• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume I
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• pp.512-515
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• 2006

Forest stand height and volume are important indicators for management purpose as well as for the environmental analysis. Shuttle Radar Topography Mission (SRTM) is backscattered over forest canopy and DSM can be acquired from such scattering characteristic, while National Elevation Dataset (NED) provides bare earth elevation data. The difference between SRTM and NED is estimated as tree height, and it is correlated with forest parameters, it is correlated with forest parameters, including average DBH, Trees per acre, net BF per acre, and total Net MBF. Especially, among them, net Board Foot(BF) per acre is the index that well represents forest volume. The Project site was Douglas-fir dominating plantation area in the western Washington an the northern Oregon in the U.S. This study shows a relationship of high correlation between the forest parameters and the product from SRTM, NED, and ETM+. This research performs multi regression analysis and regression tree algorithm, and can get more improved relationship between several parameters.

• 대한원격탐사학회지
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• 제22권5호
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• pp.427-431
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• 2006

Forest stand height and volume are important indicators for management purpose as well as for the environmental analysis. Shuttle Radar Topography Mission (SRTM) is backscattered over forest canopy and DSM can be acquired from such scattering characteristic, while National Elevation Dataset (NED) provides bare earth elevation data. The difference between SRTM and NED is estimated as tree height, and it is correlated with forest parameters, it is correlated with forest parameters, including average DBH, Trees per acre, net BF per acre, and total Net MBF. Especially, among them, net Board Foot(BF) per acre is the index that well represents forest volume. The Project site was Douglas-fir dominating plantation area in the western Washington an the northern Oregon in the U.S. This study shows a relationship of high correlation between the forest parameters and the product from SRTM, NED, and ETM+. This research performs multi regression analysis and regression tree algorithm, and can get more improved relationship between several parameters.

• 한국환경과학회지
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• 제28권1호
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• pp.19-35
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• 2019

This study investigates the performance of four Bayesian methods, Random Walk Metropolis (RWM), Hit-And-Run Metropolis (HARM), Adaptive Mixture Metropolis (AMM), and Population Monte Carlo (PMC), for estimating the parameters and uncertainties of probability rainfall distribution, and the results are compared with those of conventional parameter estimation methods; namely, the Method Of Moment (MOM), Maximum Likelihood Method (MLM), and Probability Weighted Method (PWM). As a result, Bayesian methods yield similar or slightly better results in parameter estimations compared with conventional methods. In particular, PMC can reduce parameter uncertainty greatly compared with RWM, HARM, and AMM methods although the Bayesian methods produce similar results in parameter estimations. Overall, the Bayesian methods produce better accuracy for scale parameters compared with the conventional methods and this characteristic improves the accuracy of probability rainfall. Therefore, Bayesian methods can be effective tools for estimating the parameters and uncertainties of probability rainfall distribution in hydrological practices, flood risk assessment, and decision-making support.

• 한국환경과학회지
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• 제14권1호
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• pp.33-40
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• 2005

The size of minimum order stream has a very sensitive effect on runoff analysis model using the divergence characteristic of stream. Therefore, in this study, the threshold area of minimum order stream has been examined the change characteristic of topographical parameters. The subject basin of the research was the upper basin of the Kumho water gage station which is located in the middle of the Kumho river. The 1:25,000 numerical geography which was constructed $10{\times}10m$ mesh was used. The range of investigation of topographical parameters are number of stream order, length, area, slope, basin relief, sinuosity ratio, drainage density and total stream length etc. It was found from the result of analysis that the threshold value of minimum order stream has a very big effect on topographical parameters of basin. It was found that the threshold area of minimum ord er stream revealed under $0.10km^{2}.$ Furthermore, the parameters showed a serious change except for over $0.10km^{2}.$

• Environmental Sciences Bulletin of The Korean Environmental Sciences Society
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• 제4권2호
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• pp.71-78
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• 2000

The chlorination of municipal drinking water supplies leads to the formation of so-called disinfection by-products(DBPs), many of which have been reported to cause harmful health effects based on animal studies. This study was conducted: 1) to observe seasonal changes in the major DBPs at four sampling sites on a drinking water distribution system located in Chunchon, Kangwon Do; and 2) to examine the effects of major water quality parameters on the formation of DBPs. During the field sampling, the water temperature, pH, and total and free chlorine residuals were all measured. The water samples were then analyzed for total organic carbon(TOC) and eight disinfection by-products in the laboratory. Chloroform, dichloroacetic acid, and trichloroacetic acid were the major constituents of the measured DBPs. The concentrations of the total DBPs were highest in fall, particularly in October, and lowest in summer. The concentrations of the total DBPs increased with increasing TOC concentrations. Multiple regression analyses showed that the concentrations of chloroform, bromodichloromethane, and chloral hydrate were linearly correlated with the pH. Other water parameters were not included in the regression equations. Accordingly, these results suggest that TOC and pH are both important factors in the formation of DBPs.

