• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.187-190
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• 2007

The Geostationary Ocean Color Imager (GOCI) is under development to provide a monitoring of ocean-color around the Korean Peninsula from geostationary platforms. It is planned to be loaded on Communication, Ocean, and Meteorological Satellite (COMS) of Korea. The GOCI has been designed to provide multi-spectral data to detect, monitor, quantify, and predict short term changes of coastal ocean environment for marine science research and application purpose. The target area of GOCI observation covers sea area around the Korean Peninsula. Based on the nonlinear radiometric model, the GOCI calibration method has been derived. The nonlinear radiometric model for GOCI will be validated through ground test. The GOCI radiometric calibration is based on on-board calibration devices; solar diffuser, DAMD (Diffuser Aging Monitoring Device). In this paper, the GOCI radiometric error propagation is analyzed. The radiometric model error due to the dark current nonlinearity is analyzed as a systematic error. Also the offset correction error due to gain/offset instability is considered. The radiometric accuracy depends mainly on the ground characterization accuracies of solar diffuser and DAMD.

• Bulletin of the Korean Chemical Society
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• v.30 no.11
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• pp.2735-2738
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• 2009

A simple colorimetric anion chemosensor based on 2-amino-6-nitrobenzothiazole was synthesized. The addition of tetrabutylammonium (TBA) salts of $F^-,\;{CH_3COO}^-,\;and\;{H_2PO_4}^-$ to the solution of receptor 3 caused dramatic and clearly observable color changes from light to dark yellow due to the deprotonation process which is totally different from previously reported receptors based on the same motif. According to the basicity of the anions, the sensitivity of receptor 3 towards various anions decreased in the following order: ${CH_3COO}^-\;>\;F^-\;>\;{H_2PO_4}^-$.

• Proceedings of the KSRS Conference
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• 2009.03a
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• pp.82-86
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• 2009

원격탐사 근적외선(NIR)과 Red 밴드의 반사도로부터 계산되는 정규식생지수(NDVI)는 구름에 오염된 곳에서는 실제보다 낮은 값으로 계산된다. 식생지수에서 구름오염 문제를 극복하는 기존의 대표적인 방법에는 보름 정도 장기간 식생지수 값 중에서 최대인 값을 취하는 MVC(Maximum Value Composite) 방법이 있다. 하지만 MVC 방법으로는 식생지수의 단기간 변동을 파악할 수 없으며, 장기간 계속 구름으로 오염된 곳은 잘못된 식생지수 값으로 계산되는 문제점이 있다. 가시광 RGB 자료로부터 snapshot 영상자료의 구름을 마스크(mask)하는 새로운 방법인 CIM(Color Index Manipulation) 알고리즘을 개발하였다. 이 알고리즘을 사용하면 snapshot 영상자료에서 구름에 오염된 곳은 제외하고 오염되지 않은 곳에 대한 식생지수를 계산할 수 있다. RGB 자료에 대한 정규색상지수 NCI (Normalized Color Index) 3개 성분을 $120^{\circ}$ 간격으로 벌어진 3개 축상의 좌표로 나타낸 후 이들 3개 값의 벡터합(vector sum) 정보를 이용하여 구름을 식별하는 CIM 방법으로 위성영상에서 두꺼운 구름과 않은 구름을 구분하여 식별할 수 있다. 이 구름식별 기법을 MODIS snapshot 위성영상 자료에 적용하여 한반도의 일별(daily) 식생지수 자료를 계산하였다. 그리고 수년간의 일별 식생지수 자료로부터 한반도 식생지수의 계절적 변동을 조사하였다.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.724-726
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• 2003

Currently available image fusion methods are not efficient for fusing the Landsat 7 images. Significant color distortion is one of the major problems. In this paper, using the well-known wavelet based method for data fusion between high-resolution panchromatic and low-resolution multispectral satellite images, we performed Landsat 7 image fusion. Based on the experimental results obtained from this study, we analyzed some reasons for color distortion. A new approach using the biorthogonal wavelets based method for data fusion is presented. This new method has reached an optimum fusion result - with the same spectral resolution as the multispectral image and the same spatial resolution as the panchromatic image with minimum artifacts.

• Korean Journal of Remote Sensing
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• v.39 no.6_2
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• pp.1651-1669
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• 2023

Sea ice currently covers approximately 7% of the world's ocean area, primarily concentrated in polar and high-altitude regions, subject to seasonal and annual variations. It is very important to analyze the area and type classification of sea ice through time series monitoring because sea ice is formed in various types on a large spatial scale, and oil and gas exploration and other marine activities are rapidly increasing. Currently, research on the type and area of sea ice is being conducted based on high-resolution satellite images and field measurement data, but there is a limit to sea ice monitoring by acquiring field measurement data. High-resolution optical satellite images can visually detect and identify types of sea ice in a wide range and can compensate for gaps in sea ice monitoring using Geostationary Ocean Color Imager-II (GOCI-II), an ocean satellite with short time resolution. This study tried to find out the possibility of utilizing sea ice monitoring by training a rule-based machine learning model based on learning data produced using high-resolution optical satellite images and performing detection on GOCI-II images. Learning materials were extracted from Liaodong Bay in the Bohai Sea from 2021 to 2022, and a Random Forest (RF) model using GOCI-II was constructed to compare qualitative and quantitative with sea ice areas obtained from existing normalized difference snow index (NDSI) based and high-resolution satellite images. Unlike NDSI index-based results, which underestimated the sea ice area, this study detected relatively detailed sea ice areas and confirmed that sea ice can be classified by type, enabling sea ice monitoring. If the accuracy of the detection model is improved through the construction of continuous learning materials and influencing factors on sea ice formation in the future, it is expected that it can be used in the field of sea ice monitoring in high-altitude ocean areas.

