• Korean Journal of Remote Sensing
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• v.38 no.5_2
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• pp.765-779
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• 2022

This study evaluates the accuracy in identifying the burned area in South Korea using multi-temporal data from Sentinel-2 MSI and Landsat 8/9 OLI. Spectral indices such as the Difference Normalized Burn Ratio (dNBR), Relative Difference Normalized Burn Ratio (RdNBR), and Burned Area Index (BAI) were used to identify the burned area in the March 2022 forest fire in Uljin. Based on the results of six indices, the accuracy to detect the burned area was assessed for four satellites using Sentinel-2 and Landsat 8/9, respectively. Sentinel-2 and Landsat 8/9 produce images every 16 and 10 days, respectively, although it is difficult to acquire clear images due to clouds. Furthermore, using images taken before and after a forest fire to examine the burned area results in a rapid shift because vegetation growth in South Korea began in April, making it difficult to detect. Because Sentinel-2 and Landsat 8/9 images from February to May are based on the same date, this study is able to compare the indices with a relatively high detection accuracy and gets over the temporal resolution limitation. The results of this study are expected to be applied in the development of new indices to detect burned areas and indices that are optimized to detect South Korean forest fires.

• Korean Journal of Remote Sensing
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• v.37 no.6_3
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• pp.1943-1949
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• 2021

In recent years, as the demand of high-resolution satellite images increases due to the miniaturization and constellation of satellites, various efforts to support users to utilize satellite images more conveniently are performed. Accordingly, the Korea Aerospace Research Institute produces and provides mosaic images on the Korean Peninsula every year to improve the convenience of users in the public sector and activate the use of satellite images. In order to increase the utilization of mosaic images on the Korean Peninsula, a study on satellite image segmentation and classification using mosaic images was attempted. However, since mosaic images provide only R, G, and B bands and processes such as image sharpening and color balancing are applied, there is a limitation that the spectral information of original images is distorted, so various indices were extracted and classified using R, G, and B bands to compensate for this. As a result of the study, the accuracy of image classification results using only mosaic images was about 72%, while the accuracy of image classification results using indices extracted from R, G, and B bands together was about 79%. Through this, it was confirmed that when performing image classification using mosaic images on the Korean Peninsula, the image classification results can be improved if the indices extracted from R, G, and B bands are used together. These research results are expected to be applied not only to mosaic images but also to images in which spectral information is limited or only R, G, and B bands are provided.

• Korean Journal of Remote Sensing
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• v.34 no.6_1
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• pp.1055-1066
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• 2018

Vegetation indices on the basis of optical characteristics of vegetation can represent various conditions such as canopy biomass and physiological activity. Those have been mostly developed with the large-scaled applications of multi-band optical sensors on-board satellites. However, the sensitivity of vegetation indices for detecting vegetation features will be different depending on the spatial scales. Therefore, in this study, the investigation of photochemical reflectance index (PRI), known as one of useful vegetation indices for detecting photosynthetic ability and vegetation stress, under the three spatial scales was conducted using multi-spectral camera installed in unmanned aerial vehicle (UAV),field spectrometer, and leaf reflectometer. In the leaf scale, diurnal PRI had minimum values at different local-time according to the compass direction of leaf face. It meant that each leaf in some moment had the different degree of light use efficiency (LUE). In early growth stage of crop, $PRI_{leaf}$ was higher than $PRI_{stands}$ and $PRI_{canopy}$ because the leaf scale is completely not governed by the vegetation cover fraction.In the stands and canopy scales, PRI showed a large spatial variability unlike normalized difference vegetation index (NDVI). However, the bias for the relationship between $PRI_{stands}$ and $PRI_{canopy}$ is lower than that in $NDVI_{stands}$ and $NDVI_{canopy}$. Our results will help to understand and utilize PRIs observed at different spatial scales.

• Structural Engineering and Mechanics
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• v.39 no.6
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• pp.795-812
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• 2011

Estimation of damage probability of buildings under a future earthquake is an essential issue to ensure the seismic reliability. Fragility curves are useful tools for showing the probability of structural damage due to earthquakes as a function of ground motion indices. The purpose of this study is to compare the damage probability of R/C buildings with low and high level of strength and ductility through fragility analysis. Two different types of sample buildings have been considered which represent the building types mentioned above. The first one was designed according to TEC-2007 and the latter was designed according to TEC-1975. The pushover curves of sample buildings were obtained via pushover analyses. Using 60 ground motion records, nonlinear time-history analyses of equivalent single degree of freedom systems were performed using bilinear hysteretic model and peak-oriented hysteretic model with stiffness - strength deterioration for each scaled elastic spectral displacement. The damage measure is maximum inter-story drift ratio and each performance level considered in this study has an assumed limit value of damage measure. Discrete damage probabilities were calculated using statistical methods for each considered performance level and elastic spectral displacement. Consequently, continuous fragility curves have been constructed based on the lognormal distribution assumption. Furthermore, the effect of hysteresis model parameters on the damage probability is investigated.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.6 no.3
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• pp.9-16
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• 2003

In support of remote sensing applications for monitoring processes of the Earth system, research was conducted to analyze the basic spectral response related to background soil and vegetation cover characteristics in the visible and reflective infrared wavelengths. Surface samples of seven stations were examined. Five soils were from land-field and two soils from tideland areas. The vegetation cover experiment was conducted on seven soil samples with known natural moisture content (%) by weight. To study the effect of vegetation cover, spectral measurements were taken on five or six vegetation cover treatments of the seven soils with 3 replications in air dry conditions. For collecting RS base data, used spectro-radiometer that measures reflection characteristics between 300~1,100nm was used and measured the reflection of vegetation from bean leaves. The relationships were evaluated for both a general soil line and for the individual lines of five soils, under air-dried condition as well as different vegetation cover ratio, through the determination of the line parameters. As vegetation cover ratio in bean leaves increases, features of soil reflectance decrease and those of plant reflectance become more and more apparent. In proportion to vegetation cover rate, near-infrared reflectance increased and visible reflectance decreased. Analysis results are compared to commonly used vegetation indices(RVI and NDVI ).

