• 한국안광학회지
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• 제5권1호
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• pp.31-37
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• 2000

제1~3색각 이상 검사용 Farnsworth Dichotomous Test Panel D-15의 칼라분석을 위하여 380~780 nm의 반사광 spectrum 세기를 측정하여 CIE system을 도입하였다. Panel D-15의 색상변환은 650nm 이상, 500~600 nm, 400~450 nm의 3개 파장영역의 광 반사율 세기에 의존한다. 반사 spectrum으로부터 3극치 X, Y, Z 값, 보색 평면과 명암축으로 하는 3차원 CIELAB system의 $L^*a^*b^*$와 Lab 값, CIELUV system $U^*V^*$ 값, 색도도 좌표 x, y 값을 구했다.

• 대한원격탐사학회지
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• 제17권2호
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• pp.131-139
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• 2001

Extraction of waterline in tidal flat has been one of the main concerns in the remote sensing of coastal region. This study aimed to define the spectral characteristics of turbid water near the shoreline and to find the appropriate spectrum to delineate the waterline at the inter-tidal flat in the western coast of Korean Peninsula. Spectral reflectance curves were obtained by the field measurements under the diverse condition of water depth and turbidity at the study area in Kyong-gi Bay. Spectroscopy measurements showed that reflectances of the exposed mudflat, shallow turbid water, and normal coastal water were significantly different by wavelength. Shallow water near the waterline showed diverse conditions of turbidity. Spectral reflectance tends to increase as turbidity increases, particularly at the visible and near infrared spectrum. At the middle infrared wavelength, tidal water showed very little reflectance regardless of the turbidity and water depth and was easily disting from the exposed tidal flat. The exact waterline between exposed tidal flat and seawater should be extracted from the image data obtained at the middle infrared wavelength.

• 한국해양바이오학회지
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• 제16권1호
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• pp.19-25
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• 2024

To verify the color change in dried laver postproduction during the heating process, chromaticity elements were compared via a spectrophotometer across various heating conditions within the visible light spectrum. In general, the moisture reduction rate increased with rising temperature and time. Surface image comparisons revealed an expanded area of light reflection on the heat-treated dried laver sample due to surface roughening from shrinkage. No statistically significant differences in chromaticity values were observed in the measurements of brightness (L^*), redness (a^*), and yellowness (b^*). Reflectance spectrum measurements in the visible light region confirmed high reflectance under red wavelength conditions. In particular, a significant increase in reflectance at 700 nm compared with untreated samples was noted. The correlation between the increase in 700 nm reflectance of dried laver samples and heating conditions ranged from 0.7471 to 0.7793, suggesting its potential use as an indicator for comparing color changes in dried laver based on heating conditions.

• 한국농공학회지
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• 제45권5호
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• pp.77-84
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• 2003

Recent advances in remote sensing techniques provide the potential for monitoring soil color as well as soil moisture conditions at the spatial and temporal scales required for detailed local modeling efforts. Soil moisture as well as soil color is a key feature used in the identification and classification of soils. Soil spectral reflectance has a direct relationship with soil color, as well as to other parameters such as soil moisture, soil texture. and organic matter. We evaluate the influence of seven soil properties, soil color and soil moisture, on soil spectral reflectance. This paper presents the results obtained from the ground-truth spectral reflectance measurements in the 300-1100 nm wavelength range for various land surfaces. The results suggest that the reflectance properties of soils are related to soil color, soil texture, and soil moisture. Increasing soil moisture content generally decreases soil reflectance which leads to parallel curves of soil reflectance spectra across the entire shortwave spectrum. We discuss the relationships between the soil reflectance and the Munsell Soil Color Charts which contain standard color chips with colors specified by designations for hue, value, and chroma.

• Journal of Biosystems Engineering
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• 제41권3호
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• pp.273-280
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• 2016

Purpose: This experiment was conducted to detect water stress in terms of the moisture content of cucumber seedlings under water stress condition using a hyperspectral image acquisition system, linear regression analysis, and partial least square regression (PLSR) to achieve a non-destructive measurement procedure. Methods: Changes in the reflectance spectrum of cucumber seedlings under water stress were measured using hyperspectral imaging techniques. A model for estimating moisture content of cucumber seedlings was constructed through a linear regression analysis that used the moisture content of cucumber seedlings and a normalized difference vegetation index (NDVI). A model using PLSR that used the moisture content of cucumber seedlings and reflectance spectrum was also created. Results: In the early stages of water stress, cucumber seedlings recovered completely when sub-irrigation was applied. However, the seedlings suffering from initial wilting did not recover when more than 42 h passed without irrigation. The reflectance spectrum of seedlings under water stress decreased gradually, but increased when irrigation was provided, except for the seedlings that had permanently wilted. From the results of the linear regression analysis using the NDVI, the model excluding wilted seedlings with less than 20% (n=97) moisture content showed a precision ($R^2$ and $R^2_{\alpha}$) of 0.573 and 0.568, respectively, and accuracy (RE) of 4.138% and 4.138%, which was higher than that for models including all seedlings (n=100). For PLS regression analysis using the reflectance spectrum, both models were found to have strong precision ($R^2$) with a rating of 0.822, but accuracy (RMSE and RE) was higher in the model excluding wilted seedlings as 5.544% and 13.65% respectively. Conclusions: The estimation model of the moisture content of cucumber seedlings showed better results in the PLSR analysis using reflectance spectrum than the linear regression analysis using NDVI.

