• Kyungpook Mathematical Journal
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• v.50 no.1
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• pp.15-35
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• 2010

By strengthening dichotomy condition and weakening decay conditions, we show that a four term 2n-th order differential operator with unbounded coefficients is nonlimit-point. Using stringent conditions we show that the deficiency index of this operator is determined by the behaviour of the coefficients themselves. Similarly, we prove the absence of singular continuous spectrum and that the absolutely continuous spectrum has multiplicity two.

• Publications of The Korean Astronomical Society
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• v.2 no.1
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• pp.39-46
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• 1985

We analyzed the reddening of 873 bright G and K stars from the DDO photometry in combination with MK spectral classes and (B-V) colors. About a quarter of the sample stars have DDO indices beyond the limits of DDO calibrations. To extend the reddening determination to all stars, we applied a scheme for reddening determination of field G and K stars by using the DDO calibrations (Janes 1977, 1979b) and MK-(B-V) relation of FitzGerald (1970).

• The Bulletin of The Korean Astronomical Society
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• v.41 no.2
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• pp.33.1-33.1
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• 2016

We report detection of short-term flux variability in multi-epoch observations and intraday variability in polarized emission at millimeter-wavelength from S5 0716+714 using Korean VLBI Network (KVN) radio telescopes. Over the whole observation epochs, the source shows significant inter-month variations at K- and Q-band with modulation indices of 19% at K-band and 36% at Q-band. In each epoch, the source shows monotonic flux increase in Epoch 1 and 3, and monotonic flux decrease in Epoch 2 and 4. We found an inverted spectrum with mean spectral indices of -0.57 in Epoch 1 and -0.15 in Epoch. On the contrary, we found relatively steep indices of 0.24 and 0.17 in Epoch 2 and Epoch 4, respectively. In the study of intraday variability of polarization, we found significant variations in the degree of linear polarization at 86 GHz, and in polarization angle at 43 and 86 GHz during ~10 h. The spectrum of the source is quite flat with spectral indices of -0.07 to 0.07 at 22-43 GHz and -0.23 to 0.04 at 43-86 GHz. The measured degree of the linear polarization ranges from 2.3% to 3.3 % at 22 GHz, from 0.9% to 2.2 % at 43 GHz and from 0.4 % to 4.0 % at 86 GHz, yielding prominent variations at 86 GHz over 4-5 h. The linear polarization angle is in the range of 4 to $12^{\circ}$ at 22 GHz, -39 to $81^{\circ}$ at 43 GHz, and 66 to 119 at 86 GHz with a maximum rotation of $110^{\circ}$ at 43 GHz over ~4 h. We estimated the Faraday rotation measures (RM) ranging from -9200 to 6300 rad m-2 between 22 and 43 GHz, and from -71000 to 7300 rad m-2 between 43 and 86 GHz, respectively. The frequency dependency of RM was investigated, yielding a mean power-law index, a, of 2.0. This implies that the polarized emission from S5 0716+714 at 22-86 GHz moves through a Faraday screen in or near the jet of the source.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.419-430
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• 2021

Remote sensing techniques using drone-based multispectral image were studied for fast and two-dimensional monitoring of algal blooms in the river. Drone is anticipated to be useful for algal bloom monitoring because of easy access to the field, high spatial resolution, and lowering atmospheric light scattering. In addition, application of multispectral sensors could make image processing and analysis procedures simple, fast, and standardized. Spectral indices derived from the active spectrum of photosynthetic pigments in terrestrial plants and phytoplankton were tested for estimating chlorophyll-a concentrations (Chl-a conc.) from drone-based multispectral image. Spectral indices containing the red-edge band showed high relationships with Chl-a conc. and especially, 3-band model (3BM) and normalized difference chlorophyll index (NDCI) were performed well (R²=0.86, RMSE=7.5). NDCI uses just two spectral bands, red and red-edge, and provides normalized values, so that data processing becomes simple and rapid. The 3BM which was tuned for accurate prediction of Chl-a conc. in productive water bodies adopts originally two spectral bands in the red-edge range, 720 and 760 nm, but here, the near-infrared band replaced the longer red-edge band because the multispectral sensor in this study had only one shorter red-edge band. This index is expected to predict more accurately Chl-a conc. using the sensor specialized with the red-edge range.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.49 no.2
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• pp.83-89
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• 2012

Natural Vegetation cover, which is very important earth resource, has been significantly altered by humans in some manner. Since this has currently resulted in a significant effect on global climate, various studies on vegetation environment including forest have been performed and the results are utilized in policy decision making. Remotely sensed data can detect, identify and map vegetation cover change based on the analysis of spectral characteristics and thus are vigorously utilized for monitoring vegetation resources. Among various vegetation indices extracted from spectral reponses of remotely sensed data, NDVI is the most popular index which provides a measure of how much photosynthetically active vegetation is present in the scene. In this study, for change detection in vegetation cover, a Multi-layer Perceptron Network (MLPN) as a nonparametric approach has been designed and applied to MODIS/Aqua vegetation indices 16-day L3 global 250m SIN Grid(v005) (MYD13Q1) data. The feature vector for change detection is constructed with the direct NDVI diffenrence at a pixel as well as the differences in some subset of NDVI series data. The research covered 5 years (2006-20110) over Korean peninsular.

