• Korean Journal of Remote Sensing
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• v.32 no.6
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• pp.681-691
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• 2016

Using various satellite measurements in UV, visible and IR, diverse algorithms to retrieve aerosol information have been developed and operated to date. Advanced Himawari Imager (AHI) onboard the Himawari 8 weather satellite was launched in 2014 and has 16 channels from visible to Thermal InfRared (TIR) in high temporal and spatial resolution. Using AHI, it is very valuable to retrieve aerosol optical properties over dark surface to demonstrate its capability. To retrieve aerosol optical properties using visible and Near InfRared (NIR) region, surface signal is very important to be removed which can be estimated using minimum reflectivity method. The estimated surface reflectance is then used to retrieve the aerosol optical properties through the inversion process. In this study, we retrieve the aerosol optical properties over dark surface, but not over bright surface such as clouds, desert and so on. Therefore, the bright surface was detected and masked using various infrared channels of AHI and spatial heterogeneity, Brightness Temperature Difference (BTD), etc. The retrieval result shows the correlation coefficient of 0.7 against AERONET, and the within the Expected Error (EE) of 49%. It is accurately retrieved even for low Aerosol Optical Depth (AOD). However, AOD tends to be underestimated over the Beijing Hefei area, where the surface reflectance using the minimum reflectance method is overestimated than the actual surface reflectance.

• Korean Journal of Materials Research
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• v.23 no.12
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• pp.672-679
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• 2013

$Fe_4[Fe(CN)_6]_3$ coated on a mica or $TiO_2$/mica surface as infrared reflective blue pigment was prepared by a hydrothermal method. $Fe_4[Fe(CN)_6]_3$, used as coloring agent, was uniformly coated on mica or $TiO_2$/mica under the optimized condition of a 1.2 : 1 weight ratio between iron(III) chloride hexahydrate and potassium ferrocyanidetrihydrate at the initial pH level of 4.5 at $70^{\circ}C$. The infrared (IR)-reflective pigments were characterized by SEM, Zeta-potenial, FT-IR, and UV-VIS NIR spectrophotometry. Especially the CIE color coordinate and total solar reflectance(TSR) properties of the pigments were investigated in relation to variation of the coating and coated substrate thicknesses. Isolation-heat paint was prepared with 20 wt% blue pigments fully dispersed in acryl-urethane resin and several additives to coat the film uniformly. The films were also measured with CIE color coordinate, TSR, and the surface temperature was recorded by an isolation-heat measuring system. The pigments and films of $Fe_4[Fe(CN)_6]_3$ coated on mica and $TiO_2$/mica showed high TSR values compared with the TSR value of $Fe_4[Fe(CN)_6]_3$ itself. According to the increase of TSR value, the property of isolation-heat is effective. To realize the optimal blue color, we applied the the pigment to $TiO_2$ coated mica(TM(b)) which has blueish interference color. The pigment of $Fe_4[Fe(CN)_6]_3$ coated on TM(b) shows a strong blue color compared with that of $Fe_4[Fe(CN)_6]_3$ coated on $TiO_2$/Mmca(TM(w)), which has a whitish interference color.

• Korean Journal of Remote Sensing
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• v.34 no.4
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• pp.611-624
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• 2018

The percentage of moisture content in rice before harvest is crucial to reduce the economic loss in terms of yield, quality and drying cost. This paper discusses the application of artificial neural network (ANN) in developing a reliable prediction model using the low altitude fixed-wing unmanned air vehicle (UAV) based reflectance value of green, red, and NIR and statistical moisture content data. A comparison between the actual statistical data and the predicted data was performed to evaluate the performance of the model. The correlation coefficient (R) is 0.862 and the mean absolute percentage error (MAPE) is 0.914% indicate a very good accuracy of the model to predict the moisture content in rice before harvest. The model predicted values are matched well with the measured values($R^2=0.743$, and Nash-Sutcliffe Efficiency = 0.730). The model results are very promising and show the reliable potential to predict moisture content with the error of prediction less than 7%. This model might be potentially helpful for the rice production system in the field of precision agriculture (PA).

