• Korean Journal of Remote Sensing
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• v.21 no.4
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• pp.287-302
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• 2005

Digital Elevation Models (DEMs) were generated by ERS-l/2 and JERS-1 SAR interferometry in Daejon area, Korea. The quality of the DEM's was evaluated by the Ground Control Points (GCPs) in city area where GCPs were determined by GPS surveys, while in the mountain area with no GCPs, a 1:25,000 digital map was used. In order to minimize errors due to the inaccurate satellite orbit information and the phase unwrapping procedure, a Differential InSAR (DInSAR) was implemented in addition to the traditional InSAR analysis for DEM generation. In addition, DEMs from GTOPO30, SRTM-3, and 1:25,000 digital map were used for assessment the resolution of the DEM generated from DInSAR. 5-6 meters of elevation errors were found in the flat area regardless of the usage and the resolution of DEM, as a result of InSAR analyzing with a pair of ERS tandem and 6 pairs of JERS-1 interferograms. In the mountain area, however, DInSAR with DEMs from SRTM-3 and the digital map was found to be very effective to reduce errors due to phase unwrapping procedure. Also errors due to low signal-to-noise ratio of radar images and atmospheric effect were attenuated in the DEMs generated from the stacking of 6 pairs of JERS-1. SAR interferometry with multiple pairs of SAR interferogram with low resolution DEM can be effectively used to enhance the resolution of DEM in terms of data processing time and cost.

• Korean Journal of Remote Sensing
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• v.29 no.1
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• pp.11-20
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• 2013

Space-borne Synthetic Aperture Radar(SAR) has been one of the most effective tools for monitoring quantitative oceanographic physical parameters. The Doppler information recorded in single-channel SAR raw data can be useful in estimating moving velocity of water mass in ocean. The Doppler shift is caused by the relative motion between SAR sensor and the water mass of ocean surface. Thus, the moving velocity can be extracted by measuring the Doppler anomaly between extracted Doppler centroid and predicted Doppler centroid. The predicted Doppler centroid, defined as the Doppler centroid assuming that the target is not moving, is calculated based on the geometric parameters of a satellite, such as the satellite's orbit, look angle, and attitude with regard to the rotating Earth. While the estimated Doppler shift, corresponding to the actual Doppler centroid in the situation of real SAR data acquisition, can be extracted directly from raw SAR signal data, which usually calculated by applying the Average Cross Correlation Coefficient(ACCC). The moving velocity was further refined to obtain ocean surface current by subtracting the phase velocity of Bragg-resonant capillary waves. These methods were applied to Envisat ASAR raw data acquired in the East Sea, and the extracted ocean surface currents were compared with the current measured by HF-radar.

• Korean Journal of Remote Sensing
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• v.36 no.2_2
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• pp.237-247
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• 2020

Here, we generated maps of primary production in the coastal waters of the East Sea using sea surface chlorophyll-a concentrations (CHL), photosynthetically available radiation (PAR), euphotic depth induced by GOCI along with sea surface temperature (SST) from satellites of foreign countries as input parameters, and carried out a sensitivity analysis for each parameters. On 25th of July in 2013 when a wide cold waters appeared and on 13th of August in 2013 when a big harmful algal bloom existed in the study area, it shows high productivities with averages 1,012 and 1,945 mg C m^-2 d^-1, respectively. On August 25, 2013, when the cold waters and red tide retreated, it showed an average of 778 m^-2 d^-1, similar to the results of the previous analysis. As a result of the sensitivity analysis, PAR did not significantly affect the results of the primary production, but the euphotic depth and CHL showed aboveaverage sensitivity. In particular, SST had a large influence to the results, thus we could imply that an error in SST could lead to a large error in the primary production. This study showed that GOCI data was available for primary production study, and the accuracy of input parameters might be improved by applying GOCI, which can acquire images 8 times a day, making it more accurate than foreign polar orbit satellites and consequently, it is possible to estimate highly accurately primary production.

