The purpose of this study was to compare and analyze the differences in scan time, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) in the third lumbar vertebral region including the back fat, spinal cord, and cerebrospinal fluid using the mDixon, T2 TSE, and T2 spectral pre-saturation with inversion-recovery (SPIR) techniques. With the factors affecting the SNR fixed, the lumbar sagittal plane images of 30 adults were compared on mDixon, T2 TSE, and T2 SPIR imaging tests. The test times for mDixon, T2 TSE, and T2 SPIR were 115 seconds, 60 seconds, and 60 seconds, respectively. The mDixon T2 images showed higher SNR than the T2 TSE images at the third lumbar vertebral region (p<0.05), lower SNR in the back fat and cerebrospinal fluid (p<0.05) areas, and comparable SNR in the spinal cord (p>0.05). The CNR between the third lumbar vertebral area and back fat was higher in the mDixon T2 images, and the CNR of the cerebrospinal fluid and spinal cord images was higher in the T2 TSE images (p<0.05). The mDixon T2 FS images CNR was lower for the 3rd lumbar vertebral body region and back fat than the T2 SPIR images, and higher for the spinal cord and cerebrospinal fluid images (p<0.05). The CNR between the third lumbar body and back fat areas was higher in the mDixon T2 FS images (p<0.05), and there was no difference in the CNR in the images of the cerebrospinal fluid and the spinal cord (p>0.05). It is difficult to determine whether the mDixon technique is superior to the conventional T2 TSE and T2 SPIR techniques in terms of test time, SNR, and CNR. This study was confined to patients with simple lower back pain and was limited by controlled experimental conditions. Studies using clinically applied protocols are warranted in the future.
Climate change has been accelerating in coastal waters recently; therefore, the importance of coastal environmental monitoring is also increasing. Chlorophyll-a concentration, an important marine variable, in the surface layer of the global ocean has been retrieved for decades through various ocean color satellites and utilized in various research fields. However, the commonly used chlorophyll-a concentration algorithm is only suitable for application in clear water and cannot be applied to turbid waters because significant errors are caused by differences in their distinct components and optical properties. In addition, designing a standard algorithm for coastal waters is difficult because of differences in various optical characteristics depending on the coastal area. To overcome this problem, various algorithms have been developed and used considering the components and the variations in the optical properties of coastal waters with high turbidity. Chlorophyll-a concentration retrieval algorithms can be categorized into empirical algorithms, semi-analytic algorithms, and machine learning algorithms. These algorithms mainly use the blue-green band ratio based on the reflective spectrum of sea water as the basic form. In constrast, algorithms developed for turbid water utilizes the green-red band ratio, the red-near-infrared band ratio, and the inherent optical properties to compensate for the effect of dissolved organisms and suspended sediments in coastal area. Reliable retrieval of satellite chlorophyll-a concentration from turbid waters is essential for monitoring the coastal environment and understanding changes in the marine ecosystem. Therefore, this study summarizes the pre-existing algorithms that have been utilized for monitoring turbid Case 2 water and presents the problems associated with the mornitoring and study of seas around the Korean Peninsula. We also summarize the prospective for future ocean color satellites, which can yield more accurate and diverse results regarding the ecological environment with the development of multi-spectral and hyperspectral sensors.
In this present study, the effects of Signal to Noise Ratio (SNR), Full Width Half Maximum (FWHM), Aerosol Optical Depth (AOD), $O_3$ Vertical Column Density ($O_3$ VCD), and Solar Zenith Angle (SZA) on the accuracy of sulfur dioxide Vertical Column Density ($SO_2$ VCD) retrieval have been quantified using the Differential Optical Absorption Spectroscopy (DOAS) method with the ground-based direct-sun synthetic radiances. The synthetic radiances produced based on the Beer-Lambert-Bouguer law without consideration of the diffuse effect. In the SNR condition of 650 (1300) with FWHM = 0.6 nm, AOD = 0.2, $O_3$ VCD = 300 DU, and $SZA=30^{\circ}$, the Absolute Percentage Difference (APD) between the true $SO_2$ VCD values and those retrieved ranges from 80% (28%) to 16% (5%) for the $SO_2$ VCD of $8.1{\times}10^{15}$ and $2.7{\times}10^{16}molecules\;cm^{-2}$, respectively. For an FWHM of 0.2 nm (1.0 nm) with the $SO_2$ VCD values equal to or greater than $2.7{\times}10^{16}molecules\;cm^{-2}$, the APD ranges from 6.4% (29%) to 6.2% (10%). Additionally, when FWHM, SZA, AOD, and $O_3$ VCD values increase, APDs tend to be large. On the other hand, SNR values increase, APDs are found to decrease. Eventually, it is revealed that the effects of FWHM and SZA on $SO_2$ VCD retrieval accuracy are larger than those of $O_3$ VCD and AOD. The SZA effects on the reduction of $SO_2$ VCD retrieval accuracy is found to be dominant over the that of FWHM for the condition of $SO_2$ VCD larger than $2.7{\times}10^{16}molecules\;cm^{-2}$.
