• Proceedings of the Optical Society of Korea Conference
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• 2003.07a
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• pp.278-279
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• 2003

광도의 기본 단위인 칸델라(Candela) 눈금은 물론 복사조도(irradiance), 조명도(illuminance)와 같은 유도 단위를 실현하기 위해서는 검출기의 시야를 한정하는 개구면적의 정밀한 측정이 필요하다. 여기에서는 가장자리의 광학적 검출방법에 의한 개구면적의 산출방식을 소개하고, 가우시안광에 의한 면적 측정법의 측정값과도 비교하여 그 결과를 보여준다. 기존의 개구 면적 측정방식으로 한가지 방법은 탐촉자를 물리적으로 접촉시켜서 개구의 가장자리를 결정하고, 개구의 기하학적 모양을 원으로 가정하여 면적을 산출하는 방식이 있는데, 이 방법을 사용하면 기계적인 접촉에 의하여 칼날과 같았던 개구의 가장자리가 손상을 입게 되기 때문에 측정이 잘못되는 것은 물론이고, 이렇게 측정된 개구를 사용하게되면 손상된 부위에 의한 면적의 변화와 이로 인한 산란이 증가하게 된다. (중략)

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.24 no.3
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• pp.299-309
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• 2013

A comprehensive SAR(Synthetic Aperture Radar) simulation is considered to be a complicated task since a full knowledge of the signal propagation characteristics, antenna pattern, system internal errors and interference noises should be taken into account. In high resolution target application modes, the time varying nature of target RCS(Radar Cross Section) strongly affects the generated SAR images. In this paper, in-depth SAR simulations are performed and analyzed incorporating the STK tools and MATLAB software. STK provides realistic orbit parameters while its radar module helps to extract accurate radiometric parameters of ground targets. SAR raw data corresponding to a given target is generated and processed using MATLAB simulator. The performance is measured by PSLR(Peak Sidelobe Ratio) and ISLR(Integrated Sidelobe Ratio) for a point target, which can be used as reference parameters for accurate radiometric calibration. Finally, high resolution target simulations are performed by adopting time varying target RCS characteristics.

• Korean Journal of Geomatics
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• v.2 no.1
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• pp.37-46
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• 2002

Accurate classification of water area is an preliminary step to accurately analyze the flooded area and damages caused by flood. This step is especially useful for monitoring the region where annually repeating flood is a problem. The accurate estimation of flooded area can ultimately be utilized as a primary source of information for the policy decision. Although SAR (Synthetic Aperture Radar) imagery with its own energy source is sensitive to the water area, its shadow effect similar to the reflectance signature of the water area should be carefully checked before accurate classification. Especially when we want to identify small flood area with mountainous environment, the step for removing shadow effect turns out to be essential in order to accurately classify the water area from the SAR imagery. In this paper, the flood area was classified and monitored using multi-temporal RADARSAT SAR images of Ok-Chun and Bo-Eun located in Chung-Book Province taken in 12th (during the flood) and 19th (after the flood) of August, 1998. We applied several steps of geometric and radiometric calculations to the SAR imagery. First we reduced the speckle noise of two SAR images and then calculated the radar backscattering coefficient $(\sigma^0)$. After that we performed the ortho-rectification via satellite orbit modeling developed in this study using the ephemeris information of the satellite images and ground control points. We also corrected radiometric distortion caused by the terrain relief. Finally, the water area was identified from two images and the flood area is calculated accordingly. The identified flood area is analyzed by overlapping with the existing land use map.

