• Journal of Korea Water Resources Association
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• v.56 no.2
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• pp.91-101
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• 2023

In this study, we estimated the concentration of chlorophyll-a (Chl-a) using hyperspectral water surface reflectance in an inland weir (Baekjae weir) and estuarine reservoir (Namyang Reservoir) for monitoring the occurrence of algae in freshwater in South Korea. The hyperspectral reflectance was measured by aircraft in Baekjae Weir (BJW) from 2016 to 2017, and a drone in Namyang Reservoir (NYR) from 2020 to 2021. The 30 reflectance bands (BJW: 400-530, 620-680, 710-730, 760-790 nm, NYR: 400-430, 655-680, 740-800 nm) that were highly related to Chl-a concentration were selected using permutation importance. Artificial neural network based Chl-a estimation model was developed using the selected reflectance in both water bodies. And the performance of the model was evaluated with the coefficient of determination (R²), the root mean square error (RMSE), and the mean absolute error (MAE). The performance evaluation results of the Chl-a estimation model for each watershed was R²: 0.63, 0.82, RMSE: 9.67, 6.99, and MAE: 11.25, 8.48, respectively. The developed Chl-a model of this study may be used as foundation tool for the optimal management of freshwater algal blooms in the future.

• Korean Journal of Remote Sensing
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• v.39 no.2
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• pp.183-192
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• 2023

The remotely sensed data, such as satellite imagery and aerial photos, can be used to extract and detect some objects in the image through image interpretation and processing techniques. Significantly, the possibility for utilizing digital map updating and land monitoring has been increased through automatic object detection since spatial resolution of remotely sensed data has improved and technologies about deep learning have been developed. In this paper, we tried to extract plastic greenhouses into aerial orthophotos by using fully convolutional densely connected convolutional network (FC-DenseNet), one of the representative deep learning models for semantic segmentation. Then, a quantitative analysis of extraction results had performed. Using the farm map of the Ministry of Agriculture, Food and Rural Affairsin Korea, training data was generated by labeling plastic greenhouses into Damyang and Miryang areas. And then, FC-DenseNet was trained through a training dataset. To apply the deep learning model in the remotely sensed imagery, instance norm, which can maintain the spectral characteristics of bands, was used as normalization. In addition, optimal weights for each band were determined by adding attention modules in the deep learning model. In the experiments, it was found that a deep learning model can extract plastic greenhouses. These results can be applied to digital map updating of Farm-map and landcover maps.

• Analytical Science and Technology
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• v.21 no.6
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• pp.535-542
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• 2008

A liquid chromatography-electrospray ionization tandem mass spectrometry (LC-ESI/MS/MS) method was developed for the determination and confirmation of clenbuterol in bovine muscle and milk. Clenbuterol and clenbuterol-D9 using as an internal standard in samples were extracted with ethyl acetate after hydrolysis and evaporated to dryness. The extracts were dissolved in 20% methanol and cleaned using HLB solid-phase extraction cartridge. The analytes were detected by LC-ESI/MS/MS on a $C_{18}$ column. Mass spectral acquisition was done in selected reaction monitoring (SRM) in positive ion mode to provide a high degree of sensitivity. Using MS/MS with SRM mode, the transitions (precursor to product) monitored were m/z 277${\rightarrow}$203 for clenbuterol, and m/z 286${\rightarrow}$204 for internal standard. The limits of quantitation (LOQ) and mean recoveries of clenbuterol in bovine muscle were $0.2{\mu}g/kg$ and 84.3~91.1%, respectively. The LOQ and mean recoveries in milk were $0.05{\mu}g/kg$ and 87.7~98.3%, respectively.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.3A
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• pp.305-313
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• 2008

A reliability based calibration of dynamic load allowance (DLA) of highway bridge is performed by numerical dynamic analysis of various types of bridges taking into account of the road surface roughness and bridge-vehicle interaction. A total of 10 simply supported bridges with three girder types in the form of prestressed concrete girder, steel plate girder, and steel box girder is analyzed. The cross sections recommended in "The Standardized Design of Highway Bridge Superstructure" by the Korean Ministry of Construction are used for the prestressed concrete girder bridges and steel plate girder bridges while the box girder bridges are designed by the LRFD method. Ten sets of road surface roughness for each bridge are generated from power spectral density (PSD) function by assuming the roadway as "Average Road". A three dimensionally modeled 5-axle tractor-trailer with its gross weight the same as that of DB-24 design truck is used in the dynamic analysis. For the finite element modeling of superstructure, beam elements for the main girder, shell elements for concrete deck, and rigid links between main girder and concrete deck are used. The statistical mean and coefficient of variation of DLA are obtained from a total of 100 DLA results for 10 different bridges with each having 10 sets of road surface roughness. Applying the DLA statistics obtained, the DLA is finally calibrated in a reliability based LRFD format by using the formula developed in the calibration of OHBDC code.