Kim, Seoyeon;Jeong, Yemin;Youn, Youjeong;Cho, Subin;Kang, Jonggu;Kim, Geunah;Lee, Yangwon
Korean Journal of Remote Sensing
/
v.37
no.3
/
pp.543-557
/
2021
Because aerosols have different spectral characteristics according to the size and composition of the particle and to the satellite sensors, a comparative analysis of aerosol products from various satellite sensors is required. In South Korea, however, a comprehensive study for the comparison of various official satellite AOD (Aerosol Optical Depth) products for a long period is not easily found. In this paper, we aimed to assess the performance of the AOD products from MODIS (Moderate Resolution Imaging Spectroradiometer), VIIRS (Visible Infrared Imaging Radiometer Suite), Himawari-8, and Sentinel-3 by referring to the AERONET (Aerosol Robotic Network) sun photometer observations for the period between January 2015 and December 2019. Seasonal and geographical characteristics of the accuracy of satellite AOD were also analyzed. The MODIS products, which were accumulated for a long time and optimized by the new MAIAC (Multiangle Implementation of Atmospheric Correction) algorithm, showed the best accuracy (CC=0.836) and were followed by the products from VIIRS and Himawari-8. On the other hand, Sentinel-3 AOD did not appear to have a good quality because it was recently launched and not sufficiently optimized yet, according to ESA (European Space Agency). The AOD of MODIS, VIIRS, and Himawari-8 did not show a significant difference in accuracy according to season and to urban vs. non-urban regions, but the mixed pixel problem was partly found in a few coastal regions. Because AOD is an essential component for atmospheric correction, the result of this study can be a reference to the future work for the atmospheric correction for the Korean CAS (Compact Advanced Satellite) series.
Journal of the Korean Applied Science and Technology
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v.38
no.3
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pp.824-831
/
2021
1, 2-Octanediol galactoside (OD-gal) has been synthesized from 1, 2-octanediol (OD), as a safer cosmetic preservative, using recombinant Escherichia coli β-galactosidase (β-gal). To confirm the molecular structure of synthesized OD-gal, mass spectrometry and NMR (1H- and 13C-) spectroscopy of OD-gal were carried out. In the reaction mixture, a sodium adduct ion of OD-gal (m/z=331.1732) was identified using mass spectrometry analysis. In addition, 1H NMR spectrum of OD-gal showed multiple peaks corresponding to the galactosyl group, which is evidence of galactosylation on OD. Downfield proton peaks at δH 4.39 ppm and multiple peaks from δH 3.98~3.55 ppm were indicative of galactosylation on OD. Up field proton peaks at δH 1.52~1.26 ppm and 0.89 ppm showed the presence of CH2 and CH3 protons of OD. 13C NMR spectrum revealed the presence of 24 carbons suggestive of α- and β-anomers of OD-gal. Among 14 carbon peaks from each anomer, the 4 peaks at δC 31.4, 29.0, 22.3, and 13.7 ppm were assigned to be overlapped showing only 24 peaks out of a total of 28 peaks. The mass value from mass spectrometry analysis of OD-gal, and 1H and 13C NMR spectral data were in good agreement with the expecting structure of OD-gal. Finally, we identified a galactose molecule from the hydrolysate of OD-gal using β-gal. We are expecting that through future study it will eventually be able to develop a safe cosmetic preservative.