• KOREAN JOURNAL OF CROP SCIENCE
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• v.50 no.6
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• pp.394-399
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• 2005

Near Infrared Spectroscopy (NIRS) has been used as a tool for the rapid, accurate and nondestructive assay of the fresh rice leaf in nitrogen content. NIRS used in this study was visible and near infrared spectroscopy type instrument, Foss model 6500. To obtain a useful calibration equation, standard regression between the data was analyzed by chemical analysis and by NIRS method. Accuracy of calibration equation for nitrogen content on fresh leaf of rice were 0.879, 0.858 and 0.819, respectively. Accuracy of calibration equation after outlier treatment increased as 0.017, 0.02 and 0.061 improved each with 0.896, 0.878 and 0.880, respectively. Calibration equation combined using merge function after accuracy of calibration equation more increased by 0.911. Difference analysis value between calibration equation and lab value by kjeldahl showed $0.001\%$. With this as same result is the possibility of closing the deterioration of the sample in order to omit a construction and pulverization process it is judged with the fact that the nitrogen content measurement of the fresh rice leaf which the possibility of reducing an hour and an expense is by a near infrared spectroscopy technique will be possible.

• Journal of The Korean Society of Grassland and Forage Science
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• v.29 no.1
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• pp.31-36
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• 2009

This study was conducted to find out an alternative way of rapid and accurate analysis of forage quality. Near reflectance infrared spectroscopy (NIRS) was used to evaluate the possibility of forage analysis and collect 258 samples such as barley for whole crop silage, forage corn and sudangrass from 2002 to 2007. The samples were analyzed for CP (crude protein), CF (crude fiber), ADF (acid detergent fiber), NDF (neutral detergent fiber) and IVTD (in vitro true digestibility), and also scanned using NIRSystem with wavelength from $400{\sim}2,400nm$. Multiple linear regression was used with wet analysis data for developing the calibration model and validate unknown samples. The important index In this experiment was SEC and SEP $r^2$ for CF, CP, NDF, ADF and IVTD in calibration set were 0.70, 0.86, 0.94, 0.94 and 0.89, also 0.47, 0.39, 0.89, 0.90 and 0.61 in validation sample, respectively. The results of this experiment indicates that NIRS was reliable analytical method to assess forage quality, specially in CF, ADF and IVTD, sample should be included for respective forage samples to get accurate result. More robust calibrations can be made to cover every forage samples if added representative sample set.

• Journal of The Korean Society of Grassland and Forage Science
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• v.37 no.2
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• pp.154-160
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• 2017

This study was conducted to find out an alternative way of rapid and accurate analysis of chemical composition of permanent pastures in hilly grazing area. Near reflectance infrared spectroscopy (NIRS) was used to evaluate the potential for predicting proximate analysis of permanent pastures in a vegetative stage. 386 pasture samples obtained from hilly grazing area in 2015 and 2016 were scanned for their visible-NIR spectra from 400~2,400nm. 163 samples with different spectral characteristics were selected and analysed for moisture, crude protein (CP), crude ash (CA), acid detergent fiber (ADF) and neutral detergent fiber (NDF). Multiple linear regression was used with wet analysis data and spectra for developing the calibration and validation mode1. Wavelength of 400 to 2500nm and near infrared range with different critical T outlier value 2.5 and 1.5 were used for developing the most suitable equation. The important index in this experiment was SEC and SEP. The $R^2$ value for moisture, CP, CA, CF, Ash, ADF, NDF in calibration set was 0.86, 0.94, 0.91, 0.88, 0.48 and 0.93, respectively. The value in validation set was 0.66, 0.86, 0.83, 0.71, 0.35 and 0.88, respectively. The results of this experiment indicate that NIRS is a reliable analytical method to assess forage quality for CP, CF, NDF except ADF and moisture in permanent pastures when proper samples incorporated into the equation development.

