• Solar Energy
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• v.10 no.3
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• pp.60-65
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• 1990

[ $n^+-p^+$ ] InP homojunction solar cells were fabricated by thermal diffusion of sulphur into a $p^+$-InP wafer($p=4{\times}10^{18}cm^{-3}$), and a SiO film($600{\AA}$ thick) was coated on the $n^+$ layer as an antireflection(AR) coating by an e-beam evaporator. The volume of the cells were $5{\times}5{\times}0.3mm^3$. The front contact grids of the cells with 16 finger pattern of which width and space were $20{\mu}m$ and $300{\mu}m$ respectively, were formed by photo-lithography technique. The junction depth of sulphur were as shallow as about 0.4r m We found out the fabricated solar cells that, with increasing the diffusion time, short circuit current densities($J_{sc}$), series resistances($R_s$) and energy conversion efficiencies(${\eta}$) were increased. The cells show good spectral responses in the region of $5,000-9,000{\AA}$. The short circuit current density, the open circuit voltage( $V_{oc}$), the fill factor(F.F) and the energy conversion efficiency of the cell were $13.16mA/cm^2$, 0.38V, 53.74% and 10.1% respectively.

• Korean Journal of Soil Science and Fertilizer
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• v.34 no.5
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• pp.342-349
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• 2001

This study was carried out to classify and evaluate the land cover map using Landsat TM data in Pyeongtaeg City. DGPS data, aerial photography, topographical map were used for selection the training sets and accuracy assessment. The overall accuracy and Kappa coefficient of the land cover classification map(using supervised classification with 13 classes) with Landsat TM data(16 June. 1997) were respectively, 86.8%, 85.4%, but the user's accuracy of urban/village and vinyl-house was below 60%, and the producer's accuracy of read and vinyl-house below 70%. Maybe it was caused the spectral reflectance characteristics, heterogeneity and small distribution area on the artificial things such as urban/village, vinyl_house and road, etc. And then, the agricultural land cover classification system using remote sensing data in Korea was to classify level I and II. Level I consisted of 5 classes such as agricultural land, forest land, water, barren land, urban and built-up land.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.2
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• pp.89-98
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• 2009

In the field of computer vision, image mosaicking is a common method for effectively increasing restricted the field of view of a camera by combining a set of separate images into a single seamless image. Image mosaicking based on feature points has recently been a focus of research because of simple estimation for geometric transformation regardless distortions and differences of intensity generating by motion of a camera in consecutive images. Yet, since most feature-point matching algorithms extract feature points using gray values, identifying corresponding points becomes difficult in the case of changing illumination and images with a similar intensity. Accordingly, to solve these problems, this paper proposes a method of image mosaicking based on feature points using color information of images. Essentially, the digital values acquired from a digital color camera are converted to values of a virtual camera with distinct narrow bands. Values based on the surface reflectance and invariant to the chromaticity of various illuminations are then derived from the virtual camera values and defined as color-invariant values invariant to changing illuminations. The validity of these color-invariant values is verified in a test using a Macbeth Color-Checker under simulated illuminations. The test also compares the proposed method using the color-invariant values with the conventional SIFT algorithm. The accuracy of the matching between the feature points extracted using the proposed method is increased, while image mosaicking using color information is also achieved.

• Korean Journal of Remote Sensing
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• v.37 no.2
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• pp.177-198
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• 2021

Existing change detection researches have been focused on changes of land use and land cover (LULC), damaged areas, or large vegetated and water regions. On the other hands, increased temporal and spatial resolution of satellite images are strongly suggesting the feasibility of change detection of small objects such as vehicles and ships. In order to check the feasibility, this paper analyzes the performance of existing pixel-based change detection methods over small objects. We applied pixel differencing, PCA (principal component analysis) analysis, MAD (Multivariate Alteration Detection), and IR-MAD (Iteratively Reweighted-MAD) to Kompsat-3A and Google Map images taken within 10 days. We extracted ground references for changed and non-changed small objects from the images and used them for performance analysis of change detection results. Our analysis showed that MAD and IR-MAD, that are known to perform best over LULC and large areal changes, offered best performance over small object changes among the methods tested. It also showed that the spectral band with high reflectivity of the object of interest needs to be included for change analysis.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.409-418
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• 2021

The land cover map is a very important data that is used as a basis for decision-making for land policy and environmental policy. The land cover map is mapped using remote sensing data, and the classification results may vary depending on the acquisition time of the data used even for the same area. In this study, to overcome the classification accuracy limit of single-period data, multi-series satellite images were used to learn the difference in the spectral reflectance characteristics of the land surface according to seasons on a U-Net model, one of the deep learning algorithms, to improve classification accuracy. In addition, the degree of improvement in classification accuracy is compared by comparing the accuracy of single-period data. Seoul, which consists of various land covers including 30% of green space and the Han River within the area, was set as the research target and quarterly Sentinel-2 satellite images for 2020 were aquired. The U-Net model was trained using the sub-class land cover map mapped by the Korean Ministry of Environment. As a result of learning and classifying the model into single-period, double-series, triple-series, and quadruple-series through the learned U-Net model, it showed an accuracy of 81%, 82% and 79%, which exceeds the standard for securing land cover classification accuracy of 75%, except for a single-period. Through this, it was confirmed that classification accuracy can be improved through multi-series classification.

