• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2006.04a
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• pp.391-393
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• 2006

In this study, the performance of artificial neural network (ANN) models for estimating spatial distribution of water quality was evaluated using electric conductivity (EC) values in landfill site. For the ANN model development, feedforward neural networks and backpropagation algorithm with gradient descent method were used. In Test 1, the interpolation ability of the ANN model was evaluated. Results of the ANN model were more precise than those of the Kriging model. In Test 2, spatial distributions of EC values were predicted using precipitation data. Results seemed to be reasonable, however, they showed a limitation of ANN models in extrapolations.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.8
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• pp.60-67
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• 1996

In this paper, we propose a new temporal interpolation method based on spatial filtering. Compared with the conventional method, the proposed one may use a few adjacent frames and apply temporal lowpass filtering. To develop this method, we follow the basic approach of sampling rate conversion. Additionally, we use some assumption of video sequence : moving object has constant velocity rigid translational motion. From them, spatial filtering for temporal sampling rate conversion is described. This method has a lot of noise immunity on a motion vector and doesn't make a great difference from the original frame. The interpolated frame shows moderate change even there is a great time difference. This method has exactly same description of motion adaptive spatial filter which has an efficient temporal band-limiting characteristics. It imposes the possibility to make video sequence with good pictural quality.

• Coupled systems mechanics
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• v.8 no.6
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• pp.523-535
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• 2019

Artificial Intelligence (AI) is anticipated to be the future of technology. Hence, AI has been applied in various fields over the years and its applications are expected to grow in number with the passage of time. There has been a growing need for accurate, direct, and quick prediction of geotechnical and foundation engineering models especially since the success of each project relies on numerous amounts of data. In this study, two applications of AI in the field of geotechnical and foundation engineering are presented - spatial interpolation of standard penetration test (SPT) data and prediction of consolidation of clay. SPT and soil profile data may be predicted and estimated at any location and depth at a site that has no available borehole test data using artificial intelligence techniques such as artificial neural networks (ANN) based on available geospatial information from nearby boreholes. ANN can also be used to accelerate the calculation of various theoretical methods such as the one-dimensional consolidation theory of clay with high efficiency by using lesser computation resources. The results of the study showed that ANN can be a valuable, powerful, and practical tool in providing various information that is needed in geotechnical and foundation design.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.270-270
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• 2011

본 연구는 유역강우량을 산출을 위한 공간보간기법이 격자형 강우자료 생성에 미치는 영향에 대하여 분석하고자 하였다. 본 연구의 대상지역은 우리나라에서 규모가 가장 큰 유역인 한강유역(26,018km2)을 선정하였다. 유역강우량 산출에 이용한 강우자료는 기상청에서 제공하는 2000~2010 년까지 11년간 AWS(Automatic Weather Station) 108개소의 관측자료를 제공받아 사용하였으며, 강우이벤트로 2004년~2009년까지 재산피해를 입힌 총 11개의 호우, 태풍 사상을 선정하였다. 공간 보간기법으로는 Thiessen법과 IDW(Inverse Distance Weight)법의 2가지 기법을 선정하였다. 대상 지역에 대하여 AWS의 자료를 기반으로 보간을 실시하여 미관측지역에 대한 격자분포자료를 구축하였다. 이때, 격자분포자료는 국토해양부에서 분류한 19개 중권역을 기준으로 각 권역별 평균 강우량을 산출하였다. 2가지 공간보간기법을 이용한 한강유역전체 강우량 산출 결과 고도를 고려한 공간보간의 경우 그렇지 않은 경우에 비해 한강유역의 유역평균강우량은 IDW법은 -1.81~8.1%, Thiessen법은 6.6~9.6%의 차이를 나타내었으며, 연도별 편차가 증가하고 있었다.

• Korean Journal of Agricultural and Forest Meteorology
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• v.6 no.3
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• pp.164-169
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• 2004

A spatial interpolation scheme incorporating local geographic potential for cold air accumulation (TOPSIM) was used to test the feasibility of operational frost warning in Chatancheon basin in Yeoncheon County, where the introduction of new crops including temperate zone fruits is planned. Air temperature from April to June 2003 was measured at one-minute intervals at four locations within the basin. Cold-air accumulation potentials (CAP) at 4 sites were calculated for 3 different catchment scales: a rectangular area of 65 x 55 km which covers the whole county, the KOWACO (Korea Water Corporation) hydrologic unit which includes all 4 sites, and the sub-basins delineated by a stream network analysis of the digital elevation model. Daily minimum temperatures at 4 sites were calculated by interpolating the perfect prognosis (i.e., synoptic observations at KMA Dongducheon station) based on TOPSIM with 3 different CAPs. Mean error, mean absolute error, and root mean square error were calculated for 45 days with no precipitation to test the model performance. For the 3 flat locations, little difference was detected in model performance among 3 catchment areas, but the best performance was found with the CAPs calculated for sub-basins at one site (Oksan) on complex terrain. When TOPSIM loaded with sub-basin CAPs was applied to Oksan to predict frost events during the fruit flowering period in 2004, the goodness of fit was sufficient for making an operational frost warning system for mountainous areas.