• Korean Journal of Remote Sensing
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• v.28 no.4
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• pp.421-434
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• 2012

Colored Dissolved Organic Matter (CDOM) is one of the important components of optical properties of seawater to determine ecosystem dynamics in a given marine area. The optical characteristics of CDOM may depend on the various ecosystem and environmental variables in the sea and those variables may vary region to region. Therefore, the retrieval algorithm for determining light absorption coefficient of CDOM ($a_{CDOM}$) using satellite remote sensing reflectance ($R_{rs}$) developed from other region may not be directly applicable to the other region, and it must be validated using an in-situ ground-truth observation. We have tested 6 known CDOM algorithms (three Semi-analytical and three Empirical CDOM algorithms) developed from other regions of the world ocean with laboratory determined in-situ values for the East Sea using field data collected during seven oceanographic cruises in the period of 2009~2011. Our field measurements extended from the coastal waters to the open oceanic type CASE-1 Waters. Our study showed that Quasi-Analytical Algorithm (QAA_v5) derived $a_{CDOM}$(412) appears to match in-situ $a_{CDOM}$(412) values statistically. Semi-analytical algorithms appeared to underestimate and empirical ones overestimated $a_{CDOM}$ in the East Sea. $a_{CDOM}$(412) value was found to be relatively high in the relatively high satellite derived-chlorophyll-a area. $a_{CDOM}$(412) value appears to be influenced by the amount of chlorophyll-a in seawater. The outcome of this work may be referenced to develop $a_{CDOM}$ algorithm for the new Korean Geostationary Ocean Color Imager (GOCI).

• Journal of Sensor Science and Technology
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• v.29 no.2
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• pp.93-99
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• 2020

A colorimetric paper sensor was used to detect volatile nitrogen-containing compounds emitted from spoiled salmon filets to determine their freshness. The sensing mechanism was based on acid-base reactions between acidic pH-indicating dyes and basic volatile ammonia and amines. A sensing layer was simply fabricated by drop-casting a dye solution of bromocresol green (BCG) on a polyvinylidene fluoride substrate, and its color-change response was enhanced by optimizing the amounts of additive chemicals, such as polyethylene glycol, p-toluene sulfonic acid, and graphene oxide in the dye solution. To avoid the adverse effects of water vapor, both faces of the sensing layer were enclosed by using a polyethylene terephthalate film and a gas-permeable microporous polytetrafluoroethylene sheet, respectively. When exposed to basic gas analytes, the paper-like sensor distinctly exhibited a color change from initially yellow, then to green, and finally to blue due to the deprotonation of BCG via the Brønsted acid-base reaction. The use of ammonia analyte as a test gas confirmed that the sensing performance of the optimized sensor was reversible and excellent (detection time of < 15 min, sensitive naked-eye detection at 0.25 ppm, good selectivity to common volatile organic gases, and good stability against thermal stress). Finally, the coloration intensity of the sensor was quantified as a function of the storage time of the salmon filet at 28℃ to evaluate its usefulness in monitoring of the food freshness with the measurement of the total viable count (TVC) of microorganisms in the food. The TVC value increased from 3.2 × 10⁵ to 3.1 × 10⁹ cfu/g in 28 h and then became stable, whereas the sensor response abruptly changed in the first 8 h and slightly increased thereafter. This result suggests that the colorimetric response could be used as an indicator for evaluating the degree of decay of salmon induced by microorganisms.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.101-103
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• 2005

Vicarious calibration method using MODIS-derived surface reflectivity data as inputs to a radiative transfer model have been developed for the planned COMS solar channel. Pilot test was conduced over the Simpson Desert targets in Australia. Results suggested that calibration can be achieved within $5\%$ error range.

• Proceedings of the Polymer Society of Korea Conference
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• 2006.10a
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• pp.33-34
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• 2006

The graft copolymer consisting of poly(N-isopropylacrylamide) (PNIPAAm) and single-stranded DNA was prepared. Interestingly, the copolymer was found to form nanoparticles above physiological temperature. We found that non-crosslinking aggregation of the nanoparticles was induced by the hybridization of the surface-bound DNA with the full-match complementary DNA, but not with one-base mismatch. The core material is not restricted to PNIPAAm; DNA-functionalized gold nanoparticle was found to show a similar aggregation induced only by the fully-complementary DNA, resulting in rapid color change within 3 min at ambient temperature. This methodology is general in principle and applicable for wide variety of clinical gene diagnosis.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.191-194
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• 2007

The paper clarifies all the noise sources of a CMOS image sensor, with which the GOCI (Geostationary Ocean Color Imager) is equipped, and analyzes their contribution to a nonlinear image sensor model. In particular, the noise PDF (Probability Density Function) is derived in terms of sensor-gain coefficients: a linear and a nonlinear gains. As a result, the relation between the noise characteristic and the sensor gains is studied.