• Journal of Wetlands Research
• /
• v.18 no.2
• /
• pp.148-153
• /
• 2016

Hydraulic and hydrological flood routing methods are commonly used to analyze temporal and spatial flood influences of flood wave through a river reach. Hydrological flood routing method has relatively more simple and reasonable performance accuracy compared to the hydraulic method. Storage constant used in Muskingum method widely applied in hydrological flood routing is very similar to the travel time. Focusing on this point, in this study, we estimate the travel time from HEC-RAS results to estimate storage constant, and develop a non-linear regression equation for the travel time using reach length, channel slope, and discharge. The estimated flow by Muskingum model with storage constant of nonlinear equation is compared with the flow calculated by applying the HEC-RAS 1-D unsteady flow simulation. In addition, this study examines the effect on the weighting factor changes and interval reach divisions; peak discharge increases with the bigger weighting factor, and RMSE decreases with the fragmented division.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.51 no.6
• /
• pp.221-227
• /
• 2014

In this paper, we propose a synthesis method that can effectively suppress the ambience which affects tonal components in the PS decoder. Ambience component was obtained by using decorrelation filter and the weighting of the ambience in the decoder was determined through IC parameter. However, since the parameters are extracted in the sub-band domain, a low IC value could be analyzed even if the tonal component is dominant. The quality of the output signal may be degraded. To prevent this problem, the tonality was measured in the downmixed signal and the weighting of the ambience components were adjusted appropriately according to the measured tonality index. The performance of the proposed method was evaluated by simulations. Furthermore, the subjective test was performed and the results confirmed that the proposed method offers improved quality.

• Atmosphere
• /
• v.24 no.1
• /
• pp.101-110
• /
• 2014

This study estimates and evaluates the daily January temperature from 2003 to 2012 with 30 m-resolution over South Korea, using a modified Parameter-elevation Regression on Independent Slopes Model (K-PRISM). Several factors in K-PRISM are also adjusted to 30 m grid spacing and daily time scales. The performance of K-PRISM is validated in terms of bias, root mean square error (RMSE), and correlation coefficient (Corr), and is then compared with that of inverse distance weighting (IDW) and hypsometric methods (HYPS). In estimating the temperature over Jeju island, K-PRISM has the lowest bias (-0.85) and RMSE (1.22), and the highest Corr (0.79) among the three methods. It captures the daily variation of observation, but tends to underestimate due to a high-discrepancy in mean altitudes between the observation stations and grid points of the 30 m topography. The temperature over South Korea derived from K-PRISM represents a detailed spatial pattern of the observed temperature, but generally tends to underestimate with a mean bias of -0.45. In bias terms, the estimation ability of K-PRISM differs between grid points, implying that care should be taken when dealing with poor skill area. The study results demonstrate that K-PRISM can reasonably estimate 30 m-resolution temperature over South Korea, and reflect topographically diverse signals with detailed structure features.

• Journal of Environmental Impact Assessment
• /
• v.26 no.3
• /
• pp.171-180
• /
• 2017

The vulnerability analysis of climate change driven disaster has been used as institutional framework for the urban policies of disaster prevention since 2012. However, some problems have occurred due to the structure of vulnerability analysis, such as overweighted variables and duplicated application of variables of similar meaning. The goal of this study is to examine the differences of results between the method of current guideline and the method of weight equalization. For this, we examines the current structural framework of the vulnerability analysis, and performs empirical analysis. As a result, the extent and magnitude of vulnerability showed different spatial patterns depending on the weighting methods. Standardized weighting method relatively represented wider vulnerable areas compared to the pre-existing method which follows the current instruction manual. To apply the results of vulnerability analysis to urban planning process for disaster prevention, this study suggests that the reliability of the results should be ensured by improving analytical framework and detailed review of the results.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.60 no.4
• /
• pp.49-54
• /
• 2018

With increasing satellite-based RS(Remotely Sensed) techniques, RS soil moisture footprints have been providing for various purposes at the spatio-temporal scales in hydrology, agriculture, etc. However, their coarse resolutions still limit the applicability of RS soil moisture to field regions. To overcome these drawbacks, the LDA(Landsat-based Downscaling Algorithm) was developed to downscale RS soil moisture footprints from the coarse- to finer-scales. LDA estimates Landsat-based soil moisture($30m{\times}30m$) values in a spatial domain, and then the weighting values based on the Landsat-based soil moisture estimates were derived at the finer-scale. Then, the coarse-scale RS soil moisture footprints can be downscaled based on the derived weighting values. The LW21(Little Washita) site in Oklahoma(USA) was selected to validate the LDA scheme. In-situ soil moisture data measured at the multiple sampling locations that can reprent the airborne sensing ESTAR(Electronically Scanned Thinned Array Radiometer, $800m{\times}800m$) scale were available at the LW21 site. LDA downscaled the ESTAR soil moisture products, and the downscaled values were validated with the in-situ measurements. The soil moisture values downscaled from ESTAR were identified well with the in-situ measurements, although uncertainties exist. Furthermore, the SMAP(Soil Moisture Active & Passive, $9km{\times}9km$) soil moisture products were downscaled by the LDA. Although the validation works have limitations at the SMAP scale, the downscaled soil moisture values can represent the land surface condition. Thus, the LDA scheme can downscale RS soil moisture products with easy application and be helpful for efficient water management plans in hydrology, agriculture, environment, etc. at field regions.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.21 no.7
• /
• pp.805-814
• /
• 2010

