• Korean Journal of Remote Sensing
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• v.27 no.2
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• pp.191-201
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• 2011

Soybean has widely grown for its edible bean which has numerous uses. Microwave remote sensing has a great potential over the conventional remote sensing with the visible and infrared spectra due to its all-weather day-and-night imaging capabilities. In this investigation, a ground-based polarimetric scatterometer operating at multiple frequencies was used to continuously monitor the crop conditions of a soybean field. Polarimetric backscatter data at L, C, and X-bands were acquired every 10 minutes on the microwave observations at various soybean stages. The polarimetric scatterometer consists of a vector network analyzer, a microwave switch, radio frequency cables, power unit and a personal computer. The polarimetric scatterometer components were installed inside an air-conditioned shelter to maintain constant temperature and humidity during the data acquisition period. The backscattering coefficients were calculated from the measured data at incidence angle $40^{\circ}$ and full polarization (HH, VV, HV, VH) by applying the radar equation. The soybean growth data such as leaf area index (LAI), plant height, fresh and dry weight, vegetation water content and pod weight were measured periodically throughout the growth season. We measured the temporal variations of backscattering coefficients of the soybean crop at L, C, and X-bands during a soybean growth period. In the three bands, VV-polarized backscattering coefficients were higher than HH-polarized backscattering coefficients until mid-June, and thereafter HH-polarized backscattering coefficients were higher than VV-, HV-polarized back scattering coefficients. However, the cross-over stage (HH > VV) was different for each frequency: DOY 200 for L-band and DOY 210 for both C and X-bands. The temporal trend of the backscattering coefficients for all bands agreed with the soybean growth data such as LAI, dry weight and plant height; i.e., increased until about DOY 271 and decreased afterward. We plotted the relationship between the backscattering coefficients with three bands and soybean growth parameters. The growth parameters were highly correlated with HH-polarization at L-band (over r=0.92).

• Journal of the Korean Institute of Navigation
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• v.12 no.1
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• pp.71-84
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• 1988

For traffic proceeding in random directions on a plane surface the frequency of collision, if no avoiding action in taken ,is approximately proportional to the square of the traffic density and directly proportional to the size and speed of the ship, Avoiding is normally taken and the rte of collisions is therefore also governed by additional factors such as the visibility, the effectiveness of the collisionavoidance rules, the competence of personnel or watchkeeping attitude, the maneuverability of the ship and the efficiency of radar and other equipments. From the viewpoint of watchkeeper who is responsible for maneuvering, watchkeeping attitude such as lookout and action to avoid collision is the most controllable factor among those mentioned above. In practice, according to the investigation of the institution of marine courts, about 50% co collisions occurred is caused by disorbedience to steering and sailing rules of international regulations for preventing collision at sea including lookout. So we classify the process of collisions with first sight of another ship , assessment of risk of collisions and action to avoid collisions and make a factural survey about lookout and action to avoid collisions from the point on "time" and " distance", namely relationship among ship's size, speed, first sight time of another ship, action to avoid collisions ,and distance from sight of another ship to collision occurred. According to the results of the actual survey , we come to conclude that most of collisions occurred are due to improper lookout and ineffective action to avoid collision which means time lag from first sight of another ship to time of action taken to avoid collision is relatively long. is relatively long.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2004.08a
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• pp.139-145
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• 2004

It is well known that human errors is involved in most of maritime accidents. For the purpose of reducing the influence of human elements on maritime activities, it is necessary to identify the human unsafe acts in those activities. The commonly used methods in identification of human unsafe acts are maritime accident statistics or case analysis. With the statistics data, people could roughly identify what kinds of unsafe acts or human errors have played active role in the accident, however, they often neglected some active unsafe acts while overestimated some mini-unsafe acts because of the inherent shortcoming of the methods. There should be some more accurate approaches for human error identification in maritime accidents. In this paper, the application of technique called grey relational analysis (GRA) into the identification of human unsafe acts is presented. GRA is used to examine the extent of connections between two digits by applying the, methodology of departing and scattering measurement to actual distance measurement. Based on the statistics data of maritime accidents occurred in Chinese waters in last 10years, the relationship between the happening times of maritime accidents and that of unsafe acts are established with GRA. In accordance with the value of grey relational grade, the identified main human unsafe acts involved in maritime accidents are ranked in following orders: improper lookout, improper use of radar and equivalent equipment, error of judgment, act not in time, improper communication, improper shiphandling, use of unsafe speed, violating the rule and ignorance of good seamanship. The result shows that GRA is an effective and practical technique in improving the accuracy of human unsafe acts identification.