• Journal of the Korean Society of Clothing and Textiles
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• v.41 no.2
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• pp.254-265
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• 2017

This study examines the possibility of a neuro-scientific approach to fashion Visual Merchandising (VM), by researching the brain activation of customers about fashion stores in terms of VM. Study subjects were in 20's-30's residing in Busan and ten ordinary person or fashion industry related individuals, it measures the change of cerebral blood flow on positive/negative photo stimulus in terms of VM using a functional Near Infrared Spectroscopy (fNIRS) device, and then compared the brain activation to the difference of the fashion store VM. Photo stimuli utilized in the experiment were selected through a preliminary study in advance. The results of this study are as follows. First, the brain activation was found in all 16 channels of stimulus ranges of fashion store VM regardless of positive/negative stimulus. This means that the VM of fashion store causes changes to the cerebral blood flow of consumers, which implies that consumer behavior can be affected by store VM. It also shows that the brain is more active in negative VM stimulus than positive VM despite slight differences in the subjects. In terms of VM, this suggests that the negative factors of fashion stores have a greater effect on the brains of consumers compared to the positive factors. Second, the reaction of the brain channel is different according to the positive/negative VM stimulus of the fashion store by product group and confirms that positive/negative VM stimulus can be distinguished by brain-reaction for the three product groups except for the underwear group among four product groups (men's wear store, women's wear store, underwear store, and sportswear store). The results indicate that more objective scientific measure and decision-making are possible through neuro-science in the strategic execution of VM. This study verified the possibility for a neuro-scientific approach to fashion VM; therefore, there are expectations for the various activation of interdisciplinary research and subsequent development of VM that utilize neuroscience in fashion marketing.

• Journal of Korean Society for Geospatial Information Science
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• v.19 no.1
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• pp.105-113
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• 2011

Since existing thematic maps have been made with medium- to low-resolution satellite images, they have several shortcomings including low positional accuracy and low precision of presented thematic information. Digital aerial photo image taken recently can express panchromatic and color bands as well as NIR (Near Infrared) bands which can be used in interpreting forest areas. High resolution images are also available, so it would be possible to conduct precision land cover classification. In this context, this paper implemented object-based land cover classification by using digital aerial photos with 0.12m GSD (Ground Sample Distance) resolution and IKONOS satellite images with 1m GSD resolution, both of which were taken on the same area, and also executed qualitative analysis with ortho images and existing land cover maps to check the possibility of object-based land cover classification using digital aerial photos and to present usability of digital aerial photos. Also, the accuracy of such classification was analyzed by generating TTA(Training and Test Area) masks and also analyzed their accuracy through comparison of classified areas using screen digitizing. The result showed that it was possible to make a land cover map with digital aerial photos, which allows more detailed classification compared to satellite images.

• The Bulletin of The Korean Astronomical Society
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• v.36 no.2
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• pp.77.2-77.2
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• 2011

We present our follow-up observation of the recently discovered supernova in M101. Being only 6.4 Mpc away from the Earth, the object is a Type-Ia supernova discovered this close in decades. We followed up this event with various observing facilities including on-campus telescopes at Seoul National University, the McDonald observatoy's 2.1m telescope, and UKIRT 4-m telescope. The light curves and the preliminary analysis of the multi-wavelength data will be presented, which cover the wavelengths from optical to NIR.

• Korean Journal of Plant Resources
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• v.23 no.4
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• pp.386-392
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• 2010

This study was done to measure the color and catechins contents in processed teas using the whole bands (400~2500 nm) with near-infrared spectroscopy(NIRS). The powder colors of 109 processed teas were measured with a colorimeter. The a/b ratios in Hunter color scale in processed teas accounted for about 98.9% of the variation in the fermentation degree(FD), indicating that the a/b ratio was a very useful trait for assessing fermentation degree. Also tea powders were scanned in the visible bands used with NIRSystem. The calibration equations for powder colors were developed using the regression method of modified partial least squares(MPLS) with the internal cross validation. The equations had low SECV (standard errors of cross-validation), and high $R^2$ (coefficient of determination in calibration) values with 0.996~1.00, indicating that the visible bands(400~700 nm) with NIRS could be used to rapidly measure the variables related to powder color and fermentation degree. Also another powders of 137 processed teas were scanned at 780~2500 nm bands in the reflectance mode. The calibration equations were developed using the regression method of MPLS with the internal cross validation. The equations had low SECV, and high $R^2$ (0.896~0.983) values, showing that NIRS could be used to rapidly discriminate the contents of EGC($R^2$=0.919), EC(0.896), EGCg(0.978), ECg(0.905) and total catechins(0.983) in processed teas with high precision and ease.