• Journal of The Geomorphological Association of Korea
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• v.27 no.1
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• pp.1-19
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• 2020

A river bed which is submerged in water at high flow and becomes part of the river at low flow, serves as a bridge between the river and the land. The channel bar creates a unique ecosystem with vegetation adapted to the particular environment and the water pool forms a wetland that plays a very important role in the environment. To evaluate anthropogenic impacts on the river bed in the Middle Yeongsangang River, the fluvial landforms in the stream channel were analyzed using multi-temporal remotely-sensed images. In the aerial photograph of 2005 taken before the construction of the large weirs, oxbow lakes, mid-channel bars, point bars, and natural wetlands between the artificial levees were identified. Multiple bars divided the flow of stream water to cause the braided pattern in a particular section. After the construction of the Seungchon weir, aerial photographs of 2013 and 2015 revealed that most of the fluvial landforms disappeared due to the dredging of its riverbed and water level control(maintenance at 7.5El.m). Sentinel-2 images were analyzed to identify differences between before and after the opening of weir gate. Change detection was performed with the near infrared and shortwave infrared spectral bands to effectively distinguish water surfaces from land. As a result, water surface area of the main stream of the Yeongsangang River decreased by 40% from 1.144km² to 0.692km². A large mid-channel bar that has been deposited upstream of the weir was exposed during low water levels, which shows the obvious influence of weir on the river bed. Newly formed unvegetated point bars that were deposited on the inside of a meander bend were identified from the remotely sensed images. As the maintenance period of the weir gate opening was extended, various habitats were created by creating pools and riffles around the channel bars. Considering the ecological and hydrological functions of the river bed, it is expected that the increase in bar areas through weir gate opening will reduce the artificial interference effect of the weir.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.245-257
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• 2023

The representative crop in the Republic of Korea, rice, is cultivated over extensive areas every year, which resulting in reduced resistance to pests and diseases. One of the major rice diseases, rice blast disease, can lead to a significant decrease in yields when it occurs on a large scale, necessitating early detection and effective control of rice blast disease. Drone-based crop monitoring techniques are valuable for detecting abnormal growth, but frequent image capture for potential rice blast disease occurrences can consume significant labor and resources. The purpose of this study is to early detect rice blast disease using remote sensing data, such as drone and satellite images, along with weather data. Satellite images was helpful in identifying rice cultivation fields. Effective detection of paddy fields was achieved by utilizing vegetation and water indices. Subsequently, air temperature, relative humidity, and number of rainy days were used to calculate the risk of rice blast disease occurrence. An increase in the risk of disease occurrence implies a higher likelihood of disease development, and drone measurements perform at this time. Spectral reflectance changes in the red and near-infrared wavelength regions were observed at the locations where rice blast disease occurred. Clusters with low vegetation index values were observed at locations where rice blast disease occurred, and the time series data for drone images allowed for tracking the spread of the disease from these points. Finally, drone images captured before harvesting was used to generate spatial information on the incidence of rice blast disease in each field.

• Journal of the Korean earth science society
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• v.44 no.6
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• pp.594-610
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• 2023

The horizontal-to-vertical spectral ratio (HVSR) has been widely applied to evaluate ground characteristics such as site response and thickness of the soft sedimentary layer on top of the bedrock via dominant frequencies and amplification factors of microtremors. Eight seismic stations were selected to investigate the HVSR results at the surface and at varying depths, and their variations due to wind speeds. These stations are equipped with seismic sensors on the surface and downhole(s) at depths. The borehole data analysis reveals that the geological condition at burial depth influences the HVSR results. Their dominant frequencies indicate the entire thickness of the soft layer, not the thickness to the bottom or top of the soft sedimentary layer from the seismometer burial depth. Analysis of the background noise observed at the surface showed that the resonance frequency estimation varied with wind speed changes. In the studied cases, the background noise observed in the sedimentary layer at depths of 20 to 66 meters yielded stable and consistent resonance frequency estimation regardless of wind speed fluctuations. The results of the seismic sensors buried deeper than 100 meters are unstable. The result indicates that the background noise from the buried seismometer at shallow depths (~0.3 m) under light wind conditions (wind speeds less than 3 m/s) is sufficient to achieve the purpose of the HVSR analysis.

