• Korean Journal of Remote Sensing
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• v.35 no.3
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• pp.375-387
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• 2019

The use of drone-based hyperspectral image offers considerable advantages in high resolution remote sensing applications. The primary objective of this study was to select the optimal bands based on hyperspectral image for the estimation yield of the chinese cabbage. The hyperspectral narrow bands were acquired over 403.36 to 995.19 nm using a 3.97 nm wide, 150 bands, drone-based hyperspectral imaging sensor. Fresh weight data were obtained from 2,031 sample for each field survey. Normalized difference vegetation indices were computed using red, red-edge and near-infrared bands and their relationship with quantitative each fresh weights were established and compared. As a result, predominant proportion of fresh weights are best estimated using data from three narrow bands, in order of importance, centered around 697.29 nm (red band), 717.15 nm (red-edge band) and 808.51 nm (near-infrared band). The study determined three spectral bands that provide optimal chinese cabbage productivity in the visible and near-infrared portion of the spectrum.

• Journal of Korean Society of Rural Planning
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• v.30 no.1
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• pp.57-66
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• 2024

This study aimed to develop a precise vegetation cover classification model for small streams using the combination of drone remote sensing and support vector machine (SVM) techniques. The chosen study area was the Idong stream, nestled within Geosan-gun, Chunbuk, South Korea. The initial stage involved image acquisition through a fixed-wing drone named ebee. This drone carried two sensors: the S.O.D.A visible camera for capturing detailed visuals and the Sequoia+ multispectral sensor for gathering rich spectral data. The survey meticulously captured the stream's features on August 18, 2023. Leveraging the multispectral images, a range of vegetation indices were calculated. These included the widely used normalized difference vegetation index (NDVI), the soil-adjusted vegetation index (SAVI) that factors in soil background, and the normalized difference water index (NDWI) for identifying water bodies. The third stage saw the development of an SVM model based on the calculated vegetation indices. The RBF kernel was chosen as the SVM algorithm, and optimal values for the cost (C) and gamma hyperparameters were determined. The results are as follows: (a) High-Resolution Imaging: The drone-based image acquisition delivered results, providing high-resolution images (1 cm/pixel) of the Idong stream. These detailed visuals effectively captured the stream's morphology, including its width, variations in the streambed, and the intricate vegetation cover patterns adorning the stream banks and bed. (b) Vegetation Insights through Indices: The calculated vegetation indices revealed distinct spatial patterns in vegetation cover and moisture content. NDVI emerged as the strongest indicator of vegetation cover, while SAVI and NDWI provided insights into moisture variations. (c) Accurate Classification with SVM: The SVM model, fueled by the combination of NDVI, SAVI, and NDWI, achieved an outstanding accuracy of 0.903, which was calculated based on the confusion matrix. This performance translated to precise classification of vegetation, soil, and water within the stream area. The study's findings demonstrate the effectiveness of drone remote sensing and SVM techniques in developing accurate vegetation cover classification models for small streams. These models hold immense potential for various applications, including stream monitoring, informed management practices, and effective stream restoration efforts. By incorporating images and additional details about the specific drone and sensors technology, we can gain a deeper understanding of small streams and develop effective strategies for stream protection and management.

• Korean Journal of Remote Sensing
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• v.40 no.4
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• pp.319-341
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• 2024

The utilization of multispectral imaging systems (MIS) in remote sensing has become crucial for large-scale agricultural operations, particularly for diagnosing plant health, monitoring crop growth, and estimating plant phenotypic traits through vegetation indices (VIs). However, environmental factors can significantly affect the accuracy of multispectral reflectance data, leading to potential errors in VIs and crop status assessments. This paper reviewed the complex interactions between environmental conditions and multispectral sensors emphasizing the importance of accounting for these factors to enhance the reliability of reflectance data in agricultural applications.An overview of the fundamentals of multispectral sensors and the operational principles behind vegetation index (VI) computation was reviewed. The review highlights the impact of environmental conditions, particularly solar zenith angle (SZA), on reflectance data quality. Higher SZA values increase cloud optical thickness and droplet concentration by 40-70%, affecting reflectance in the red (-0.01 to 0.02) and near-infrared (NIR) bands (-0.03 to 0.06), crucial for VI accuracy. An SZA of 45° is optimal for data collection, while atmospheric conditions, such as water vapor and aerosols, greatly influence reflectance data, affecting forest biomass estimates and agricultural assessments. During the COVID-19 lockdown,reduced atmospheric interference improved the accuracy of satellite image reflectance consistency. The NIR/Red edge ratio and water index emerged as the most stable indices, providing consistent measurements across different lighting conditions. Additionally, a simulated environment demonstrated that MIS surface reflectance can vary 10-20% with changes in aerosol optical thickness, 15-30% with water vapor levels, and up to 25% in NIR reflectance due to high wind speeds. Seasonal factors like temperature and humidity can cause up to a 15% change, highlighting the complexity of environmental impacts on remote sensing data. This review indicated the importance of precisely managing environmental factors to maintain the integrity of VIs calculations. Explaining the relationship between environmental variables and multispectral sensors offers valuable insights for optimizing the accuracy and reliability of remote sensing data in various agricultural applications.

