• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.5
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• pp.1443-1454
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• 2014

In this study, we assess impact of spatial resolution of radar rainfall and a distributed hydrologic model on parameter estimation and rainfall-runoff response. Radar data measured by S-band polarimetric radar located at Mt. Bisl in the year of 2012 are used for the comparative study. As different rainfall estimates such as R-KDP, R-Z, and R-ZDR show good agreement with ground rainfall, R-KDP are applied for rainfall-runoff modeling due to relatively high accuracy in terms of catchment averaged and gauging point rainfall. GRM (grid based rainfall-runoff model) is implemented for flood simulations at the Geumho River catchment with spatial resolutions of 200m, 500m, and 1000m. Automatic calibration is performed by PEST (model independent parameter estimation tool) to find suitable parameters for each spatial resolution. For 200m resolution, multipliers of overlandflow and soil hydraulic conductivity are estimated within stable ranges, while high variations are found from results for 500m and 1000m resolution. No tendency is found in the estimated initial soil moisture. When parameters estimated for different spatial resolution are applied for other resolutions, 200m resolution model shows higher sensitivity compared to 1000m resolution model.

• Journal of Climate Change Research
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• v.5 no.4
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• pp.323-329
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• 2014

Since the terrain of Korea is complex, micro- as well as meso-climate variability is extreme by locations in Korea. In particular, air temperature of agricultural fields is influenced by topographic features of the surroundings making accurate interpolation of regional meteorological data from point-measured data. This study was carried out to compare spatial interpolation methods to estimate air temperature in agricultural fields surrounded by rugged terrains in South Korea. Four spatial interpolation methods including Inverse Distance Weighting (IDW), Spline, Ordinary Kriging (with the temperature lapse rate) and Cokriging were tested to estimate monthly air temperature of unobserved stations. Monthly measured data sets (minimum and maximum air temperature) from 588 automatic weather system(AWS) locations in South Korea were used to generate the gridded air temperature surface. As the result, temperature lapse rate improved accuracy of all of interpolation methods, especially, spline showed the lowest RMSE of spatial interpolation methods in both maximum and minimum air temperature estimation.

• Korean Journal of Remote Sensing
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• v.35 no.4
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• pp.503-516
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• 2019

We have estimated the vertical column density (VCD) of formaldehyde (HCHO) on a global scale using a multiple linear regression method (MRM) with Ozone Monitoring Instrument (OMI) and Moderate-Resolution Imaging Spectroradiometer (MODIS) data. HCHO VCDs were estimated in regions of biogenic, pyrogenic, and anthropogenic emissions using independent variables, including $NO_2$ VCD, land surface temperature (LST), an enhanced vegetation index (EVI), and the mean fire radiative power (MFRP), which are strongly correlated with HCHO. To evaluate the HCHO estimates obtained using the MRM, we compared estimates of HCHO VCD data measured by OMI ($HCHO_{OMI}$) with those estimated by multiple linear regression equations (MRE) ($HCHO_{MRE}$). Good MRM performances were found, having the average statistical values (R = 0.91, slope = 1.03, mean bias = $-0.12{\times}10^{15}molecules\;cm^{-2}$, percent difference = 11.27%) between $HCHO_{MRE}$ and $HCHO_{OMI}$ in our study regions where high HCHO levels are present. Our results demonstrate that the MRM can be a useful tool for estimating atmospheric HCHO levels.

• The Korean Journal of Applied Statistics
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• v.19 no.3
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• pp.421-430
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• 2006

In sample survey sample designs are performed by geographically-based domain such as countries, states and metropolitan areas. However mostly statistics of interests are smaller domain than sample designed domain. Then sample sizes are typically small or even zero within the domain of interest. Shin and Lee(2003) mentioned Spatial Autoregressive(SAR) model in small area estimation model-based method and show the effectiveness by MSE. In this study, Bayesian Auto-Poisson Model is applied in model-based small area estimation method and compare the results with SAR model using MSE ME and bias check diagnosis using regression line. In this paper Survey of Disability, Aging and Cares(SDAC) data are used for simulation studies.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.8 no.3
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• pp.224-228
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• 2015

In this paper, we study the method for desired signals estimation that array antennas are received signals. We apply sub spatial method of direction of arrival algorithm and adaptive array antennas in order to remove interference and noise signal of received antenna signals. Array response vector of adaptive array antenna is probability, it is correctly estimation of direction of arrival of targets to update weight signal. Desired signals are estimated updating covariance matrix after moving interference and noise signals among received signals. We estimate signals using eigen decomposition and eigen value, high resolution direction of arrival estimation algorithm is devided signal sub spatial and noise sub spatial. Though simulation, we analyze to compare proposed method with general method.

