• The Bulletin of The Korean Astronomical Society
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• v.40 no.1
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• pp.78.3-78.3
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• 2015

About 70 high redshift quasars with $z{\geq}5$ have been discovered through combinations of standard broad-band filters to distinguish them from contaminating sources. However, among the discovered quasars so far, there is a redshift gap at $5{\leq}z{\leq}6$ due to the limitation of traditional filter sets and selection techniques. To understand the early mass growth of supermassive black holes and the final stage of the cosmic reionization, it is important to find a statistically meaningful sample of quasars with various physical properties. Here we suggest a new selection technique of high redshift quasars using medium-band filters: nine filters with bandwidths of 50nm and central wavelengths from 625 to 1025nm. Photometry with these medium-bands traces the spectral energy distribution (SED) of a source, similar to spectroscopy with R~15. We installed these filters to SED camera for QUasars in EArly uNiverse (SQUEAN) on the 2.1m telescope at McDonald Observatory, and conducted test observations of known high redshift quasars at $4.7{\leq}z{\leq}6.1$ and also dwarf stars for comparison. We found differences in SED shapes between high redshift quasars and dwarf stars, determined their locations on color-color diagrams, and demonstrated that the medium-band filters can enhance the efficiency of selecting robust quasar candidates in this redshift range. In this poster, we propose an effective selection method of high redshift quasars using these medium-band filters and discuss its effect on our high redshift quasar survey.

• Korean Journal of Remote Sensing
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• v.35 no.6_3
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• pp.1299-1312
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• 2019

As land remote sensing applications are expanding to the extraction of quantitative information, the importance of atmospheric correction is increasing. Considering the difficulty of atmospheric correction for land images, it should be applied when it is necessary. The quantitative information extraction and time-series analysis on biophysical variables in land surfaces are two major applications that need atmospheric correction. Atmospheric aerosol content and column water vapor, which are very dynamic in spatial and temporal domain, are the most influential elements and obstacles in retrieving accurate surface reflectance. It is difficult to obtain aerosol and water vapor data that have suitable spatio-temporal scale for high- and medium-resolution multispectral imagery. Selection of atmospheric correction method should be based on the availability of appropriate aerosol and water vapor data. Most atmospheric correction of land imagery assumes the Lambertian surface, which is not the case for most natural surfaces. Further BRDF correction should be considered to remove or reduce the anisotropic effects caused by different sun and viewing angles. The atmospheric correction methods of optical imagery over land will be enhanced to meet the need of quantitative remote sensing. Further, imaging sensor system may include pertinent spectral bands that can help to extract atmospheric data simultaneously.

• Korean Journal of Optics and Photonics
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• v.13 no.1
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• pp.1-8
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• 2002

Optical payloads for earth-observation satellites become bigger as the required resolution becomes finer. For example, the diameter of the primary mirror of IKONOS, which has ground sampling distances of 1m/4m in panchromatic/multi spectral bands, is about 700mm. As the size of optical payload becomes bigger, the light-weighting of the mirrors becomes more significant. This paper presents the FEM results of the following four mirror types of 300 m diameter under gravity release and temperature changes: flat back mirror, single arch mirror, double arch mirror, and honeycomb sandwich mirror. Furthermore, this paper extends the FEM results to larger mirrors up to the diameter of 1m based on a general scaling law and Valenete\`s equation.

• The Bulletin of The Korean Astronomical Society
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• v.38 no.2
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• pp.84.1-84.1
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• 2013

We present a python-based data reduction pipeline for the Immersion GRating INfrared Spectrograph (IGRINS). IGRINS covers the complete H- and K-bands in a single exposure with a spectral resolving power of greater than 40,000. IGRINS is designed to be compatible with telescopes of diameters ranging from 2.7-m (the Harlan J. Smith telescope at McDonald Observatory) to 8-10m. Commissioning and initial operation will be on the 2.7-m telescope from late 2013. The pipeline package is a part of the IGRINS software and designed to be compatible with other package that maneuvers the spectrograph during the observation. This package provides high-quality spectra with minimal human intervention and the processes of order extraction, distortion correction, and wavelength calibration can be automatically carried out using the predefined functions (e.g. echellogram mapping and 2D transform). Since the IGRINS is a prototype of the Giant Magellan Telescope Near-Infrared Spectrometer (GMTNIRS), this pipeline will be extended to the GMTNIRS software.

• Publications of The Korean Astronomical Society
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• v.32 no.1
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• pp.257-261
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• 2017

We built a $8{\mu}m$ selected sample of galaxies in the NEP-AKARI field by defining 4 redshift bins with the four AKARI bands at 11, 15, 18 and 24 microns (0.15 < z < 0.49, 0.75 < z < 1.34, 1.34 < z < 1.7 and 1.7 < z < 2.05). Our sample contains 4079 sources, 599 are securely detected with Herschel/PACS. Also adding ultraviolet (UV) data from GALEX, we fit the spectral energy distributions using the physically motivated code CIGALE to extract the star formation rate, stellar mass, dust attenuation and the AGN contribution to the total infrared luminosity ($L_{IR}$). We discuss the impact of the adopted attenuation curve and that of the wavelength coverage to estimate these physical parameters. We focus on galaxies with a luminosity close the characteristic $L^*_{IR}$ in the different redshift bins to study the evolution with redshift of the dust attenuation in these galaxies.