• Korean Journal of Soil Science and Fertilizer
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• v.47 no.3
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• pp.217-224
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• 2014

Ground-based remote sensing can be used as one of the non-destructive, fast, and real-time diagnostic tools for predicting yield, biomass, and nitrogen stress during growing season. The objectives of this study were: 1) to assess biomass and nitrogen (N) status of tobacco (Nicotiana tabacum L.) plants under N stress using ground-based remote sensors; and 2) to evaluate the feasibility of spectral reflectance indices for estimating an application rate of N and predicting yield of tobacco. Dry weight (DW), N content, and N uptake at the 40th and 50th day after transplanting (DAT) were positively correlated with chlorophyll content and normalized difference vegetation indexes (NDVIs) from all sensors (P<0.01). Especially, Green NDVI (GNDVI) by spectroradiometer and Crop Circle-passive sensors were highly correlated with DW, N content and N uptake. The yield of tobacco was positively correlated with canopy reflectance indices measured at each growth stage (P<0.01). The regression of GNDVI by spectroradiometer on yield showed positively quadratic curve and explained about 90% for the variability of measured yield. The sufficiency index (SI) calculated from data/maximum value of GNDVI at the $40^{th}$ DAT ranged from 0.72 to 1.0 and showed the same positively quadratic regression with N application rate explaining 84% for the variability of N rate. These results suggest that use of reflectance indices measured with ground-based remote sensors may assist in determining application rate of fertilizer N at the critical season and estimating yield in mid-season.

• Journal of Biosystems Engineering
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• v.43 no.2
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• pp.138-147
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• 2018

Purpose: A narrowband hyperspectral imaging sensor of high-dimensional spectral bands is advantageous for identifying the reflectance by selecting the significant spectral bands for predicting crop yield over the broadband multispectral imaging sensor for each wavelength range of the crop canopy. The images acquired by each imaging sensor were used to develop the models for predicting the Chinese cabbage yield. Methods: The models for predicting the Chinese cabbage (Brassica campestris L.) yield, with multispectral images based on unmanned aerial vehicle (UAV), were developed by simple linear regression (SLR) using vegetation indices, and forward stepwise multiple linear regression (MLR) using four spectral bands. The model with hyperspectral images based on the ground were developed using forward stepwise MLR from the significant spectral bands selected by dimension reduction methods based on a partial least squares regression (PLSR) model of high precision and accuracy. Results: The SLR model by the multispectral image cannot predict the yield well because of its low sensitivity in high fresh weight. Despite improved sensitivity in high fresh weight of the MLR model, its precision and accuracy was unsuitable for predicting the yield as its $R^2$ is 0.697, root-mean-square error (RMSE) is 1170 g/plant, relative error (RE) is 67.1%. When selecting the significant spectral bands for predicting the yield using hyperspectral images, the MLR model using four spectral bands show high precision and accuracy, with 0.891 for $R^2$, 616 g/plant for the RMSE, and 35.3% for the RE. Conclusions: Little difference was observed in the precision and accuracy of the PLSR model of 0.896 for $R^2$, 576.7 g/plant for the RMSE, and 33.1% for the RE, compared with the MLR model. If the multispectral imaging sensor composed of the significant spectral bands is produced, the crop yield of a wide area can be predicted using a UAV.

• Korean Journal of Remote Sensing
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• v.28 no.6
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• pp.597-609
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• 2012

Leaf area index (LAI) is important in explaining the ability of the crop to intercept solar energy for biomass production and in understanding the impact of crop management practices. This paper describes a procedure for estimating LAI as a function of image-derived vegetation indices from temporal series of IKONOS, Landsat TM, and MODIS satellite images using empirical models and demonstrates its use with data collected at Missouri field sites. LAI data were obtained several times during the 2002 growing season at monitoring sites established in two central Missouri experimental fields, one planted to soybean (Glycine max L.) and the other planted to corn (Zea mays L.). Satellite images at varying spatial and spectral resolutions were acquired and the data were extracted to calculate normalized difference vegetation index (NDVI) after geometric and atmospheric correction. Linear, exponential, and expolinear models were developed to relate temporal NDVI to measured LAI data. Models using IKONOS NDVI estimated LAI of both soybean and corn better than those using Landsat TM or MODIS NDVI. Expolinear models provided more accurate results than linear or exponential models.

• The Bulletin of The Korean Astronomical Society
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• v.39 no.1
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• pp.61.2-61.2
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• 2014

We present a set of fiducial sequences of horizontal-branch stars in bright Galactic globular clusters, which have previously been observed in the Sloan Digital Sky Survey (SDSS). We derive fiducial lines on color-magnitude diagrams in multiple color indices (g - r, g - i, g - z, and u - g), after rejecting foreground and background objects as well as RR Lyrae variables utilizing these color indices. We compare our fiducial sequences with model predictions from Yonsei-Yale evolutionary tracks and BaSel spectral libraries, and find a satisfactory agreement between them in terms of their color-magnitude relations, except in u - g. We also compare theoretical models to color-magnitude diagrams of two open clusters (M67 and NGC 6791). Based on our best available cluster distance and reddening, we find that the mass of red clump (RC) stars in NGC 6791 is about a factor of two smaller than an earlier estimate from the application of asteroseismic scaling relations for solar-like oscillations. The smaller RC mass implies an enhanced mass loss along the red giant branch, which is in accordance with other compelling evidences found in this metal-rich system. Our estimated luminosity of RC stars in NGC 6791 is about 0.2 mag fainter than in earlier investigations based on solar-metallicity calibrations, and results in ~10% reduction in the RC-based distance estimation, when applied to metal-rich systems such as in the Galactic bulge.

• 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.