• 한국공간구조학회논문집
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• 제21권2호
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• pp.99-110
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• 2021

This study presents the estimation of crack depth by analyzing temperatures extracted from thermal images and environmental parameters such as air temperature, air humidity, illumination. The statistics of all acquired features and the correlation coefficient among thermal images and environmental parameters are presented. The concrete crack depths were predicted by four different machine learning models: Multi-Layer Perceptron (MLP), Random Forest (RF), Gradient Boosting (GB), and AdaBoost (AB). The machine learning algorithms are validated by the coefficient of determination, accuracy, and Mean Absolute Percentage Error (MAPE). The AB model had a great performance among the four models due to the non-linearity of features and weak learner aggregation with weights on misclassified data. The maximum depth 11 of the base estimator in the AB model is efficient with high performance with 97.6% of accuracy and 0.07% of MAPE. Feature importances, permutation importance, and partial dependence are analyzed in the AB model. The results show that the marginal effect of air humidity, crack depth, and crack temperature in order is higher than that of the others.

• 한국콘크리트학회:학술대회논문집
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• 한국콘크리트학회 2006년도 춘계학술발표회 논문집(I)
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• pp.334-337
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• 2006

Generally, fragility curve has been used in predicting failure of structures due to seismic actions. In this research, the method of drawing fragility curve has been applied to evaluating success/failure of structures and satisfactory/unsatisfactory of concrete mixture performance based on material parameters. In the paper, a detailed explanation of the procedure of drawing fragility curve based on material parameter has been introduced. Fragility curve generating procedure includes generation of virtual data points from limited number of actual data points by bell curve implementation, determination of success/failure status of each data point by assigned criterion, and completion of final fragility curve. For practical applications, workability of concrete mixture content based on "unit water" has been used to obtain fragility curve. Detailed explanation of fragility curve drawing procedure for material parameters is presented.

• Computers and Concrete
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• 제20권1호
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• pp.23-29
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• 2017

In this study engineered steel fibres used as reinforcement for concrete were characterized by number of key mechanical and spatial parameters, which are easy to measure and quantify. Such commonly used parameters as length, diameter, fibre intrinsic efficiency ratio (FIER), hook geometry, tensile strength and ductility were considered. Effective classification of various fibres was demonstrated using simple multivariate computations involving principal component analysis (PCA). Contrary to univariate data mining approach, the proposed analysis can be efficiently adapted for fast, robust and direct classification of engineered steel fibres. The results have revealed that in case of particular spatial/geometrical conditions of steel fibres investigated the FIER parameter can be efficiently replaced by a simple aspect ratio. There is also a need of finding new parameters describing properties of steel fibre more precisely.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2002년도 Proceedings of International Symposium on Remote Sensing
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• pp.442-447
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• 2002

When a SAR system operates in a full-polarimetic mode, the amount of the information one can extract is so complex that the effective presentation of the information is important. However, the information acquired from the polarimetric SAR data is often difficult to interpret by itself, because it is consisted of both the amplitude information and the phase information. Polarimetric parameters are the good way of representing the polarimetric SAR information in a quantitative manner. Also they can characterize the scattering behavior of the ground scatterer. In this research, extraction of polarimetric parameters, evaluation and interpretation of the scattering behavior of the ground with respect to polarimetric SAR signal are carried out. Using the NASA/JPL AIRSAR data, we estimated the polarimetric parameters and compared them in terms of the ground features. In general, extracted parameters well represent the characteristics of the different features on the ground.

• 한국지하수토양환경학회지:지하수토양환경
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• 제25권1호
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• pp.37-52
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• 2020

Sensitivity analysis of hydrodynamic and reaction parameters in conceptual model reflecting aquifer characteristics of Korea was performed to evaluate the uncertainty in the predicted concentrations. Among the hydrodynamic input parameters, both hydraulic conductivity (K_x) and hydraulic gradient (I) affected transport behaviors of contaminants, and resulted in same convergence concentrations with continuous injections of contaminant. However, longitudinal dispervisity (α_L) affected both transport behaviors and the convergence concentrations of contaminants. Compared to the hydrodynamic parameters, growth kinetic and degradation parameters (μ_m & K_c) more significantly affected both transport behaviors and the convergence concentrations of contaminants, indicating those parameters had higher sensitivity indices causing the uncertainties of model predictions. Considering that the sensitivity indices of both hydrodynamic and reaction parameters were a function of transport distance of groundwater, the parameters with higher sensitivity indices, a priori, need to be investigated using conceptual model reflecting site-specific aquifer characteristics before field investigation. After determining the parameters with higher sensitivity indices, the detail field investigations for the selected hydrodynamic and reaction parameters were warranted to reduce the uncertainties of model predictions.