• Journal of Industrial Technology
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• v.14
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• pp.127-140
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• 1994

This study is concerned with the accuracy and the patterns when different methods was used in interpolation task. Although 3 methods employed the same modality for input (visual) and for output (manual responding), they differed in central processing, which method 1 is relatively more tendency of verbal processing, method 2 is realtively more tendency of spatial processing and method 3 needed a number of switching code (verbal/spatial) performing task. Split-plot design was adopted, which whole plot consisted of methods (3), orientations (horizon, vertical), base-line sizes (300, 500, 700 pixels) and split plot consisted of target locations (1-99). The results showed the anchor effect and the range effect. Method 2, method 3 and method 1 that order was better accuracy. ANOVA showed that the accuracy was significantly influenced by the method, the location of target, and its interactions ($method{\times}location$, $size{\times}location$). Analysis of error data, response time and frequency of under, just, over estimate indicated that a systematic error pattern was made in task and methods changed not only the performance but also the pattern. The results provided support for the importance of the multiple resources theory in accounting for S-C-R compatibility and task performance. They are discussed in terms of multiple resources theory and guidelines for system design is suggested by the S-C-R compatibility.

• Journal of the Korean earth science society
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• v.42 no.4
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• pp.401-411
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• 2021

This study provides comprehensive assessment results for the most recent high-resolution regional climatology in the East/Japan Sea by comparing with the various existing climatologies. This new high-resolution climatology is generated based on the Optimal Interpolation (OI) method with individual profiles from the World Ocean Database and gridded World Ocean Atlas provided by the National Centers for Environmental Information (NCEI). It was generated from the recent previous study which had a primary focus to solve the abnormal horizontal gradient problem appearing in the other high-resolution climatology version of NCEI. This study showed that this new OI field simulates well the meso-scale features including closed-curve temperature spatial distribution associated with eddy formation. Quantitative spatial variability was compared to the other four different climatologies and significant variability at 160 km was presented through a wavelet spectrum analysis. In addition, the general improvement of the new OI field except for warm bias in the coastal area was confirmed from the comparison with serial observation data provided by the National Fisheries Research and Development Institute's Korean Oceanic Data Center.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.7
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• pp.1383-1388
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• 2016

Although image signal processing is used in many fields, degradation takes place in the process of transmitting image data by several causes. CWMF, A-TMF, and AWMF are the typical methods to eliminate noises from image data damaged under salt and pepper noise environment. However, those filters are not effective for noise rejection under highly dense noise environment. In this respect, the present study proposed an algorithm to remove in salt and pepper noise. In case the center pixel is determined to be non-noise, it is replaced with original pixel. In case the center pixel is noise, it segments local mask into 4 directions and uses linear interpolation to estimate original pixel. And then it applies spatial weight to the estimated pixel. The proposed algorithm shows a high PSNR of 24.56[dB] for House images that had been damaged of salt and pepper noise(P = 50%), compared to the existing CWMF, A-TMF and AWMF there were improvements by 16.46[dB], 12.28[dB], and 12.32[dB], respectively.

• Journal of Environmental Impact Assessment
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• v.27 no.5
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• pp.447-474
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• 2018

The purpose of this study is to build a new dataset of spatially interpolated climate data of South Korea by performing various geo-statistical interpolation techniques for comparison with the LDAPS grid data of KMA. Among 595 observation data in 2017, 80 % of the total points and remaining 117 points were used for spatial mapping and quantification,respectively. IDW, cokriging, and kriging were performed via the ArcGIS10.3.1 software and Python3.6.4, and each result was then divided into three clusters and four watersheds for statistical verification. As a result, cokriging produced the most suitable grid climate data for instantaneous temperature. For 1-hr accumulated precipitation, IDW was most suitable for expressing local rainfall effects.

• Spatial Information Research
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• v.18 no.4
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• pp.33-41
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• 2010

Approximately 100 permanent GPS stations are currently operational in Korea. However, only 10 sites have their own weather sensors connected directly to the GPS receiver. Thus. calculation of meteorological data through interpolation of AWS data are needed to determine precipitable water vapors at a specific GPS station without a meteorological sensor. This study analyzed the accuracy of two meteorological data interpolation methods called reverse sea level correction and kriging. As a result, the root-mean square-error of reverse sea level correction were seven times more accurate in pressure and twice more accurate in temperature than the kriging method. For the analysis of PWV accuracy, we calculated GPS PWV during the summer season in :2008 by using GPS observation data and interpolated meteorological data by reverse sea level correction. And, we compared GPS PWV s based on interpolated meteorological data with those from radiosonde observations and GPS PWV s based on onsite GPS meteorological sensor measurements. As a result, the accuracy of GPS PWV s from our interpolated meteorological data was within the required operational accuracy of 3mm.