• Korean Journal of Remote Sensing
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• v.27 no.3
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• pp.213-223
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• 2011

The purpose of this study is to estimate the spherical wave parameters that appears in synthetic aperture radar (SAR) image acquired over the coast of Chukk, Micronesia. The retrieval of ocean wave parameters consists of two main stages: the first is to determine the dominant wavelengths by Fast Fourier Transform (FFT) over 16 sub-image areas and the second is to estimate wave slopes and heights using dispersion relationship under various water wave conditions. It is assumed that the spherical waves are linear and progressive. These type of waves have the range and azimuth components traveling in radial directions. The azimuth travelling waves are more affected by the velocity bunching mechanism and it is difficult to estimate the wave parameters for these affected areas in SAR imagery. In order to compensate these effects, the velocity bunching ratio (VBR) based on modulation transfer function (MTF) was compared with the intensity ratio for neighbor area in the radial direction in order to assign the spherical wave properties for azimuthally travelling waves. Dispersion relation provides the good estimates for the wave heights for all the selected sub-image areas in the range of 1m to 2m. VBR based on MTF was found to be 0.78 at wave height of 1.36m, while the intensity-based VBR was 0.69 which corresponds to the height of 1.75m. It can be said that the velocity bunching accounts for azimuthally travelling spherical waves and the difference results from the sea-bottom effects.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.27 no.2
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• pp.188-197
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• 2016

In this paper, we propose a method that represents a mathematical form of wave propagation by using the fact the refractive index determining wave propagation characteristic is a function of altitude. Proposed method uses Snell's law that expresses relationship between incident angle and refraction angle when incident wave passes medium having a different refractive index. We present the simulation results about wave propagation by setting the square of refractive index in the form of the polynomial for altitude and show that it is possible to estimate the coefficients of the polynomial through the angle information from vertical axis of multiple radar systems.

• Computers and Concrete
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• v.32 no.6
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• pp.577-594
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• 2023

Engineered cementitious composites with calcined clay limestone cement (LC³-ECC) as a kind of green, low-carbon and high toughness concrete, has recently received significant investigation. However, the complicated relationship between potential influential factors and LC³-ECC compressive strength makes the prediction of LC³-ECC compressive strength difficult. Regarding this, the machine learning-based prediction models for the compressive strength of LC³-ECC concrete is firstly proposed and developed. Models combine three novel meta-heuristic algorithms (golden jackal optimization algorithm, butterfly optimization algorithm and whale optimization algorithm) with support vector regression (SVR) to improve the accuracy of prediction. A new dataset about LC³-ECC compressive strength was integrated based on 156 data from previous studies and used to develop the SVR-based models. Thirteen potential factors affecting the compressive strength of LC³-ECC were comprehensively considered in the model. The results show all hybrid SVR prediction models can reach the Coefficient of determination (R²) above 0.95 for the testing set and 0.97 for the training set. Radar and Taylor plots also show better overall prediction performance of the hybrid SVR models than several traditional machine learning techniques, which confirms the superiority of the three proposed methods. The successful development of this predictive model can provide scientific guidance for LC³-ECC materials and further apply to such low-carbon, sustainable cement-based materials.

• Korean Journal of Soil Science and Fertilizer
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• v.44 no.5
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• pp.878-886
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• 2011

The soybean is one of the oldest cultivated crops in the world. Microwave remote sensing is an important tool because it can penetrate into cloud independent of weather and it can acquire day or night time data. Especially a ground-based polarimetric scatterometer has advantages of monitoring crop conditions continuously with full polarization and different frequencies. In this study, soybean growth parameters and soil moisture were estimated using polarimetric discrimination ratio (PDR) by radar scatterometer. A ground-based polarimetric scatterometer operating at multiple frequencies was used to continuously monitor the soybean growth condition and soil moisture change. It was set up to obtain data automatically every 10 minutes. The temporal trend of the PDR for all bands agreed with the soybean growth data such as fresh weight, Leaf Area Index, Vegetation Water Content, plant height; i.e., increased until about DOY 271 and decreased afterward. Soil moisture lowly related with PDR in all bands during whole growth stage. In contrast, PDR is relative correlated with soil moisture during below LAI 2. We also analyzed the relationship between the PDR of each band and growth data. It was found that L-band PDR is the most correlated with fresh weight (r=0.96), LAI (r=0.91), vegetation water content (r=0.94) and soil moisture (r=0.86). In addition, the relationship between C-, X-band PDR and growth data were moderately correlated ($r{\geq}0.83$) with the exception of the soil moisture. Based on the analysis of the relation between the PDR at L, C, X-band and soybean growth parameters, we predicted the growth parameters and soil moisture using L-band PDR. Overall good agreement has been observed between retrieved growth data and observed growth data. Results from this study show that PDR appear effective to estimate soybean growth parameters and soil moisture.

