• The Korean Journal of Applied Statistics
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• v.5 no.2
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• pp.113-121
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• 1992

Statistical interpolation which uses past experience about the behaviour of the atmosphere(correlation function) to interpolate the observations irregularly distributed in space and time to regular grids is discussed. Correlation functions are computed in the Far East Asian region during the winter periods of December 1977 to February 1980. Results show from the computation of correlation functions that there exists a large difference in the autocorrelation functions by slowly decreasing geopotential height and temperature, and rapidly decreasing wind and mixing ratio with increasing data-correlation functions between geopotential height and wind are well corresponed to persistence of wintertime synoptic features.

• Geophysics and Geophysical Exploration
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• v.26 no.4
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• pp.185-198
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• 2023

In marine seismic surveys, the inevitable occurrence of trace gaps in the near offset resulting from geometrical differences between sources and receivers adversely affects subsequent seismic data processing and imaging. The absence of data in the near-offset region hinders accurate seismic imaging. Therefore, reconstructing the missing near-offset information is crucial for mitigating the influence of seismic multiples, particularly in the case of offshore surveys where the impact of multiple reflections is relatively more pronounced. Conventionally, various interpolation methods based on the Radon transform have been proposed to address the issue of the nearoffset data gap. However, these methods have several limitations, leading to the recent emergence of deep-learning (DL)-based approaches as alternatives. In this study, we conducted an in-depth analysis of two representative DL-based studies to scrutinize the challenges that future studies on near-offset interpolation must address. Furthermore, through field data experiments, we precisely analyze the limitations encountered when applying previous DL-based trace interpolation techniques to near-offset situations. Consequently, we suggest that near-offset data gaps must be approached by extrapolation rather than interpolation.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.229-229
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• 2019

본 연구에서는 현행 홍수예보에 활용되고 있는 지점 강우량의 면적강우량 산정 방법인 티센(Thiessen) 방법의 유역 평균 강우량 산정 시 발생하는 구조적 문제점을 검토하여 보았다. 현행지상 강수량계 기반의 면적평균강우량 산정 방법은 호우의 이동 방향에 따라 실제 강우량과 시차가 발생할 수 있는 구조적 문제점을 가지고 있다. 분석 결과 호우의 이동방향에 따른 강우의 시차발생이나 내삽 영역의 불확실성은 지점 강우량 관측의 한계로 티센방법 뿐만 아니라 지점 강우량을 사용하는 다른 내삽 방법에서도 정도의 차이는 있지만 유사하게 나타났다. 그러나 티센방법은 유역별 지점의 가중치(영향영역)가 고정되어 있기 때문에 이러한 현상이 심각하게 나타났다. 즉 현행 티센방법에 의한 지상 강우량의 면적평균 강우량 산정 방법은 시공간적으로 큰 바이어스를 초래가 가능하다. 크리깅 방법을 이용하면 시공간적 바이어스 감소하나 지점 관측의 한계를 완전하게 해소하는데는 미흡한 것으로 나타났다. 따라서 지점강우량 기반의 티센 유역평균 강수량 산정 체계에서 레이더 기반 유역평균 강우량 생산 활용 체계로 전환이 필요하다고 판단된다.

• Journal of the Korean Geographical Society
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• v.34 no.3
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• pp.319-336
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• 1999

본 연구는 우리나라의 수치지형도에서 수치고도모형(DEM)을 개발하고자 할 때 고려해야 할 요인들을 분석하였다. 특히 DEM의 정확도에 결정적으로 영향을 미치는 내삽법의 과정을 지형적 유형(평지.계곡.산지)과 공간적 표본추출법(체계적추출법.군집형무작위추출법.복합점진적표본추출법)에 따라 구분하여 살펴 보았다. RMSE의 측정을 통해 크리깅 내삽법이 지형의 기복에 산관없이 정확도를 유지함녀서 DEM을 생성할 수 있는 방법으로 평가되었다. 그리고 표본추출법에 따라 공간적 표본 밀도를 달리한 낮은 표본을 대상으로 한 경우에 비해 낮게 나타났다. 또한 본 연구에서 제안한 복합 점진적 표본추출법을 적용한 DEM의 정확도는 다른 표본추출법을 적용한 경우보다 그 정확도가 향상됨을 확인하였고, 반면에 계산상의 효율성이 다른 방법에 비해 떨어지는 단점을 보였다.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.6
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• pp.61-67
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• 2011

Stereoscopic 3D video can be transmitted by frame-compatible packing format to fulfill the compatibility requirement with the existing digital TV. Then, the reduced stereo image needs to be expanded to the original size at the receiver. This paper proposes an adaptive interpolation method for the discarded image lines. The horizontal line-based linear filter and NEDI6 filter are used selectively for the interpolation of each pixel. Experimental results show that the NEDI6 combined with the horizontal line-based linear filter yields better image quality than the bilinear method by around 0.6dB.