• Investigative Magnetic Resonance Imaging
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• v.8 no.2
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• pp.79-85
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• 2004

Purpose : To evaluate the usefulness and reproducibility of $^1H$ MRS in different 1.5 T MR machines with different coils to compare the SNR, scan time and the spectral patterns in different brain regions in normal volunteers. Materials and Methods : Localized $^1H$ MR spectroscopy ($^1H$ MRS) was performed in a total of 10 normal volunteers (age; 20-45 years) with spectral parameters adjusted by the autoprescan routine (PROBE package). In all volunteers, MRS was performed in a three times using conventional MRS (Signa Horizon) with 1 channel coil and upgraded MRS (Echospeed plus with EXCITE) with both 1 channel and 8 channel coil. Using these three different machines and coils, SNRs of the spectra in both phantom and volunteers and (pre)scan time of MRS were compared. Two regions of the human brain (basal ganglia and deep white matter) were examined and relative metabolite ratios (NAA/Cr, Cho/Cr, and mI/Cr ratios) were measured in all volunteers. For all spectra, a STEAM localization sequence with three-pulse CHESS $H_2O$ suppression was used, with the following acquisition parameters: TR=3.0/2.0 sec, TE=30 msec, TM=13.7 msec, SW=2500 Hz, SI=2048 pts, AVG : 64/128, and NEX=2/8 (Signa/Echospeed). Results : The SNR was about over $30\%$ higher in Echospeed machine and time for prescan and scan was almost same in different machines and coils. Reliable spectra were obtained on both MRS systems and there were no significant differences in spectral patterns and relative metabolite ratios in two brain regions (p>0.05). Conclusion : Both conventional and new MRI systems are highly reliable and reproducible for $^1H$ MR spectroscopic examinations in human brains and there are no significant differences in applications for $^1H$ MRS between two different MRI systems.

• Investigative Magnetic Resonance Imaging
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• v.12 no.1
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• pp.20-26
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• 2008

Purpose : To present the T1 and T2 relaxation times of the major cerebral metabolites at 1.5T and 3.0T and compare those between 1.5T and 3.0T. Materials and Methods : Using the phantom containing N-acetyl aspartate (NAA), Choline (Cho), and Creatine (Cr) at both 1.5T and 3.0T MRI, the T1 relaxation times were calculated from the spectral data obtained with 5000 ms repetition time (TR), 20 ms echo time (TE), and 11 different mixing time (TM)s using STEAM (STimulated Echo-Acquisition Mode) method. The T2 relaxation times were obtained from the spectral data obtained with 3000 ms TR and 5 different TEs using PRESS (Point-RESolved Spectroscopy) method. The T1 and T2 relaxation times obtained at 1.5T were compared with those of 3.0T. Results : The T1 relaxation times of NAA were $2293\;{\pm}\;48\;ms$ at 1.5T and $2559\;{\pm}\;124\;ms$ at 3.0T (11.6% increase at 3.0T). The T1 relaxation times of Cho were $2540\;{\pm}\;57\;ms$ at 1.5T and $2644\;{\pm}\;76\;ms$ at 3.0T (4.1% increase at 3.0T). The T1 relaxation times of Cr were $2543\;{\pm}\;75\;ms$ at 1.5T and $2665\;{\pm}\;94\;ms$ at 3.0T (4.8% increase). The T2 relaxation times of NAA were $526\;{\pm}\;81\;ms$ at 1.5T and $468\;{\pm}\;74\;ms$ at 3.0T (11.0% decrease at 3.0T). The T2 relaxation times of Cho were $220\;{\pm}\;44ms$ at 1.5T and $182\;{\pm}\;35\;ms$ at 3.0T (17.3% decrease at 3.0T). The T2 relaxation times of Cr were $289\;{\pm}\;47\;ms$ at 1.5T and $275\;{\pm}\;57\;ms$ at 3.0T (4.8% decrease at 3.0T). Conclusion : The T1 relaxation times of the major cerebral metabolites (NAA, Cr, Cho), which were measured at the phantom, were 4.1%-11.6% longer at 3.0T than at 1.5T. The T2 relaxation times of them were 4.8%-17.3% shorter at 3.0T than at 1.5T. To optimize MR spectroscopy at 3.0T, TR should be lengthened and TE should be shortened.

• 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.