• Publications of The Korean Astronomical Society
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• v.32 no.1
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• pp.131-133
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• 2017

We present the latest results from the Mission Program NIRLT (PI: I.Yamamura), the near-infrared spectroscopy of brown dwarfs using the AKARI/IRC grism mode with the spectral resolution of ~ 120. The near-infrared spectra in the wavelength range between 2.5 and $5.0{\mu}m$ are especially important to study the brown dwarf atmospheres because of the presence of major molecular bands, including $CH_4$ at $3.3{\mu}m$, $CO_2$ at $4.2{\mu}m$, CO at $4.6{\mu}m$, and $H_2O$ around $2.7{\mu}m$. We observed 27 sources, and obtained 16 good spectra. Our model fitting reveals deviations between theoretical model and observed spectra in this wavelength range, which may be attributed to the physical condition of the upper atmosphere. The deviations indicate additional heating, which we hypothesize to be due to chromospheric activity. We test this effect by modifying the brown dwarf atmosphere model to artificially increase the temperature of the upper atmosphere, and compare the revised model with observed spectra of early- to mid-L type objects with $H{\alpha}$ emission. We find that the chemical structure of the atmosphere changes dramatically, and the heating model spectra of early-type brown dwarfs can be considerably improved to match the observed spectra. Our result suggests that chromospheric activity is essential to understand early-type brown dwarf atmospheres.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.2
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• pp.165-172
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• 2013

In this paper, high-quality mosaic image is generated by high-resolution hyperspectral strip images using scale-invariant feature transform (SIFT) algorithm, which is one of the representative image matching methods. The experiments are applied to AISA Eagle images geo-referenced by using GPS/INS information acquired when it was taken on flight. The matching points between three strips of hyperspectral images are extracted using SIFT method, and the transformation models between images are constructed from the points. Mosaic image is, then, generated using the transformation models constructed from corresponding images. Optimal band appropriate for the matching point extraction is determined by selecting representative bands of hyperspectral data and analyzing the matched results based on each band. Mosaic image generated by proposed method is visually compared with the mosaic image generated from initial geo-referenced AISA hyperspectral images. From the comparison, we could estimate geometrical accuracy of generated mosaic image and analyze the efficiency of our methodology.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.142-145
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• 2005

Since the successful launch of FORMOSAT -2 satellite by National Space Organization of Taiwan in May 2004, the Remote Sensing Instrument (RSI) on- board the FORMOSAT -2 has continuously acquired images at one panchromatic and four multi-spectral bands (http://www.nspo.org.tw). In general, the RSI performs well and receives high quality images which proved to be very useful for various applications. However, some RSI panchromatic products exhibit obvious trembling artifact that must be removed. Preliminary study reveals that the trembling artifact is caused by the instability of the spacecraft attitude. Though the magnitude of this artifact is actually less than half of a pixel, it affects the applicability of panchromatic products. A procedure removing this artifact is therefore needed for providing image products of consistent quality. Due to the nature of trembling artifact, it is impossible to describe the trembling amount by employing an analytic model. Relied only on image itself, an algorithm determining trembling amount and removing accordingly the trembling artifact is proposed. The algorithm consists of 3 stages. First, a cross-correlation based scheme is used to measure the relative shift between adjacent scan lines. Follows, the trembling amount is estimated from the measured value. For this purpose, the Fourier transform is utilized to characterize random shifts in frequency domain. An adaptive estimation method is then applied to deduce the approximate trembling amount. In the subsequent stage, image re-sampling operation is applied to restore the trembling-free product. Experimental results show that by applying the proposed algorithm, the unpleasant trembling artifact is no longer evident.

• Korean Journal of Remote Sensing
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• v.29 no.6
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• pp.611-619
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• 2013

Although the need of crop production has increased in Mongolia, crop cultivation is very limited because of the harsh climatic and topographic conditions. Crop lands are sparsely distributed with relatively small sizes and, therefore, it is difficult to survey the exact area of crop lands. The study aimed to find an easy and effective way of accurate classification to map crop lands in Mongolia using satellite images. To classify the crop lands over the study area in northern Mongolia, four classifications were carried out by using 1) Thematic Mapper (TM) image August 23, 2) TM image of July 6, 3) combined 12 bands of TM images of July and August, and 4) both TM images of July and August by layered classification. Wheat and potato are the major crop types and they show relatively high variation in crop conditions between July and August. On the other hands, other land cover types (forest, riparian vegetation, grassland, water and bare soil) do not show such difference between July and August. The results of four classifications clearly show that the use of multi-temporal images is essential to accurately classify the crop lands. The layered classification method, in which each class is separated by a subset of TM images, shows the highest classification accuracy (93.7%) of the crop lands. The classification accuracies are lower when we use only a single TM image of either July or August. Because of the different planting practice of potato and the growth condition of wheat, the spectral characteristics of potato and wheat cannot be fully separated from other cover types with TM image of either July or August. Further refinements on the spatial characteristics of existing crop lands may enhance the crop mapping method in Mongolia.

• KIISE Transactions on Computing Practices
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• v.23 no.3
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• pp.141-147
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• 2017

Recently there has been an increasing demand for developing a domestic software (S/W) for infrared signature generation to prevent technology leakage and match the domestic operating environment. In this study, we developed a S/W for infrared signature generation and presented its structures and functions for creating and analyzing the IR images of designated spectral bands. The proposed S/W generates IR images of an object through calculations of surface temperatures and IR signals including the self-emitted, surface reflected and path dependent radiances. Moreover, the proposed S/W includes the features of infrared threat analyses from the generated IR images including the infrared contrast radiant intensity (CRI), detection ranges or detection probability analyses, unlike the imported, commercial infrared signature generation S/W.