• Korean Journal of Remote Sensing
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• v.26 no.2
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• pp.251-262
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• 2010

In order to provide quantitative control of the standard products of Geostationary Ocean Color Imager (GOCI), on-board radiometric correction, atmospheric correction, and bio-optical algorithm are obtained continuously by comprehensive and consistent calibration and validation procedures. The calibration/validation for radiometric, atmospheric, and bio-optical data of GOCI uses temperature, salinity, ocean optics, fluorescence, and turbidity data sets from buoy and platform systems, and periodic oceanic environmental data. For calibration and validation of GOCI, we compared radiometric data between in-situ measurement and HyperSAS data installed in the Ieodo ocean research station, and between HyperSAS and SeaWiFS radiance. HyperSAS data were slightly different in in-situ radiance and irradiance, but they did not have spectral shift in absorption bands. Although all radiance bands measured between HyperSAS and SeaWiFS had an average 25% error, the 11% absolute error was relatively lower when atmospheric correction bands were omitted. This error is related to the SeaWiFS standard atmospheric correction process. We have to consider and improve this error rate for calibration and validation of GOCI. A reference target site around Dokdo Island was used for studying calibration and validation of GOCI. In-situ ocean- and bio-optical data were collected during August and October, 2009. Reflectance spectra around Dokdo Island showed optical characteristic of Case-1 Water. Absorption spectra of chlorophyll, suspended matter, and dissolved organic matter also showed their spectral characteristics. MODIS Aqua-derived chlorophyll-a concentration was well correlated with in-situ fluorometer value, which installed in Dokdo buoy. As we strive to solv the problems of radiometric, atmospheric, and bio-optical correction, it is important to be able to progress and improve the future quality of calibration and validation of GOCI.

• Korean Journal of Remote Sensing
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• v.31 no.5
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• pp.385-394
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• 2015

Pine wilt disease has greatly damaged pine forests not only in East Asia including South Korea and China, but also in European region. The damage caused by pine wood nematode (Bursaphelenchus xylophilus) is expressed in bundles within stands and rapidly spreading, however, present field survey methods have limitations to detecting damaged trees at regional level. This study extracted the damaged trees by pine wilt disease using time series hyperspectral aerial photographs, and analyzed their distribution characteristics. Hyperspectral aerial photographs of 1 meter spatial resolution were obtained in June, September, and October. Damaged trees by pine wilt disease were extracted using Normalized Difference Vegetation Index (NDVI) and Vegetation Index green (VIgreen) of the September photograph. Among extracted damaged trees, dead trees with leaves and without leaves were classified, and the spectral reflectance values from the photographs obtained in June, September, and October were compared to extract new outbreaks in September and October. Based on the time series dispersion of extracted damaged trees, nearest neighbor analysis was conducted to analyze distribution characteristics of the damaged trees within the region where hyperspectral aerial photographs were acquired. As a result, 2,262 damaged trees were extracted in the study area, and 604 dead trees (dead trees in last year) with leaves in relation to the damaged time and 300 and 101 newly damaged trees in September and October were classified. The result of nearest neighbor analysis using the data shows that aggregated distribution was the dominant pattern both previous and current year in the study area. Also, 80% of the damaged trees in current year were found within 60 m of dead trees in previous year.

• Korean Journal of Remote Sensing
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• v.39 no.6_2
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• pp.1565-1576
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• 2023

An atmospheric correction algorithm based on the radiative transfer model is required to obtain remote-sensing reflectance (R_rs) from the Geostationary Ocean Color Imager-II (GOCI-II) observed at the top-of-atmosphere. This R_rs derived from the atmospheric correction is utilized to estimate various marine environmental parameters such as chlorophyll-a concentration, total suspended materials concentration, and absorption of dissolved organic matter. Therefore, an atmospheric correction is a fundamental algorithm as it significantly impacts the reliability of all other color products. However, in clear waters, for example, atmospheric path radiance exceeds more than ten times higher than the water-leaving radiance in the blue wavelengths. This implies atmospheric correction is a highly error-sensitive process with a 1% error in estimating atmospheric radiance in the atmospheric correction process can cause more than 10% errors. Therefore, the quality assessment of R_rs after the atmospheric correction is essential for ensuring reliable ocean environment analysis using ocean color satellite data. In this study, a Quality Assurance (QA) algorithm based on in-situ R_rs data, which has been archived into a database using Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Bio-optical Archive and Storage System (SeaBASS), was applied and modified to consider the different spectral characteristics of GOCI-II. This method is officially employed in the National Oceanic and Atmospheric Administration (NOAA)'s ocean color satellite data processing system. It provides quality analysis scores for R_rs ranging from 0 to 1 and classifies the water types into 23 categories. When the QA algorithm is applied to the initial phase of GOCI-II data with less calibration, it shows the highest frequency at a relatively low score of 0.625. However, when the algorithm is applied to the improved GOCI-II atmospheric correction results with updated calibrations, it shows the highest frequency at a higher score of 0.875 compared to the previous results. The water types analysis using the QA algorithm indicated that parts of the East Sea, South Sea, and the Northwest Pacific Ocean are primarily characterized as relatively clear case-I waters, while the coastal areas of the Yellow Sea and the East China Sea are mainly classified as highly turbid case-II waters. We expect that the QA algorithm will support GOCI-II users in terms of not only statistically identifying R_rs resulted with significant errors but also more reliable calibration with quality assured data. The algorithm will be included in the level-2 flag data provided with GOCI-II atmospheric correction.