The Crank-Nicolson isotropic-dispersion finite difference time domain(CN ID-FDTD) scheme is proposed based on isotropic-dispersion finite difference(ID-FD) $equation^{[1],[2]}$. The dispersion relation of CN ID-FDTD is derived for lossy media by solving the eigenvalue problem of iteration matrix in spatial spectral domain, in addition, the weighting factors and scaling factors of the CN ID-FDTD scheme are presented for low dispersion error. The CN ID-FDTD scheme makes the dispersion error drastically reduced and shows accurate numerical results compared to the conventional Crank-Nicolson FDTD method.

• The Journal of the Acoustical Society of Korea
• /
• v.41 no.5
• /
• pp.525-533
• /
• 2022

We propose an effective method for suppressing both side and grating lobes by applying 2-dimensional Fourier Transform to the received channel data during the receive focusing process of an ultrasound imaging system. When the signal from the image point is focused, the channel signals have the same DC value across the channels. However, even after echoes from outside an imaging point are focused, they are manifested as having different spatial frequencies depending on their incident angles. Therefore, after the receive focusing delay time is applied, 2-D Fourier Transform is performed on the time-channel data to separate the DC component and other frequency components in the spectral domain, and the weighting value is defined using the ratio of the two values. The side lobe and grating lobe were suppressed by multiplying the ultrasound image by a weighting value. Ultrasound images with a frequency of 5 MHz were simulated in a 64-channel linear array. The grating lobe appearing in the ultrasound image was completely removed by applying the proposed method. In addition, the side lobe was reduced and the lateral resolution was greatly increased. Results of computer simulation on a human organ mimicking image show that the proposed method can aid in better lesion diagnosis by increasing the image contrast.

• Spatial Information Research
• /
• v.23 no.1
• /
• pp.41-48
• /
• 2015

BIM Technology contains data from the life cycle of facility through 3D modeling. For these, one building products the huge file because of massive data. One of them is IFC which is the standard format, and there are issues that large scale data processing based on geometry and property information of object. It increases the rendering speed and constitutes the graphic card, so large scale data is inefficient for screen visualization to user. The light weighting of large scale BIM data has to solve for process and quality of program essentially. This paper has been searched and confirmed about light weight techniques from domestic and abroad researches. To control and visualize the large scale BIM data effectively, we proposed and verified the technique which is able to optimize the BIM character. For operating the large scale data of facility on web based GIS platform, the quality of screen switch from user phase and the effective memory operation were secured.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
• /
• v.6 no.1
• /
• pp.1-12
• /
• 2001

Tidal computations of $M_2,\;S_2,\; K_1$ and $O_1$ constituents in the northeast Asian sea are presented by blending the Topex/Poseidon (T/P) altimeter data into a hydrodynamic model with $5'{\times}5'$ resolution. A series of sensitivity experiments on a weighting factor, which is the control parameter in the blending method, are carried out using $M_2$ constituent. The weighting factor is set to be in inverse proportion to the square root of water depth to reduce noises which could occur in data-assimilative model by blending T/P data. Model results obtained by blending the T/P-derived $M_2,\;S_2,\; K_1$ and $O_1$ constituents simultaneously are compared with all T/P-track tidal data; Average values of amplitude and phase errors are close to zero. Standard deviations of amplitude and phase errors are approximately 2 cm and less than 10 degrees respectively. The data-assimilative model results show a quite good agreement with T/P-derived tidal data, particularly in shallow water region (h<250m). In deep water regions, T/P-derived tidal data show unreasonable spatial variations in amplitude and phase. The data-assimilative model results differ from T/P-derived data, but are improved to show reasonable spatial variations in amplitude and phase. In addition, the T/P-blended model results are in good agreement with coastal tide gauge data which are not blended into the model.

• Journal of Korean Society of Forest Science
• /
• v.101 no.3
• /
• pp.374-380
• /
• 2012

The k-Nearest Neighbor (kNN) technique is popularly applied to assess forest resources at the county level and to provide its spatial information by combining large area forest inventory data and remote sensing data. In this study, two approaches such as distance-weighting and stratification of training dataset, were compared to improve kNN-based forest growing stock estimates. When compared with five distance weights (0 to 2 by 0.5), the accuracy of kNN-based estimates was very similar ranged ${\pm}0.6m^3/ha$ in mean deviation. The training dataset were stratified by horizontal reference area (HRA) and forest cover type, which were applied by separately and combined. Even though the accuracy of estimates by combining forest cover type and HRA- 100 km was slightly improved, that by forest cover type was more efficient with sufficient number of training data. The mean of forest growing stock based kNN with HRA-100 and stratification by forest cover type when k=7 were somewhat underestimated ($5m^3/ha$) compared to statistical yearbook of forestry at 2011.