• 대한원격탐사학회지
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• 제32권1호
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• pp.67-71
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• 2016

The surface reflectance is essential to retrieval various indicators related land properties such as vegetation index, albedo and etc. In this study, we estimated surface reflectance using Himawari-8 / Advanced Himawari Imager (AHI) channel data. In order to estimate surface reflectance from Top of Atmosphere (TOA) reflectance, the atmospheric correction is necessary because all of the TOA reflectance from optical sensor is affected by gas molecules and aerosol in the atmosphere. We used Second Simulation of a Satellite Signal in the Solar Spectrum Vector (6SV) Radiative Transfer Model (RTM) to correct atmospheric effect, and Look-Up Table (LUT) to shorten the calculation time. We verified through comparison Himawri-8 / AHI surface reflectance and Proba-V S1 products. As a result, bias and Root Mean Square Error (RMSE) are calculated about -0.02 and 0.05.

• 한국환경복원기술학회지
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• 제6권1호
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• pp.34-40
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• 2003

The deterioration of agricultural environment, which is characterized by dryness and desertification of land, is one of the main reasons which explain the recent decrease of land productivity. To solve these environmental problems, it is very important to make clear the mechanism between soil, water, vegetation and temperature. The main objective of this study is to provide a soil surface information, which represent a soil reflectance spectrum, by remote sensing technology. The soil reflectance of the soil was measured using a spectro-radiometer in the wavelength range from 300nm to 1100nm. The results suggest that the reflectance properties of soils are related to their mineral composition and soil moisture. Increasing soil moisture resulted in an decrease in the rate of reflectance which leads to parallel curves of soil reflectance spectra.

• 대한원격탐사학회지
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• 제25권6호
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• pp.487-499
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• 2009

Atmospheric correction of satellite measurements is a major step to estimate accurate surface reflectance of solar spectrum channels. In this study, Simplified Method for the Atmospheric Correction (SMAC) radiative transfer model used to retrieve surface reflectance from MODIS (MODerate resolution Imaging Spectrometer) top of atmosphere (TOA) reflectance. It is fast and simple atmospheric correction method, so it uses for work site operation in various satellite. This study attempts a test of accuracy of SMAC through a sensitivity test to detected error sources and to improve accuracy of surface reflectance using SMAC. The results of SMAC as compared with MODIS surface reflectance (MOD09) was represented that low accuracy ($R^2\;=\;0.6196$, Root Means Square Error (RMSE) = 0.00031, bias = - 0.0859). Thus sensitivity analysis of input parameters and coefficients was conducted to searching error sources. Among the input parameters, Aerosol Optical Depth (AOD) is the most influence input parameter. In order to modify AOD term in SMAC code, Stepwise multiple regression was performed with testing and remove variable in three stages with independent variables of AOD at 550nm, solar zenith angle, viewing zenith angle. Surface reflectance estimation by using Newly proposed AOD term in the study showed that improve accuracy ($R^2\;=\;0.827$, RMSE = 0.00672, bias = - 0.000762).

• 한국안광학회지
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• 제7권2호
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• pp.175-180
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• 2002

렌즈의 thin film 균일성을 평가하기 위하여 spctrophotometer를 이용한다. 렌즈의 중심 중간, edge 등의 지점에서 파장의존상의 반사율을 측정하여 반사율 spectrum의 두 peak를 선택하여 비교하여, 박막 균일성 여부를 분석한다. 반사율의 두 peak의 파장 영역(${\lambda}_1,{\lambda}_2$)으로부터 thin film의 thickness(t)를 구한다. $$t=\frac{1}{2(n^2-\sin^2{\theta})^{1/2}}{\times}\frac{{\lambda}_1{\lambda}_2}{{\lambda}_2-{\lambda}_1}$$ 렌즈의 중심 중간, edge 등의 지점에서 반사율 pattern이 동일 값이면 coating 렌즈의 박막은 균일성 갖는다. coating 렌즈의 박막 균일성 평가 방법을 단층막 $MgF_2$(n=1.38) coating 렌즈에 적용하였다. 박막의 thickness 차이는 360nm 정도였다. 파장의존성에 대한 광반사율의 측정으로부터 coating 렌즈의 박막 균일성을 쉽게 분석할 수 있다.

• 약학회지
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• 제38권4호
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• pp.366-371
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• 1994

To improve the identification power of TLC/HPTLC the in situ reflectance spectra obtained directly from plates with commercial scanner are used. The spectrum normalization should be carried out prior to comparing and searching the spectra from library for the identification of compounds. Because the reflectance does not obey the Lambert-Beer's law, there arise some problems in normalization. These problems could be solved to some extent by normalizing the spectra with regression methods. The spectra are manipulated with the regression function of a curve obtained from the correlation plot. When the parabola was used as the manipulating function, the spectra were identified with the accuracy of 97% and this result was better than that of conventionally used the point and area normalization method.