• Title/Summary/Keyword: spectral measurements

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Least-Square Fitting of Intrinsic and Scattering Q Parameters (최소자승법(最小自乘法)에 의(衣)한 고유(固有) Q와 산란(散亂) Q의 측정(測定))

  • Kang, Ik Bum;McMechan, George A.;Min, Kyung Duck
    • Economic and Environmental Geology
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    • v.27 no.6
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    • pp.557-561
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    • 1994
  • Q estimates are made by direct measurements of energy loss per cycle from primary P and S waves, as a function of frequency. Assuming that intrinsic Q is frequency independent and scattering Q is frequency dependent over the frequencies of interest, the relative contributions of each, to a total observed Q, may be estimated. Test examples are produced by computing viscoelastic synthetic seismograms using a pseudo spectral solution with inclusion of relaxation mechanisms (for intrinsic Q) and a fractal distribution of scatterers (for scattering Q). The composite theory implies that when the total Q for S-waves is smaller than that for P-waves (the usual situation), intrinsic Q is dominating; when it is larger, scattering Q is dominating. In the inverse problem, performed by a global least squares search, intrinsic $Q_p$ and $Q_s$ estimates are reliable and unique when their absolute values are sufficiently low that their effects are measurable in the data. Large $Q_p$ and $Q_s$ have no measurable effect and hence are not resolvable. Standard deviation of velocity $({\sigma})$ and scatterer size (A) are less unique as they exhibit a tradeoff as predicted by Blair's equation. For the P-waves, intrinsic and scattering contributions are of approximately the same importance, for S-waves, the intrinsic contributions dominate.

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Evaluation of Effective Sensing Distance and Measurement Efficiency for Ground-Based Remote Sensors with Different Leaf Distribution in Tobacco Plant (연초의 엽위 분포형태에 따른 지상 원격센서의 유효 탐사거리와 측정 효율성 평가)

  • Jeong, Hyun-Cheol;Hong, Soon-Dal
    • Korean Journal of Soil Science and Fertilizer
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    • v.41 no.2
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    • pp.126-136
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    • 2008
  • Tobacco plants grown in pots by sand culture for 70 days after transplanting were used to evaluate the sensing distance and measurement efficiency of ground-based remote sensors. The leaf distribution of tobacco plant and sensing distance from the sensors to the target leaves were controlled by two removal methods of leaves, top-down and bottom-up removal. In the case of top-down removal, the canopy reflectance was measured by the sensor located at a fixed position having an optimum distance from the detector to the uppermost leaf of tobacco every time that the higher leaves were one at a time. The measurement of bottom-up removal, a the other hand, was conducted in the same manner as that of the top-down removal except that the lower leaves were removed one by one. Canopy reflectance measurements were made with hand held spectral sensors including the active sensors such as $GreenSeeker^{TM}$ red and green, $Crop\;Circle\;ACS-210^{TM}$ red and amber, the passive sensors of $Crop\:Circle^{TM}$, and spectroradiometer $SD2000^{TM}$. The reflectance indices by all sensors were generally affected by the upper canopy condition rather than lower canopy condition of tobacco regardless of sensor type, passive or active. The reflectance measurement by $GreenSeeker^{TM}$ was affected sensitively at measurement distance longer than 120 cm, the upper limit of effective sensing distance, beyond which measurement errors are appreciable. In case of the passive sensors that has no upper limit of effective distance and $Crop\;Circle^{TM}(ACS210)$ that has the upper limit of effective sensing distance specified with 213 cm, longer than that of estimated distance, the measurement efficiency affected by the sensing distance showed no difference. This result suggests that it is necessary to use the sensor specified optimum distance. The result revealed that active sensors are more superior than their passive counterparts in establishing between the relative ratio of reflectance index and the dry weight of tobacco treated by top-down removal, and in the evaluation of biomass. $The\;Crop\;Circle\;ACS-210^{TM}$ red was proved to have the highest efficiency of measurement, followed by $Crop\;Circle^{TM}(ACS210)$ amber and $GreenSeeker^{TM}$ red, $Crop\;Circle^{TM}$ passive, $GreenSeeker^{TM}$ green, and spectroradiometer, in descending order.