• Journal of Korea Water Resources Association
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• v.45 no.9
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• pp.853-860
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• 2012

It is well-known that loop effect of the stage-discharge relationship is formulated based on many field observations especially for the sand rivers. Theoretical understandings of the loop effect for the sand rivers have been widely provided, based on the facts that it is driven by the flood wave propagation and bed form changes over the given flood period. However, very few theoretical studies or field observations associated with loop-rating curves in the gravel or rock-bed mountain streams have been attempted so far, due particularly to the difficulties in the accurate discharge measurement during the flood in such field conditions. The present paper aims to report a unique loop-rating curve measured at a gravel and rock-bed mountain stream based on the flood discharge observation acquired during the typhoon, Muifa that passed nearby Jeju Island in summer of 2011. As velocity instrumentation, a non-intrusive Surface Velocity Doppler Radar to be suitable for the flood discharge measurement was utilized, and discharges were consecutively measured for every hour. Interestingly, the authors found that the hysteresis of the loop-rating curve was adverse compared to the typical trend of the sand bed streams, which means that the discharge of the rising limb is smaller than the falling limb at the same stage. We carefully speculate that the adverse trend of the loop-rating curve in the gravel bed was caused by the bed resistance change that works differently from the sand bed case.

• Journal of Korea Water Resources Association
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• v.47 no.4
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• pp.371-384
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• 2014

This study developed a new algorithm of extreme rainfall extraction based on the Communication, Ocean and Meteorological Satellite (COMS) and the Tropical Rainfall Measurement Mission (TRMM) Satellite image data and evaluated its applicability for the heavy rainfall event in July-2011 in Seoul, South Korea. The power-series-regression-based Z-R relationship was employed for taking into account for empirical relationships between TRMM/PR, TRMM/VIRS, COMS, and Automatic Weather System(AWS) at each elevation. The estimated Z-R relationship ($Z=303R^{0.72}$) agreed well with observation from AWS (correlation coefficient=0.57). The estimated 10-minute rainfall intensities from the COMS satellite using the Z-R relationship generated underestimated rainfall intensities. For a small rainfall event the Z-R relationship tended to overestimated rainfall intensities. However, the overall patterns of estimated rainfall were very comparable with the observed data. The correlation coefficients and the Root Mean Square Error (RMSE) of 10-minute rainfall series from COMS and AWS gave 0.517, and 3.146, respectively. In addition, the averaged error value of the spatial correlation matrix ranged from -0.530 to -0.228, indicating negative correlation. To reduce the error by extreme rainfall estimation using satellite datasets it is required to take into more extreme factors and improve the algorithm through further study. This study showed the potential utility of multi-geostationary satellite data for building up sub-daily rainfall and establishing the real-time flood alert system in ungauged watersheds.

• Korean Journal of Soil Science and Fertilizer
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• v.45 no.2
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• pp.127-134
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• 2012

Microwave remote sensing can help monitor the land surface water cycle, crop growth and soil moisture. A ground-based polarimetric scatterometer has an advantage for continuous crop using multi-polarization and multi-frequencies and various incident angles have been used extensively in a frequency range expanding from L-band to Ka-band. In this study, we analyzed the relationships between L-, C- and X-band signatures and soil moisture content over the whole soybean growth period. Polarimetric backscatter data at L-, C- and X-bands were acquired every 10 minutes. L-band backscattering coefficients were higher than those observed using C- or X-band over the period. Backscattering coefficients for all frequencies and polarizations increased until Day Of Year (DOY) 271 and then decreased until harvesting stage (DOY 294). Time serious of soil moisture content was not a corresponding with backscattering over the whole growth stage, although it increased relatively until early August (R2, DOY 224). We conducted the relationship between the backscattering coefficients of each band and soil moisture content. Backscattering coefficients for all frequencies were not correlated with soil moisture content when considered over the entire stage ($r{\leq}0.50$). However, we found that L-band HH polarization was correlated with soil moisture content (r=0.90) when Leaf Area Index (LAI)<2. Retrieval equations were developed for estimating soil moisture content using L-band HH polarization. Relation between L-HH and soil moisture shows exponential pattern and highly related with soil moisture content ($R^2=0.92$). Results from this study show that backscattering coefficients of radar scatterometer appear effective to estimate soil moisture content.