• Korean Journal of Remote Sensing
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• v.21 no.6
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• pp.445-456
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• 2005

The land surface parameters should be determined with sufficient accuracy, because these play an important role in climate change near the ground. As the surface reflectance presents strong anisotropy, off-nadir viewing results a strong dependency of observations on the Sun - target - sensor geometry. They contribute to the random noise which is produced by surface angular effects. The principal objective of the study is to provide a database of accurate surface reflectance eliminated the angular effects from MODIS 250m reflective channel data over Korea. The MODIS (Moderate Resolution Imaging Spectroradiometer) sensor has provided visible and near infrared channel reflectance at 250m resolution on a daily basis. The successive analytic processing steps were firstly performed on a per-pixel basis to remove cloudy pixels. And for the geometric distortion, the correction process were performed by the nearest neighbor resampling using 2nd-order polynomial obtained from the geolocation information of MODIS Data set. In order to correct the surface anisotropy effects, this paper attempted the semiempirical kernel-driven Bi- directional Reflectance Distribution Function(BRDF) model. The algorithm yields an inversion of the kernel-driven model to the angular components, such as viewing zenith angle, solar zenith angle, viewing azimuth angle, solar azimuth angle from reflectance observed by satellite. First we consider sets of the model observations comprised with a 31-day period to perform the BRDF model. In the next step, Nadir view reflectance normalization is carried out through the modification of the angular components, separated by BRDF model for each spectral band and each pixel. Modeled reflectance values show a good agreement with measured reflectance values and their RMSE(Root Mean Square Error) was totally about 0.01(maximum=0.03). Finally, we provide a normalized surface reflectance database consisted of 36 images for 2001 over Korea.

• Korean Journal of Optics and Photonics
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• v.28 no.3
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• pp.108-115
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• 2017

We report the assembly procedure and performance evaluation of a visible and near-infrared spectrometer in the wavelength region of 400-900 nm, which is later to be combined with fore-optics (a telescope) to form a f/2.5 imaging spectrometer with a field of view of ${\pm}7.68^{\circ}$. The detector at the final image plane is a $640{\times}480$ charge-coupled device with a $24{\mu}m$ pixel size. The spectrometer is in an Offner relay configuration consisting of two concentric, spherical mirrors, the secondary of which is replaced by a convex grating mirror. A double-pass test method with an interferometer is often applied in the assembly process of precision optics, but was excluded from our study due to a large residual wavefront error (WFE) in optical design of 210 nm ($0.35{\lambda}$ at 600 nm) root-mean-square (RMS). This results in a single-path test method with a Shack-Hartmann sensor. The final assembly was tested to have a RMS WFE increase of less than 90 nm over the entire field of view, a keystone of 0.08 pixels, a smile of 1.13 pixels and a spectral resolution of 4.32 nm. During the procedure, we confirmed the validity of using a Shack-Hartmann wavefront sensor to monitor alignment in the assembly of an Offner-like spectrometer.

• Journal of the Korean Society of Radiology
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• v.15 no.6
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• pp.927-933
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• 2021

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.

• Journal of the Korean Society of Radiology
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• v.5 no.6
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• pp.401-407
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• 2011

The purpose of this study is to know the differences of MR spectra, obtained from normal volunteers by variable TE value, through the quantitative analysis of brain metabolites by peak integral and SNR between 1.5T and 3.0T, together with PRESS and STEAM pulse sequence. Single-voxel MR proton spectra of the human brain obtained from normal volunteers at both 3.0T MR system (Magnetom Trio, SIEMENS, Germany) and 1.5T MR system (Signa Twinspeed, GE, USA) using the STEAM and PRESS pulse sequence. 10 healthy volunteers (3.0T:3 males, 2 females; 1.5T : 3 males, 2 females) with the range from 22 to 30 years old (mean 26 years) participated in our study. They had no personal or familial history of neurological diseases and had a normal neurological examination. Data acquisition parameters were closely matched between the two field strengths. Spectra were recorded in the white matter of the occipital lobe. Spectra were compared in terms of resolution and signal-to-noise ratio(SNR), and echo time(TE) were estimated at both field strengths. Imaging parameters was used for acquisition of the proton spectrum were as follow : TR 2000msec, TE 30ms, 40ms, 50ms, 60ms, 90ms, 144ms, 288ms, NA=96, VOI=$20{\times}20{\times}20mm3$. As the echo times were increased, the spectra obtained from 3.0T and 1.5T show decreased peak integral and SNR at both pulse sequence. PRESS pulse sequence shows higher SNR and signal intensity than those of STEAM. Especially, Spectra in normal volunteers at 3.0T demonstrated significantly improved overall SNR and spectral resolution compared to 1.5T(Fig1). The spectra acquired at short echo time, 3T MR system shows a twice improvement in SNR compared to 1.5T MR system(Table. 1). But, there was no significant difference between 3.0Tand 1.5T at long TE It is concluded that PRESS and short TE is useful for quantification of the brain metabolites at 3.0T MRS, our standardized protocol for quantification of the brain metabolites at 3.0T MRS is useful to evaluate the brain diseases by monitoring the systematic changes of biochemical metabolites concentration in vivo.