Kim, Tae-Yang;Ryu, Chan-Seok;Kang, Ye-seong;Jang, Si-Hyeong;Park, Jun-Woo;Kang, Kyung-Suk;Baek, Hyeon-Chan;Park, Min-Jun;Park, Jin-Ki
Korean Journal of Agricultural and Forest Meteorology
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v.23
no.4
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pp.306-315
/
2021
This study analyzed the effects of light-shielding curtains and halogens on spectrum when acquiring hyperspectral images in a greenhouse. The image data of tarp (1.4*1.4 m, 12%) with 30 degrees of angles was achieved three times with four conditions depending on 14 heights using the automatic image acquisition system installed in the greenhouse at the department of Southern Area of National Institute of Crop Science. When the image was acquired without both a light-shielding curtain and halogen lamp, there was a difference in spectral tendencies between direct light and shadow parts on the base of 550 nm. The average coefficient of variation (CV) for direct light and shadow parts was 1.8% and 4.2%, respective. The average CV value was increased to 12.5% regardless of shadows. When the image was acquired only used a halogen lamp, the average CV of the direct light and shadow parts were 2 .6% and 10.6%, and the width of change on the spectrum was increased because the amount of halogen light was changed depending on the height. In the case of shading curtains only used, the average CV was 1.6%, and the distinction between direct light and shadows disappeared. When the image was acquired using a shading curtain and halogen lamp, the average CV was increased to 10.2% because the amount of halogen light differed depending on the height. When the average CV depending on the height was calculated using halogen and light-shielding curtains, it was 1.4% at 0.1m and 1.9% at 0.2 m, 2 .6% at 0.3m, and 3.3% at 0.4m of height, respectively. When hyperspectral imagery is acquired, it is necessary to use a shading curtain to minimize the effect of shadows. Moreover, in case of supplementary lighting by using a halogen lamp, it is judged to be effective when the size of the object is less than 0.2 m and the distance between the object and the housing is kept constant.
Park, Jeonghyeon;Yang, Jiwon;Choi, Wonei;Kim, Serin;Lee, Hanlim
Korean Journal of Remote Sensing
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v.38
no.2
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pp.189-198
/
2022
In this present study, we investigated the effect of the offset correction factor calculation method on the sulfur dioxide (SO2) column density in the SO2 retrieval algorithm of the Geostationary Environment Monitoring Spectrometer (GEMS) launched in February 2020. The GEMS operational SO2 retrieval algorithm is the Differential Optical Absorption Spectroscopy (DOAS) - Principal Component Analysis (PCA) Hybrid algorithm. In the GEMS Hybrid algorithm, the offset correction process is essential to correct the absorption effect of ozone appearing in the SO2 slant column density (SCD) obtained after spectral fitting using DOAS. Since the SO2 column density may depend on the conditions for calculating the offset correction factor, it is necessary to apply an appropriate offset correction value. In this present study, the offset correction values were calculated for days with many cloud pixels and few cloud pixels, respectively. And a comparison of the SO2 column density retrieved by applying each offset correction factor to the GEMS operational SO2 retrieval algorithm was performed. When the offset correction value was calculated using radiance data of GEMS on a day with many cloud pixels was used, the standard deviation of the SO2 column density around India and the Korean Peninsula, which are the edges of the GEMS observation area, was 1.27 DU, and 0.58 DU, respectively. And around Hong Kong, where there were many cloud pixels, the SO2 standard deviation was 0.77 DU. On the other hand, when the offset correction value calculated using the GEMS data on the day with few cloud pixels was used, the standard deviation of the SO2 column density slightly decreased around India (0.72 DU), Korean Peninsula (0.38 DU), and Hong Kong (0.44 DU). We found that the SO2 retrieval was relatively stable compared to the SO2 retrieval case using the offset correction value on the day with many cloud pixels. Accordingly, to minimize the uncertainty of the GEMS SO2 retrieval algorithm and to obtain a stable retrieval, it is necessary to calculate the offset correction factor under appropriate conditions.
