• Journal of the Korean Solar Energy Society
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• v.33 no.2
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• pp.28-34
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• 2013

It is essential to reduce building energy consumption in office building because government enact policy which encourages building energy certification from 2013. Office building has high cooling energy demand due to large glazed area of facade in these days. Shading devices can be an alternative of reducing high cooling energy demand. So, this study simulated a variety of exterior venetian blinds to know how much building energy be affected by orientation and reflectance of slat. The results of this study are based on Seoul weather data. The following is a summary of this study. 1) As a slat of venetian blinds has the lower reflectance, the more building energy reduced. Reflectance is usually affected by color and material of slat. In case reflectance is 0.2 reduce 4% of building energy than reflectance is 0.8. 2) Horizontal exterior venetian blinds are more effective than vertical exterior venetian blinds in all of orientation. Horizontal shape is average 16% more effective in shading effect than vertical shape. 3) In this case study, the most effective shading device is low reflectance horizontal exterior venetian blinds that result about 18% building energy reduction than no shade model. The results of this research can be used to plan shading devices for energy conservative office building.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1-3
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• 2003

In this study, spectroradiometer data were coupled with fluorometer data to find out the best suited bands ratio to monitor the chlorophyll a concentration for inland water. Remote sensing reflectance measurements were used to evaluate the performance of several default ocean color chlorophyll algorithms for SeaWiFS data. This study shows that the chlorophyll a concentration from fluorometer and reflectance from spectroradiometer lies in exploiting the signal provided by the chlorophyll a red absorption peak near 670nm. Two-band ratio based on a ratio of reflectance 670 and 700nm provided a good correlation for a linear model, compare with blue-green two band ratio.

• Journal of Biosystems Engineering
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• v.33 no.1
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• pp.63-68
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• 2008

This study was carried out to find a useful method to predict hardness of tomato using optical spectrum data. Optical spectrum of reflectance and transmittance data were collected processed by 9 kind of preprocessing methods-normalizations of mean, maximum and range, SNV (standard normal variate), MSC (multiplicative scatter correction), the first derivative and second derivative of Savitzky-Golay and Norris-Gap. With the preprocessed and non-processed original spectrum data, prediction models of hardness of tomato were developed using analytical tools of PLS (partial least squares) and MLR (multiple linear regression) and tested for their validation. The test of validation resulted that the analytical tools of PLS and MLR output similar performances while the transmittance spectra showed much better result than the reflectance spectra.

• Proceedings of the KSRS Conference
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• v.2
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• pp.668-671
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• 2006

Radiative transfer modeling of ice clouds is developed. Ice clouds located near tropopause reflect most of sunlight, thus atmospheric and surface effects can be minimized. Cloud properties such as cloud optical thickness (COT) and effective radius are important parameters to determine the magnitude of reflectance, while atmospheric and surface parameters rarely affect reflectance value. For selected homogeneous cloud pixels of MODerate Resolution Imaging Spectroradiometer (MODIS) observation, reflectances are calculated using MODIS cloud products as inputs of radiative transfer model (RTM). For three types of phase function (Henyey-Greenstein, Garcia-Siewert, Baum) calculated reflectances are compared with observations for validation. All cases show linear relationship between simulated values and measured values, however each represent different bias and slope. The result shows that phase function determine angular distribution of reflectance.

• Journal of Biosystems Engineering
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• v.38 no.4
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• pp.318-326
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• 2013

Purpose: We developed a viability evaluation method for cucumber (Cucumis sativus) seed using hyperspectral reflectance imaging. Methods: Reflectance spectra of cucumber seeds in the 400 to 1000 nm range were collected from hyperspectral reflectance images obtained using blue, green, and red LED illumination. A partial least squares-discriminant analysis (PLS-DA) was developed to predict viable and non-viable seeds. Various ranges of spectra induced by four types of LEDs (Blue, Green, Red, and RGB) were investigated to develop the classification models. Results: PLS-DA models for spectra in the 600 to 700 nm range showed 98.5% discrimination accuracy for both viable and non-viable seeds. Using images based on the PLS-DA model, the discrimination accuracy for viable and non-viable seeds was 100% and 99%, respectively Conclusions: Hyperspectral reflectance images made using LED light can be used to select high quality cucumber seeds.

• Proceedings of the KSRS Conference
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• 2009.03a
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• pp.254-259
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• 2009

In this study, Simplified Method for the Atmospheric Correction (SMAC) radiative transfer model (RTM) used to retrieve surface reflectance from MODIS Top Of Atmosphere (TOA) reflectance (MOD02). SMAC code provides coefficients which were previously yielded by Second Simulation of the Satellite Signal in the Solar Spectrum (6S) for each satellite sensor. We conducted error analysis of SMAC RTM using MOD02 over comparison with MODIS surface reflectance (MOD09) which was provided from 6S. It showed that low accuracy values such as, $R^2$ : 0.6196, Root Means Square Error (RMSE) : 0.00031, bias : - 0.0859. Thus sensitivity analysis of input parameters and coefficients was conducted to searching error sources. Coefficients about $\tau_p$ (average AOD) are more influence than any other coefficients of $\tau_{a550}$ (Aerosol Optical Depth at 550nm) from sensitivity test. Calibrated coefficients of $\tau_p$ from regression analysis were used to surface reflectance which showed that improve accuracy of surface reflectance ($R^2$ : 0.827, RMSE : 0.00672, bias : - 0.000762).