• Korean Journal of Remote Sensing
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• v.22 no.1
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• pp.25-40
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• 2006

Synthetic aperture radar (SAR) from satellites provides the opportunity to regularly incorporate microwave information into forest classification. Radar backscatter can improve classification accuracy, and SAR interferometry could provide improved thematic information through the use of coherence. This research examined the potential of using multi-temporal JERS-l SAR (L band) backscatter information and interferometry in distinguishing forest classes of mountainous areas in the Northeastern U.S. for future forest mapping and monitoring. Raw image data from a pair of images were processed to produce coherence and backscatter data. To improve the geometric characteristics of both the coherence and the backscatter images, this study used the interferometric techniques. It was necessary to radiometrically correct radar backscatter to account for the effect of topography. This study developed a simplified method of radiometric correction for SAR imagery over the hilly terrain, and compared the forest-type discriminatory powers of the radar backscatter, the multi-temporal backscatter, the coherence, and the backscatter combined with the coherence. Statistical analysis showed that the method of radiometric correction has a substantial potential in separating forest types, and the coherence produced from an interferometric pair of images also showed a potential for distinguishing forest classes even though heavily forested conditions and long time separation of the images had limitations in the ability to get a high quality coherence. The method of combining the backscatter images from two different dates and the coherence in a multivariate approach in identifying forest types showed some potential. However, multi-temporal analysis of the backscatter was inconclusive because leaves were not the primary scatterers of a forest canopy at the L-band wavelengths. Further research in forest classification is suggested using diverse band width SAR imagery and fusing with other imagery source.

• Korean Journal of Remote Sensing
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• v.34 no.5
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• pp.739-747
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• 2018

Integration analysis of multi-sensor satellite images is becoming increasingly important. The first step in integration analysis is image registration between multi-sensor. SIFT (Scale Invariant Feature Transform) is a representative image registration method. However, optical image and SAR (Synthetic Aperture Radar) images are different from sensor attitude and radiation characteristics during acquisition, making it difficult to apply the conventional method, such as SIFT, because the radiometric characteristics between images are nonlinear. To overcome this limitation, we proposed a modified method that combines the SAR-SIFT method and shape descriptor vector DLSS(Dense Local Self-Similarity). We conducted an experiment using two pairs of Cosmo-SkyMed and KOMPSAT-2 images collected over Daejeon, Korea, an area with a high density of buildings. The proposed method extracted the correct matching points when compared to conventional methods, such as SIFT and SAR-SIFT. The method also gave quantitatively reasonable results for RMSE of 1.66m and 2.45m over the two pairs of images.

• Bulletin of the Korean Space Science Society
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• 2011.04a
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• pp.30.2-30.2
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• 2011

In this report, we present in-orbit radiometric performance prediction for the Amon-Ra (Albedo Monitor and Radiometer) energy channel instrument. The Integrated Ray Tracing (IRT) computational technique uses the ray sets arriving at the Amon-Ra instrument aperture orbiting around the L1 halo orbit. Using this, the variation of flux arriving at the energy channel detector was obtained when the Amon-Ra instrument including the energy channel design observes the Sun and Earth alternately. The flux detectability was verified at the energy channel detector (LME-500-A, InfraTecTM). The detector time response and RMS signal voltage were then derived from the simulated flux variation results. The computation results demonstrate that the designed energy channel optical system satisfies the in-orbit detectability requirement. The technical details of energy channel instrument design, IRT model construction, radiative transfer simulation and output signal computation results are presented together with future development plan.

• Korean Journal of Remote Sensing
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• v.27 no.3
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• pp.225-234
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• 2011

This study proposes an inversion algorithm to extract the surface parameters, such as surface roughness and soil moisture contents, using multi-frequency SAR data. The study areas include the tidal flats of Jebu Island and the reclaimed lands of Hwaong district on the western coasts of the Korean peninsula. SAR data of three frequencies were accordingly calibrated to provide precise backscattering coefficients through absolute radiometric calibration. The root mean square (RMS) height and the correlation length, which can describe the surface roughness, were extracted from the backscattering coefficients using the inversion of the Integral Equation Method (IEM). The IEM model was appropriately modified to accommodate the environmental conditions of tidal flats. Volumetric soil moisture was also simultaneously extracted from the dielectric constant using the empirical model, which define the relations between volumetric soil moistures and dielectric constants. The results obtained from the proposed algorithm were verified with the in-situ measurements, and we confirmed that multi-frequency SAR observations combined with the surface scattering model for tidal flats can be used to quantitatively retrieve the geophysical surface parameters in tidal flats.