• Journal of Korea Water Resources Association
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• v.39 no.6 s.167
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• pp.495-502
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• 2006

The importance of the bandwidth selection has been more emphasized than the kernel function selection for nonparametric frequency analysis since the interpolation is more reliable than the extrapolation method. However, when the extrapolation method is being applied(i.e. recurrence interval more than the length of data or extreme probabilities such as $200{\sim}500$ years), the selection of the kernel function is as important as the selection of the bandwidth. So far, the existing kernel functions have difficulties for extreme value estimations because the values extrapolated by kernel functions are either too small or too big. This paper suggests a Modified Cauchy kernel function that is suitable for both interpolation and extrapolation as an improvement.

• Journal of the Korean Society of Propulsion Engineers
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• v.15 no.2
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• pp.29-35
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• 2011

The behaviors of combustion-induced internal flows of SRM equipped with fin-slot grain and submerged nozzle are very complex and diverse. Cold air-flow tests for 2D and 3D scale models of SRM have been done in order to specify the visualization method to analyze particular internal flow patterns such as roll-torque inducing flow. Swirl flow induced by asymmetric vortical tubes also has been visualized through employing various light source and recording directions.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2010.11a
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• pp.181-185
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• 2010

The behavior of combustion-induced internal flow of SRM equipped with fin-slot grain and submerged nozzle is very complex and diverse. Cold air-flow test for 2D and 3D scale models of SRM has been done in order to specify the visualization method to analyze particular internal flow patterns such as roll-torque inducing flow. Swirl flow induced by asymmetric vortical tube also has been visualized through employing various light source and recording directions.

• 한국해양학회지
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• v.29 no.3
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• pp.228-238
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• 1994

The change of sea-level is a good indicator of the change of climate during the Quaternary period. The sea-levels in the world have been changing very irregularly during that time. The pattern of the Quaternary sea-level change was assumed to be a stochastic fractal in this study. We measured fractal dimensions of the Holocene sea-levels of the Hudson river estuary and the Delaware coast. A box counting method gave almost the same values. i.e., D=1.358 for the Hudson sea-level changes and D+1.346 for the Delaware sea-level changes. the ability of the inverse method of fractal interposea-levels. IFIF reproduction the realistic sea-levels for the both of them. The delaware sea-level data made less statistical errors for the interpolation of IFIF than the Hudson and the Delaware sea-levels. IFIF reproduction the realistic sea-levels for the both of them. The Delaware sea-level data made less statistical errors for the interpolation of IFIF than the Hudson sea-level data. This suggests that the Delaware sea-level data are more reliable than the Hudson sea-level data was calculated from the fractal dimension of the Delaware sea-level data. Fractal interpolation functions (FIF) was used to reconstruct the peleosea-levels of the Korean coasts and the Atlantic Ocean coasts of the United States. The Korean Peleosea-level change generacted by FIF is different from the peleosea-level change of the eastern U.S.. The Korean peleosea-levels are much higher than the eastern U.S. Paleosea-levels, comparing to each other from the present to 8,000 BP.

• Korean Journal of Agricultural and Forest Meteorology
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• v.2 no.4
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• pp.175-182
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• 2000

Spatial interpolation of daily temperature forecasts and observations issued by public weather services is frequently required to make them applicable to agricultural activities and modeling tasks. In contrast to the long term averages like monthly normals, terrain effects are not considered in most spatial interpolations for short term temperatures. This may cause erroneous results in mountainous regions where the observation network hardly covers full features of the complicated terrain. We developed a spatial interpolation model for daily minimum temperature which combines inverse distance squared weighting and elevation difference correction. This model uses a time dependent function for 'mountain slope lapse rate', which can be derived from regression analyses of the station observations with respect to the geographical and topographical features of the surroundings including the station elevation. We applied this model to interpolation of daily minimum temperature over the mountainous Korean Peninsula using 63 standard weather station data. For the first step, a primitive temperature surface was interpolated by inverse distance squared weighting of the 63 point data. Next, a virtual elevation surface was reconstructed by spatially interpolating the 63 station elevation data and subtracted from the elevation surface of a digital elevation model with 1 km grid spacing to obtain the elevation difference at each grid cell. Final estimates of daily minimum temperature at all the grid cells were obtained by applying the calculated daily lapse rate to the elevation difference and adjusting the inverse distance weighted estimates. Independent, measured data sets from 267 automated weather station locations were used to calculate the estimation errors on 12 dates, randomly selected one for each month in 1999. Analysis of 3 terms of estimation errors (mean error, mean absolute error, and root mean squared error) indicates a substantial improvement over the inverse distance squared weighting.