• The Bulletin of The Korean Astronomical Society
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• v.40 no.1
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• pp.61.3-62
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• 2015

Remote-sensing observation is one of the observation methods that provide valuable information, such as composition and surface physical conditions of solar system objects. The Hayabusa spacecraft succeeded in the first sample returning from a near-Earth asteroid, (25143) Itokawa. It has established a ground truth technique to connect between ordinary chondrite meteorites and S-type asteroids. One of the scientific observation instruments that Hayabusa carried, Asteroid Multi-band Imaging Camera(AMICA) has seven optical-near infrared filters (ul, b, v, w, x, p, and zs), taking more than 1400 images of Itokawa during the rendezvous phase. The reflectance of planetary body can provide valuable information of the surface properties, such as the optical aspect of asteroid surface at near zero phase angle (i.e. Sun-asteroid-observer's angle is nearly zero), light scattering on the surface, and surface roughness. However, only little information of the phase angle dependences of the reflectance of the asteroid is known so far. In this study, we investigated the phase angle dependences of Itokawa's surface to understand the surface properties in the solar phase angle of $0^{\circ}-40^{\circ}$ using AMICA images. About 700 images at the Hayabusa rendezvous phase were used for this study. In addition, we compared our result with those of several photometry models, Minnaert model, Lommel-Seeliger model, and Hapke model. At this conference, we focus on the AMICA's v-band data to compare with previous ground-based observation researches.

• Journal of The Geomorphological Association of Korea
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• v.21 no.4
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• pp.121-131
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• 2014

This study analyzed the spectral reflectance characteristics of kaolinite and ASTER(Advanced Spaceborne Thermal Emission and Reflectance Radiometer) image to extract the distribution of kaolin mines in Hadong area, Gyeongsangnam-do. The band ratio model was applied to extract kaolinite using difference of wavelength absorption band distinct feature of minerals from ASTER image which is the major mineral of kaolin mines. According to the spectral reflectance curve of kaolinite, it showed the absorption features around 0.96 and $2.18{\mu}m$ by Al-OH. Also, it affected 1.24 and $1.38{\sim}1.41{\mu}m$ by OH. Applying for new band ratio model from the spectral features of kaolinite to ASTER image, it is possible to make the distribution map of mining traces including present- developing kaolin mines.

• Korean Journal of Remote Sensing
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• v.36 no.5_1
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• pp.807-821
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• 2020

The objective of this study is to evaluate the applicability of representative spatio-temporal fusion models developed for the fusion of mid- and low-resolution satellite images in order to construct a set of time-series high-resolution images for crop monitoring. Particularly, the effects of the characteristics of input image pairs on the prediction performance are investigated by considering the principle of spatio-temporal fusion. An experiment on the fusion of multi-temporal Sentinel-2 and RapidEye images in agricultural fields was conducted to evaluate the prediction performance. Three representative fusion models, including Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM), SParse-representation-based SpatioTemporal reflectance Fusion Model (SPSTFM), and Flexible Spatiotemporal DAta Fusion (FSDAF), were applied to this comparative experiment. The three spatio-temporal fusion models exhibited different prediction performance in terms of prediction errors and spatial similarity. However, regardless of the model types, the correlation between coarse resolution images acquired on the pair dates and the prediction date was more significant than the difference between the pair dates and the prediction date to improve the prediction performance. In addition, using vegetation index as input for spatio-temporal fusion showed better prediction performance by alleviating error propagation problems, compared with using fused reflectance values in the calculation of vegetation index. These experimental results can be used as basic information for both the selection of optimal image pairs and input types, and the development of an advanced model in spatio-temporal fusion for crop monitoring.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.55 no.4
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• pp.357-364
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• 2010

Kjeldahl method used in many materials from various plant parts to determine protein contents, is laborious and time-consuming and utilizes hazardous chemicals. Near-infrared (NIR) reflectance spectroscopy, a rapid and environmentally benign technique, was investigated as a potential method for the prediction of protein content. Near-infrared reflectance spectra(1100-2400 nm) of coarse cereal grains(n=100 for each germplasm) were obtained using a dispersive spectrometer as both of grain itself and flour ground, and total protein contents determined according to Kjeldahl method. Using multivariate analysis, a modified partial least-squares model was developed for prediction of protein contents. The model had a multiple coefficient of determination of 0.99, 0.99, 0.99, 0.96 and 0.99 for foxtail millet, sorghum, millet, adzuki bean and mung bean germplasm, respectively. The model was tested with independent validation samples (n=10 for each germplasm). All samples were predicted with the coefficient of determination of 0.99, 0.99, 0.99, 0.91 and 0.99 for foxtail millet, sorghum, millet, adzuki bean and mung bean germplasm, respectively. The results indicate that NIR reflectance spectroscopy is an accurate and efficient tool for determining protein content of diverse coarse cereal germplasm for nutrition labeling of nutritional value. On the other hands appropriate condition of cereal material to predict protein using NIR was flour condition of grains.