• Nuclear Engineering and Technology
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• v.55 no.10
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• pp.3913-3923
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• 2023

Todays, medium energy resolution detectors are preferably used in radioisotope identification devices(RID) in nuclear and radioactive material categorization. However, there is still a need to develop or enhance « automated identifiers » for the useful RID algorithms. To decide whether any material is SNM or NORM, a key parameter is the better energy resolution of the detector. Although masking, shielding and gain shift/stabilization and other affecting parameters on site are also important for successful operations, the suitability of the RID algorithm is also a critical point to enhance the identification reliability while extracting the features from the spectral analysis. In this study, a RID algorithm based on Bayesian statistical method has been modified for medium energy resolution detectors and applied to the uranium gamma-ray spectra taken by a LaBr3:Ce detector. The present Bayesian RID algorithm covers up to 2000 keV energy range. It uses the peak centroids, the peak areas from the measured gamma-ray spectra. The extraction features are derived from the peak-based Bayesian classifiers to estimate a posterior probability for each isotope in the ANSI library. The program operations were tested under a MATLAB platform. The present peak based Bayesian RID algorithm was validated by using single isotopes(²⁴¹Am, ⁵⁷Co, ¹³⁷Cs, ⁵⁴Mn, ⁶⁰Co), and then applied to five standard nuclear materials(0.32-4.51% at.²³⁵U), as well as natural U- and Th-ores. The ID performance of the RID algorithm was quantified in terms of F-score for each isotope. The posterior probability is calculated to be 54.5-74.4% for ²³⁸U and 4.7-10.5% for ²³⁵U in EC-NRM171 uranium materials. For the case of the more complex gamma-ray spectra from CRMs, the total scoring (ST) method was preferred for its ID performance evaluation. It was shown that the present peak based Bayesian RID algorithm can be applied to identify ²³⁵U and ²³⁸U isotopes in LEU or natural U-Th samples if a medium energy resolution detector is was in the measurements.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1427-1435
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• 2023

Vegetation indices based on selected wavelength reflectance measurements are used to represent crop growth and physiological conditions. However, the anisotropic properties of the crop canopy surface can govern spectral reflectance and vegetation indices. In this study, we applied an ensemble of bidirectional reflectance distribution function (BRDF) models to high-resolution Sentinel-2 satellite imagery and compared the differences between correction results before and after reflectance. In the red and near-infrared (NIR) band reflectance images, BRDF-corrected outlier values appeared in certain urban and paddy fields of farmland areas and forest shadow areas. These effects were equally observed when calculating the normalized difference vegetation index (NDVI) and 2-band enhanced vegetation index (EVI2). Furthermore, the outlier values in corrected NIR band were shown in pixels shadowed by mountain terrain. These results are expected to contribute to the development and improvement of BRDF models in high-resolution satellite images.

• Korean Journal of Optics and Photonics
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• v.34 no.6
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• pp.241-247
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• 2023

We examine the spectral characteristics of laser-induced periodic surface structures (LIPSSs) formed on an amorphous silicon film irradiated by a 355-nm nanosecond laser. A Gaussian beam with a diameter of 196 ㎛ is used to perform a two-dimensional raster scan. The laser's pulse number is varied from 190 to 280, and its intensity is adjusted within 100-130 mJ/cm². LIPSSs with a periodicity of approximately 330 nm form on the surface of the Si film, aligned perpendicular to the laser's polarization. Transmission spectra of the samples show dips around 700 nm for transverse electric polarization and around 500 nm for transverse magnetic polarization. The features are investigated with a one-dimensional-grating model using a rigorous coupled-wave analysis. Simulations confirm that the observed dips are due to the resonant modes, depending on the polarization.