• The Bulletin of The Korean Astronomical Society
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• v.36 no.2
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• pp.59.1-59.1
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• 2011

I present an analysis of the long-term evolution of the fluxes of six active galactic nuclei (AGN) - 0923+392, 3C 111, 3C 273, 3C 345, 3C 454.3, and 3C 84 - in the frequency range 80 - 267 GHz using archival calibration data of the IRAM Plateau de Bure Interferometer. Our dataset spans a long timeline of ~14 years with 974 - 3027 flux measurements per source. We find strong (factors ~2-8) flux variability on timescales of years for all sources. The flux density distributions of five out of six sources show clear signatures of bi- or even multimodality. Our sources show mostly steep (alpha~0.5-1), variable spectral indices that indicate outflow dominated emission; the variability is most probably due to optical depth variations. The power spectra globally correspond to red-noise spectra with five sources being located between the cases of white and flicker noise and one source (3C 111) being closer to the case of random walk noise. For three sources the low-frequency ends of their power spectra appear to be upscaled in spectral power by factors ~2-3 with respect to the overall powerlaws. We conclude that the source emission cannot be described by uniform stochastic emission processes; instead, a distinction of "quiescent" and (maybe multiple) "flare" states of the source emission appears to be necessary.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.4C
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• pp.232-240
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• 2011

While the water-filling algorithm is an efficient power allocation method that maximizes the ergodic capacity of adaptive MIMO systems, its excessive residual power causes spectrum loss in real systems employing discrete modulation indices. In this paper we propose new power allocation algorithms that improve the spectral efficiency of MIMO systems by efficiently reallocating the residual power of the water-filling algorithm. We apply the proposed algorithms to the adaptive turbo-coded MIMO system to verify their performance through computer simulation in various environments. Simulation results show that the spectral efficiency of the proposed algorithms is better than that of the water-filling algorithm by about 8.9% at SNR of 20dB in Rayleigh fading environments.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.8
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• pp.1507-1514
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• 2015

Non-orthogonal multiple access (NOMA) is a promising candidate for 5G networks. NOMA achieves superior spectral efficiency than conventional orthogonal multiple access (OMA), as in NOMA multiple users uses the same time and frequency resources. Multiple-input-multiple-output (MIMO) is one another promising technique that can enhance system performance. In this paper we present a spectral and energy efficient multiple antenna based NOMA scheme, known as spatially modulated NOMA. In the proposed scheme the cell edge users are multiplexed in spatial domain, which means the information to cell edge users is conveyed using the transmit antenna indices. In NOMA the performance of cell edge users are deeply effected as it treats signals of others as noise. The proposed scheme achieves superior spectral efficiency than the conventional NOMA. The number of decoding steps involved in decoding NOMA signal reduces by one as cell edge user is multiplexed in spatial domain. The proposed scheme is more energy efficient as compare to conventional NOMA. All of the three gains high spectral, energy efficiency and one step reduction in decoding comes at cost of multiple transmit antennas at base station.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.4
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• pp.86-101
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• 2019

Remote sensing technology has been continuously developed both quantitatively and qualitatively, including platform development, exploration area, and exploration functions. Recently, the use cases and related researches in the agricultural field are increasing. Also, since it is possible to detect and quantify the condition of cropland and establish management plans and policy support for cropland and agricultural environment, it is being studied in various fields such as crop growth abnormality determination and crop estimation based on time series information. The purpose of this study was to analyze the vegetation index for agricultural land reclamation area using a UAV equipped with a multi-spectral sensor. In addition, field surveys were conducted to evaluate the accuracy of vegetation indices calculated from multispectral image data obtained using UAV. The most appropriate vegetation index was derived by evaluating the correlation between vegetation index calculated by field survey and vegetation index calculated from UAV multispectral image, and was used to analyze vegetation index of the entire area.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.5
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• pp.123-131
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• 2016

To capture color and near-infrared images simultaneously, a multi-spectral filter array(MSFA) sensor is used. This is because an NIR band gives additional invisible information to human eyes to see subject under extremely low light level. However, because lenses have different refractive indices for different wavelengths, lenses may fail to focus widely different rays to the same convergence point. This is why a chromatic aberration(CA) problem occurs and images are degraded. In this paper, the image restoration algorithm for an MSFA image, which removes the CA problem, is presented. The obtained MSFA image is filtered by the estimated low-pass kernel to generate a base image. This base image is used to remove CA problem in multi-spectral(MS) images. By modeling the image degradation process and by using the least squares approach of the difference between the high-frequencies of the base and MS images, the desired high-resolution MS images are reconstructed. The experimental results show that the proposed algorithm performs well in estimating the high-quality MS images and reducing the chromatic aberration problem.