• Water Engineering Research
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• v.3 no.1
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• pp.31-44
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• 2002

The effect of diurnal cycle, intermittent visit of observation satellite, sensor installation, partial coverage of remote sensing, heterogeneity of soil properties and precipitation to the soil moisture estimation error were analyzed to present the global sampling strategy of soil moisture. Three models, the theoretical soil moisture model, WGR model proposed Waymire of at. (1984) to generate rainfall, and Turning Band Method to generate two dimensional soil porosity, active soil depth and loss coefficient field were used to construct sufficient two-dimensional soil moisture data based on different scenarios. The sampling error is dominated by sampling interval and design scheme. The effect of heterogeneity of soil properties and rainfall to sampling error is smaller than that of temporal gap and spatial gap. Selecting a small sampling interval can dramatically reduce the sampling error generated by other factors such as heterogeneity of rainfall, soil properties, topography, and climatic conditions. If the annual mean of coverage portion is about 90%, the effect of partial coverage to sampling error can be disregarded. The water retention capacity of fields is very important in the sampling error. The smaller the water retention capacity of the field (small soil porosity and thin active soil depth), the greater the sampling error. These results indicate that the sampling error is very sensitive to water retention capacity. Block random installation gets more accurate data than random installation of soil moisture gages. The Walnut Gulch soil moisture data show that the diurnal variation of soil moisture causes sampling error between 1 and 4 % in daily estimation.

• The Korean Journal of Applied Statistics
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• v.22 no.2
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• pp.403-414
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• 2009

Many researches have been devoted to the small area estimation related with the area level statistics. Almost all of the small area estimation methods are derived based on minimization of mean squared error(MSE). Recently Hwang and Shin (2008) suggested an alternative small area estimation method by minimizing mean squared percentage error. In this paper we apply this small area estimation method to the labor statistics, especially monthly wages by a branch area of labor department. The Monthly Labor Survey data (2007) is used for analysis and comparison of these methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.2
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• pp.372-379
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• 2015

The latest video compression standard (such as H.264/AVC and HEVC) utilizes quarter-pel accuracy motion estimation in order to retain detailed motion information. Many sub-pixel motion estimation algorithms used in the spatial domain usually encounters increment of computational complexity due to embedded interpolation algorithm. In this paper, an approach to measure sub-pixel accuracy motion estimation in frequency domain using shifting matrix is proposed. Complexity can be reduced utilizing shifting matrix algorithm in frequency domain and simulation results demonstrate not only higher PSNR but lower bit rates than spatial domain algorithms.

• Journal of the Korean Institute of Landscape Architecture
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• v.20 no.4
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• pp.26-38
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• 1993

The purpose of this study was to suggest objective basic data for landscape research which cotained interdiciplinary approach between ecological and psychophysical method. For this, the naturalness and preference in greenary space, spatial image structure of physical elements have been analyzed by correlation coefficient and factor analysis algorithm. The results are as follows; 1. The relation between the estimation of naturalness and the preference in natural forest was deeply correlated. And the estimation of naturalness was higher than the estimation of DGN(Degree of Green Naturality). 2. The estimation of naturalnesss was decided by the physical features of forest and was different from the DGN. 3. Factors covering the spatial image of the forests have been found to be the 'overall evaluation', 'ability', 'naturalness' and 'idiosyncracy'. By using the control method for the number of factors, T.V. has been obtained as 61.68%. 4. The factors of the 'overall evauation', 'naturalness' were found to be the main factors determining the visual preference of greenary space.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.82-86
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• 2004

A fuzzy rule-based hand-motion estimation algorithm is proposed for a 6 dimensional spatial tracker in which low cost accelerometers and gyros are employed. To be specific, beginning and stopping of hand motions needs to be accurately detected to initiate and terminate integration process to get position and pose of the hand from accelerometer and gyro signals, since errors due to noise and/or hand-shaking motions accumulated by integration processes. Fuzzy rules of yes or no of hand-motion-detection are here proposed for rules of accelerometer signals, and sum of derivatives of accelerometer and gyro signals. Several experimental results and shown to validate our proposed algorithms.