Cheonji Lake, the caldera of Baekdu Mountain, located on the border of the Korean Peninsula and China, alternates between melting and freezing seasonally. There is a magma chamber beneath Cheonji, and variations in the magma chamber cause volcanic antecedents such as changes in the temperature and water pressure of hot spring water. Consequently, there is an abnormal region in Cheonji where ice melts quicker than in other areas, freezes late even during the freezing period, and has a high-temperature water surface. The abnormal area is a discharge region for hot spring water, and its ice gradient may be used to monitor volcanic activity. However, due to geographical, political and spatial issues, periodic observation of abnormal regions of Cheonji is limited. In this study, the degree of ice change in the optimal region was quantified using a Landsat -5/-7/-8 optical satellite image and a Modified U-Net regression model. From January 22, 1985 to December 8, 2020, the Visible and Near Infrared (VNIR) band of 83 Landsat images including anomalous regions was utilized. Using the relative spectral reflectance of water and ice in the VNIR band, unique data were generated for quantitative ice variability monitoring. To preserve as much information as possible from the visible and near-infrared bands, ice gradient was noticed by applying it to U-Net with two encoders, achieving good prediction accuracy with a Root Mean Square Error (RMSE) of 140 and a correlation value of 0.9968. Since the ice change value can be seen with high precision from Landsat images using Modified U-Net in the future may be utilized as one of the methods to monitor Baekdu Mountain's volcanic activity, and a more specific volcano monitoring system can be built.
The color and optical properties of seawater are determined by the interaction between dissolved organic and inorganic substances and plankton contained in it. The Ieodo - Ocean Research Institute (I-ORS), located in the East China Sea, is affected by the low salinity of the Yangtze River in the west and the Tsushima Warm Current in the south. Thus, it is a suitable site for analyzing the fluctuations in circulation and optical properties around the Korean Peninsula. In this study, seawater surrounding the I-ORS was classified according to its optical characteristics using the satellite remote reflectance observed with Moderate Resolution Imaging Spectroradiometer (MODIS)/Aqua and National Aeronautics and Space Administration (NASA) bio-Optical Marine Algorithm Dataset (NOMAD) from January 2016 to December 2020. Additionally, the variation characteristics of optical water types (OWTs) from different seasons were presented. A total of 59,532 satellite match-up data (d ≤ 10 km) collected from seawater surrounding the I-ORS were classified into 23 types using the spectral angle mapper. The OWTs appearing in relatively clear waters surrounding the I-ORS were observed to be greater than 50% of the total. The maximum OWTs frequency in summer and winter was opposite according to season. In particular, the OWTs corresponding to optically clear seawater were primarily present in the summer. However, the same OWTs were lower than overall 1% rate in winter. Considering the OWTs fluctuations in the East China Sea, the I-ORS is inferred to be located in the transition zone of seawater. This study contributes in understanding the optical characteristics of seawater and improving the accuracy of satellite ocean color variables.
Due to river maintenance projects such as the creation of hydrophilic areas around rivers and the Four Rivers Project, the flow characteristics of rivers are continuously changing, and the risk of water quality accidents due to the inflow of various pollutants is increasing. In the event of a water quality accident, it is necessary to minimize the effect on the downstream side by predicting the concentration and arrival time of pollutants in consideration of the flow characteristics of the river. In order to track the behavior of these pollutants, it is necessary to calculate the diffusion coefficient and dispersion coefficient for each section of the river. Among them, the dispersion coefficient is used to analyze the diffusion range of soluble pollutants. Existing experimental research cases for tracking the behavior of pollutants require a lot of manpower and cost, and it is difficult to obtain spatially high-resolution data due to limited equipment operation. Recently, research on tracking contaminants using RGB drones has been conducted, but RGB images also have a limitation in that spectral information is limitedly collected. In this study, to supplement the limitations of existing studies, a hyperspectral sensor was mounted on a remote sensing platform using a drone to collect temporally and spatially higher-resolution data than conventional contact measurement. Using the collected spatio-temporal hyperspectral images, the tracer concentration was calculated and the transverse dispersion coefficient was derived. It is expected that by overcoming the limitations of the drone platform through future research and upgrading the dispersion coefficient calculation technology, it will be possible to detect various pollutants leaking into the water system, and to detect changes in various water quality items and river factors.
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