• 2011

• Korean Journal of Remote Sensing
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• v.26 no.6
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• pp.681-691
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• 2010

LiDAR waveform decomposition plays an important role in LiDAR data processing since the resulting decomposed components are assumed to represent reflection surfaces within waveform footprints and the decomposition results ultimately affect the interpretation of LiDAR waveform data. Decomposing the waveform into a mixture of Gaussians involves two related problems; 1) determining the number of Gaussian components in the waveform, and 2) estimating the parameters of each Gaussian component of the mixture. Previous studies estimated the number of components in the mixture before the parameter optimization step, and it tended to suggest a larger number of components than is required due to the inherent noise embedded in the waveform data. In order to tackle these issues, a new LiDAR waveform decomposition algorithm based on the sequential approach has been proposed in this study and applied to the ICESat waveform data. Experimental results indicated that the proposed algorithm utilized a smaller number of components to decompose waveforms, while resulting IMP value is higher than the GLA14 products.

• Spatial Information Research
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• v.22 no.4
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• pp.59-65
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• 2014

Recently, increasing demand for 'Digital Elevation Model(DEM)' to climate change research and various development by global warming in the Arctic region. So we need to verify the accuracy to utilize DEM. In this research, we verified 'ASTER GDEM' and 'GIMP DEM' in several DEM which constructed in the Greenland that most of the area is covered ice sheet. We divided greenland into two part, ice sheet area and non ice sheet area by using the ESA globcover. Then, comparing a difference between 'ASTER DEM', 'GIMP DEM' and ICESat elevation data to verify the accuracy. As a result, GIMP DEM has higher accuracy in ice sheet area and ASTER GDEM has higher accuracy in non-ice sheet area.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.5
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• pp.343-353
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• 2018

Ocean tides in Antarctica are not well constrained mostly due to the lack of tidal observations. Especially, tides underneath and around ice shelves are uncertain. InSAR (Interferometric Synthetic Aperture Radar) data has been used to observe ice shelf movements primarily caused by ocean tides. Here, we demonstrate that it is possible to estimate tidal constituents underneath the Sulzberger ice shelf, West Antarctica, solely using ERS-1/2 tandem mission DInSAR (differential InSAR) observations. In addition, the tidal constituents can be estimated in a high-resolution (~200 m) grid which is beyond any tidal model resolution. We assume that InSAR observed ocean tidal heights can be derived after correcting the InSAR data for the effect of atmospheric loading using the inverse barometric effect, solid earth tides, and ocean tide loading. The ERS (European Remote Sensing) tandem orbit configuration of a 1-day separation between SAR data takes diminishes the sensitivity to major tidal constituents including $K_1$ and $S_2$. Here, the dominant tidal constituent $O_1$ is estimated using 8 differential interferograms underneath the Sulzberger ice shelf. The resulting tidal constituent is compared with a contemporary regional tide model (CATS2008a) and a global tide model (TPXO7.1). The InSAR estimated tidal amplitude agrees well with both models with RMS (root-mean-square) differences of < 2.2 cm and the phase estimate corroborating both tide models to within $8^{\circ}$. We conclude that fine spatial scale (~200 m) Antarctic ice shelf ocean tide determination is feasible for dominant constituents using C-band ERS-1/2 tandem mission InSAR.

• Korean Journal of Remote Sensing
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• v.28 no.3
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• pp.307-318
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• 2012

To understand forest structures, the Geoscience Laser Altimeter System (GLAS) instrument have been employed to measure and monitor forest canopy with feasibility of acquiring three dimensional canopy structure information. This study tried to examine the potential of GLAS dataset in measuring forest canopy structures, particularly maximum canopy height estimation. To estimate maximum canopy height using feasible GLAS dataset, we simply used difference between signal start and ground peak derived from Gaussian decomposition method. After estimation procedure, maximum canopy height was derived from airborne Light Detection and Ranging (LiDAR) data and it was applied to evaluate the accuracy of that of GLAS estimation. In addition, several influences, such as topographical and biophysical factors, were analyzed and discussed to explain error sources of direct maximum canopy height estimation using GLAS data. In the result of estimation using direct method, a root mean square error (RMSE) was estimated at 8.15 m. The estimation tended to be overestimated when comparing to derivations of airborne LiDAR. According to the result of error occurrences analysis, we need to consider these error sources, particularly terrain slope within GLAS footprint, and to apply statistical regression approach based on various parameters from a Gaussian decomposition for accurate and reliable maximum canopy height estimation.

• Bulletin of the Korean Space Science Society
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• 2004.10b
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• pp.296-299
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• 2004

KARI precision attitude determination system has been developed for high accurate geo-coding of KOMPSAT-2 image. Sensor data from two star trackers and a IRU are used as measurement and dynamic data. Sensor data from star tracker are composed of QUEST and unit vector filter. Filter algorithms consists of extended Kalman filter, unscented Kalman filter, and least square batch filter. The type of sensor data and filter algorithm can be chosen by user options. Estimated parameters are Euler angle from 12000 frame to optical bench frame, gyro drift rate bias, gyro scale factor, misalignment angle of star tracker coordinate frame with respect to optical bench frame, and misalignment angle of gyro coordinate frame with respect to optical bench frame. In particular, ground control point data can be applied for estimating misalignment angle of star tracker coordinate frame. Through the simulation, KPADS is able to satisfy the KOMPSAT-2 mission requirement in which geo-location accuracy of image is 80 m (CE90) without ground control point.