• Journal of the Mineralogical Society of Korea
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• v.16 no.4
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• pp.333-339
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• 2003

A new mineral, Zn analogue of rancieite (Chimooite), has been discovered at the Dongnam mine, Korea. It occurs as compact subparallel fine­grained flaky or acicular aggregates in the massive manganese oxide ores which were formed by supergene oxidation of rhodochrosite­sulfide ores in the hydrothermal veins trending NS­N25E and cutting the Pungchon limestone of the Cambrian age. The flakes of chimooite are 0.2 mm for the largest one, but usually less than 0.05 mm. The acicular crystals are elongated parallel to and flattened on (001). This mineral shows gradation to rancieite constituting its marginal part, thus both minerals are found in one and the same flake. Color is bluish black, with dull luster and brown streak in globular or massive aggregates. Cleavage is perfect in one direction. The hardness ranges from 2.5 to 4. Under reflected light it is anisotropic and bireflectant. It shows reddish brown internal reflection. Chemical analyses of different parts of both minerals suggest that rancieite and chimooite constitute a continuous solid solution series by cationic substitution. The empirical chemical formula for chimooite has been calculated following the general formula, $R_2_{x}$ M $n^{4+}$$_{9­x}$ $O_{18}$ $.$n$H_2O$ for the 7 $\AA$ phyllomanganate minerals, where x varies from 0.81 to 1.28 in so far studied samples, thus averaging to 1.0. Therefore, the formula of Zn­rancieite is close to the well­known strochiometric formula $_Mn_4^{4+}$ $O_{9}$ $.$4$H_2O$. The mineral has the formula (Z $n_{0.78}$N $a_{0.15}$C $a_{0.08}$M $g_{0.01}$ $K_{0.01}$)(M $n^{4+}$$_{3.98}$F $e^{3+}$$_{0.02}$)$_{4.00}$ $O_{9}$ $.$3.85$H_2O$, thus the ideal formula is (Zn,Ca)M $n^{4+}$$_4$ $O_{9}$ $.$3.85$H_2O$. The mineral has a hexagonal unit ceil with a=2.840 $\AA$ c=7.486 $\AA$ and a : c = 1 : 2.636. The DTA curve shows endothermic peaks at 65, 180, 690 and 102$0^{\circ}C$. The IR absorption spectrum shows absorption bands at 445, 500, 1630 and 3400 c $m^{1}$. The mineral name Chimooite has been named in honour of late Prof, Chi Moo Son of Seoul National University.ity.versity.ity.y.

• Clean Technology
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• v.25 no.1
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• pp.46-55
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• 2019

CdS and CdZnS/ZnO materials were prepared using precipitation method and used as photocatalysts for the photocatalytic degradation of rhodamine B (RhB) under visible light irradiation. The prepared photocatalysts were also characterized by XRD and UV-vis DRS. The results indicated that the photocatalysts with intended crystalline structures were successfully obtained and both the CdS and CdZnS/ZnO can absorb visible light as well as UV. The photocatalytic activities were examined with the addition of scavenger for various active chemical species and the difference of reaction mechanisms over the catalysts were discussed. The $CH_3OH$, KI and p-benzoquinone were used as scavengers for ${\cdot}OH$ radical, photogenerated positive hole and ${\cdot}O_2{^-}$ radical, respectively. The CdS and CdZnS/ZnO showed different photocatalytic degradation mechanisms of RhB. It can be postulated that ${\cdot}O_2{^-}$ radical is the main active species for the reaction over CdS photocatalyst, while the photogenerated positive hole for CdZnS/ZnO photocatalyst. As a result, the predominant reaction pathways over CdS and CdZnS/ZnO photocatalysts were found to be the dealkylation of chromophore skeleton and the cleavage of the conjugated chromophore structure, respectively. The above results may be mainly ascribed to the difference of band edge potential of conduction and valence bands in CdS, CdZnS and ZnO semiconductors and the redox potentials for formation of active chemical species.