• Korean Journal of Remote Sensing
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• v.14 no.3
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• pp.213-222
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• 1998

Electro-Optical Camera(EOC) is the main payload of the KOrea Multi-Purpose SATellite(KOMPSAT) with the mission of cartography to build up a digital map of Korean territory including a Digital Terrain Elevation Map(DTEM). This instalment which comprises EOC Sensor Assembly and EOC Electronics Assembly produces the panchromatic images of 6.6 m GSD with a swath wider than 17 km by push-broom scanning and spacecraft body pointing in a visible range of wavelength, 510~730 nm. The high resolution panchromatic image is to be collected for 2 minutes during 98 minutes of orbit cycle covering about 800 km along ground track, over the mission lifetime of 3 years with the functions of programmable gain/offset and on-board image data storage. The image of 8 bit digitization, which is collected by a full reflective type F8.3 triplet without obscuration, is to be transmitted to Ground Station at a rate less than 25 Mbps. EOC was elaborated to have the performance which meets or surpasses its requirements of design phase. The spectral response, the modulation transfer function, and the uniformity of all the 2592 pixel of CCD of EOC are illustrated as they were measured for the convenience of end-user. The spectral response was measured with respect to each gain setup of EOC and this is expected to give the capability of generating more accurate panchromatic image to the users of EOC data. The modulation transfer function of EOC was measured as greater than 16 % at Nyquist frequency over the entire field of view, which exceeds its requirement of larger than 10 %. The uniformity that shows the relative response of each pixel of CCD was measured at every pixel of the Focal Plane Array of EOC and is illustrated for the data processing.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.6_1
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• pp.455-461
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• 2013

Kompsat-3 is an optical high-resolution earth observation satellite launched in May 2012. The AEISS sensor of the Korean satellite provides 0.7m panchromatic and 2.8m multi-spectral images with 16.8km swath width from the sun-synchronous near-circular orbit of 685km altitude. Kompsat-3 is more advanced than Kompsat-2 and the improvements include better agility such as in-track stereo acquisition capability. This study investigated the characteristic of the epipolar curves of in-track Kompsat-3 stereo images. To this end we used the RPCs(Rational Polynomial Coefficients) to derive the epipolar curves over the entire image area and found out that the third order polynomial equation is required to model the curves. In addition, we could observe two different groups of curve patterns due to the dual CCDs of AEISS sensor. From the experiment we concluded that the third order polynomial-based RPCs update is required to minimize the sample direction image distortion. Finally we carried out the experiment on the epipolar resampling and the result showed the third order polynomial image transformation produced less than 0.7 pixels level of y-parallax.

• Korean Journal of Remote Sensing
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• v.36 no.5_1
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• pp.763-774
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• 2020

Wind data forecasted from the numerical weather prediction (NWP) model is generally used as the first-guess of the target tracking process to obtain the atmospheric motion vectors(AMVs) because it increases tracking accuracy and reduce computational time. However, there is a contradiction that the NWP model used as the first-guess is used again as the reference in the AMVs verification process. To overcome this problem, model-independent first guesses are required. In this study, we propose the AMVs derivation from Lucas and Kanade optical flow method and then using it as the first guess. To retrieve AMVs, Himawari-8/AHI geostationary satellite level-1B data were used at 00, 06, 12, and 18 UTC from August 19 to September 5, 2015. To evaluate the impact of applying the optical flow method on the AMV derivation, cross-validation has been conducted in three ways as follows. (1) Without the first-guess, (2) NWP (KMA/UM) forecasted wind as the first-guess, and (3) Optical flow method based wind as the first-guess. As the results of verification using ECMWF ERA-Interim reanalysis data, the highest precision (RMSVD: 5.296-5.804 ms^-1) was obtained using optical flow based winds as the first-guess. In addition, the computation speed for AMVs derivation was the slowest without the first-guess test, but the other two had similar performance. Thus, applying the optical flow method in the target tracking process of AMVs algorithm, this study showed that the optical flow method is very effective as a first guess for model-independent AMVs derivation.