• Korean Journal of Remote Sensing
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• v.34 no.6_3
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• pp.1457-1468
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• 2018

The sigma naught (${\sigma}^0$) equation is essential to calculate geo-physical properties from Synthetic Aperture Radar (SAR) images for the applications such as ground target identification,surface classification, sea wind speed calculation, and soil moisture estimation. In this paper, we are suggesting new Kompsat-5 (K5) Radar Cross Section (RCS) and ${\sigma}^0$ equations reflecting the final SAR processor update and absolute radiometric calibration in order to increase the application of K5 SAR images. Firstly, we analyzed the accuracy of the K5 RCS equation by using trihedral corner reflectors installed in the Kompsat calibration site in Mongolia. The average difference between the calculated values using RCS equation and the measured values with K5 SAR processor was about $0.2dBm^2$ for Spotlight and Stripmap imaging modes. In addition, the verification of the K5 ${\sigma}^0$ equation was carried out using the TerraSAR-X (TSX) and Sentinel-1A (S-1A) SAR images over Amazon rainforest, where the backscattering characteristics are not significantly affected by the seasonal change. The calculated ${\sigma}^0$ difference between K5 and TSX/S-1A was less than 0.6 dB. Considering the K5 absolute radiometric accuracy requirement, which is 2.0 dB ($1{\sigma}$), the average difference of $0.2dBm^2$ for RCS equation and the maximum difference of 0.6 dB for ${\sigma}^0$ equation show that the accuracies of the suggested equations are relatively high. In the future, the validity of the suggested RCS and ${\sigma}^0$ equations is expected to be verified through the application such as sea wind speed calculation, where quantitative analysis is possible.

• Bulletin of the Korean Space Science Society
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• 2008.10a
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• pp.27.3-28
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• 2008

In this study, we report a new Monte Carlo ray tracing technique for estimating GOCI (Geostationary Ocean Color Instrument) radiative transfer characteristics and imaging performance simultaneously. First, a full scale GOCI optical model was constructed with measured characteristics at the component level and placed in the geostationary orbit. An optical model of approximated GOCI target area centered at the Korean penninsular was then built using the USGS coastal line data and representative land and sea surface reflectivity data. The light rays launched from a simulated sun model travel to the Earth surface, where they are reflected and scattered. Some of the light rays that are headed to the GOCI model in the orbit were selected and traced, as they have entered into the GOCI aperture. As they pass through each GOCI optical part, the ray path and intensity are adjusted according to the measured characteristics for reflection, transmission, refractive index and surface scattering. The ray-traced imaging and radiative transfer performance indicators confirm that the computer generated GOCI optical system with measured characteristics can be used for in-orbit operation simulation following the designed measurement sequence. The computational technique and its implications as a operation support tool are discussed.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.152-152
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• 2019

This study demonstrates a novel approach of remotely sensed estimates of stream flow at fifteen hydrological station in the Han River Basin, Korea. Multi-temporal data of the European Space Agency's Sentinel-1 SAR satellite from 19 January, 2015 to 25 August, 2018 is used to develop and validate the flow estimation model for each station. The flow estimation model is based on a power law relationship established between the remotely sensed surface area of water at a selected reach of the stream and the observed discharge. The satellite images were pre-processed for thermal noise, radiometric, speckle and terrain correction. The difference in SAR image brightness caused by the differences in SAR satellite look angle and atmospheric condition are corrected using the histogram matching technique. Selective area filtering is applied to identify the extent of the selected stream reach where the change in water surface area is highly sensitive to the change in stream discharge. Following this, an iterative procedure called the Optimum Threshold Classification Algorithm (OTC) is applied to the multi-temporal selective areas to extract a series of water surface areas. It is observed that the extracted water surface area and the stream discharge are related by the power law equation. A strong correlation coefficient ranging from 0.68 to 0.98 (mean=0.89) was observed for thirteen hydrological stations, while at two stations the relationship was highly affected by the hydraulic structures such as dam. It is further identified that the availability of remotely sensed data for a range of discharge conditions and the geometric properties of the selected stream reach such as the stream width and side slope influence the accuracy of the flow estimation model.