Choroidal Thickness in Thyroid-associated Ophthalmopathy between Normal Tension Glaucoma Using Optical Coherence Tomography (스펙트럼영역 빛간섭단층촬영으로 측정한 갑상선 안병증 환자와 녹내장환자의 맥락막 두께 분석)

  • Lee, Bo Young;La, Tae Yoon;Choi, Jin A
    • Journal of The Korean Ophthalmological Society
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    • v.58 no.8
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    • pp.960-967
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    • 2017
  • Purpose: To compare the macular choroidal thickness in patients with thyroid-associated ophthalmopathy (TAO) with those with normal tension glaucoma (NTG). Methods: A total of 70 normal eyes, 74 eyes with TAO and 60 eyes with NTG were enrolled in this study. All patients underwent spectral-domain optical coherence tomography (SD-OCT) (Cirrus HD-OCT, Carl Zeiss Meditec Inc., Dublin, CA, USA). Macular choroidal thickness was assessed using enhanced depth imaging. The average macular choroidal thickness was defined as the average value of three measurements: at the fovea and at the points located 1.5 mm in the nasal and temporal directions from the fovea. Generalized estimating equations were used to uncover factors affecting the average macular choroidal thickness. Results: The average, superior and inferior quadrant retinal nerve fiber layer thicknesses were significantly thinner in the NTG group compared with the TAO and control groups (p < 0.001). The average macular choroidal thickness of the TAO group, NTG group and controls was $281.01{\pm}60.06{\mu}m$, $241.66{\pm}55.00{\mu}m$ and $252.07{\pm}55.05{\mu}m$, respectively, which were significantly different (p = 0.013). The subfoveal, nasal and temporal side choroidal thicknesses were significantly thinner in the NTG group compared with the TAO group (p = 0.014, 0.012 and 0.034, respectively). Subjects with TAO were associated with a thicker average macular choroidal thickness compared with the NTG group after adjusting for age, sex, spherical equivalent and intraocular pressure (${\beta}=32.61$, p = 0.017). Conclusions: Macular choroidal thickness was significantly thicker in patients with TAO compared with those with NTG. Further evaluation is required to determine if a thick choroid in subjects with TAO has any role in glaucomatous optic neuropathy.

Review of applicability of Turbidity-SS relationship in hyperspectral imaging-based turbid water monitoring (초분광영상 기반 탁수 모니터링에서의 탁도-SS 관계식 적용성 검토)

  • Kim, Jongmin;Kim, Gwang Soo;Kwon, Siyoon;Kim, Young Do
    • Journal of Korea Water Resources Association
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    • v.56 no.12
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    • pp.919-928
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    • 2023
  • Rainfall characteristics in Korea are concentrated during the summer flood season. In particular, when a large amount of turbid water flows into the dam due to the increasing trend of concentrated rainfall due to abnormal rainfall and abnormal weather conditions, prolonged turbid water phenomenon occurs due to the overturning phenomenon. Much research is being conducted on turbid water prediction to solve these problems. To predict turbid water, turbid water data from the upstream inflow is required, but spatial and temporal data resolution is currently insufficient. To improve temporal resolution, the development of the Turbidity-SS conversion equation is necessary, and to improve spatial resolution, multi-item water quality measurement instrument (YSI), Laser In-Situ Scattering and Transmissometry (LISST), and hyperspectral sensors are needed. Sensor-based measurement can improve the spatial resolution of turbid water by measuring line and surface unit data. In addition, in the case of LISST-200X, it is possible to collect data on particle size, etc., so it can be used in the Turbidity-SS conversion equation for fraction (Clay: Silt: Sand). In addition, among recent remote sensing methods, the spatial distribution of turbid water can be presented when using UAVs with higher spatial and temporal resolutions than other payloads and hyperspectral sensors with high spectral and radiometric resolutions. Therefore, in this study, the Turbidity-SS conversion equation was calculated according to the fraction through laboratory analysis using LISST-200X and YSI-EXO, and sensor-based field measurements including UAV (Matrice 600) and hyperspectral sensor (microHSI 410 SHARK) were used. Through this, the spatial distribution of turbidity and suspended sediment concentration, and the turbidity calculated using the Turbidity-SS conversion equation based on the measured suspended sediment concentration, was presented. Through this, we attempted to review the applicability of the Turbidity-SS conversion equation and understand the current status of turbid water occurrence.