• Journal of the Korean association of regional geographers
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• v.10 no.2
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• pp.389-406
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• 2004

with the increasing popularity of regional studies, the importance of regional data has been recognized dramatically in recent years. However, due to potential problems from the intrinsic characteristics of aggregate regional data for the research, and incompatible regional units between source and target regional data units, the method for reorganizing the regional data units for a given research analysis should be required. In this regard, the purpose of this research is to review the significant interpolation methods for reorganizing the data units and, based on it, to propose the population weighted interpolation method. For the first purpose, areal weighted interpolation method, pycnophylactic method, dasymetric method, area-to-point method were reviewed. The proposed population-weighted interpolation method was applied to the case study of population census regional data in Erie County, NY, compared with areal weighted interpolation method, pycnophylactic method in terms of several statistical characteristics.

• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.3
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• pp.125-140
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• 2017

Until recently, regression based spatial interpolation methods and Kriging based spatial interpolation methods have been largely used to estimate land price or housing price, but less attention has been paid on comparing the performance of these spatial interpolation methods. In this regard, this research applied regression based spatial interpolators and Kriging based spatial interpolators for estimating the land prices in Dalseo-gu, Daegu metropolitan city and evaluated the accuracy of eight spatial interpolators. OLS, SLM, SEM, and GWR were used as regression based spatial interpolators while SK, OK, UK, and CK were employed as Kriging based spatial interpolators. The global accuracy was statistically evaluated by RMSE, adjusted RMSE, and COD. The relative accuracy was visually compared by three-dimensional residual error map and scatterplot. Results from statistical and visual analyses indicate that GWR reflecting the spatial non-stationarity was a relatively more accurate spatial predictor to estimate land prices in the study area than SAR and Kriging based spatial interpolators considering the spatial dependence. The findings from this research will contribute to the secondary research into analyzing the urban spatial structure with land prices.

• Journal of Korean Society for Geospatial Information Science
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• v.14 no.4 s.38
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• pp.27-36
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• 2006

Conventionally, in order to get accurate geolocation of satellite images we need a set of ground control points with respect to individual scenes. In this paper, we tested the possibilities of modeling satellite orbits from individual scenes by establishing a sensor model for one scene and by applying the model, which was derived from the same orbital segment, to other scenes that has been acquired from the same orbital segment. We investigated orbit-attitude models with several interpolation methods and with various parameter sets to be adjusted. We used 7 satellite images of SPOT-3 with a length of 420km and ground control points acquired from GPS surveying. Results of the conventional individual scene modeling hardly introduced differences among different interpolation methods and different adjustment parameter sets. As the results of orbit modeling, the best model was the one with Lagrange interpolation for position/velocity and linear interpolation for attitude and with position/angle bias as parameter sets. The best model showed that it is possible to model orbital segments of 420km with ground control points measured within one scene (60km).

• International Journal of Highway Engineering
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• v.9 no.3
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• pp.21-28
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• 2007

We suggest a new spatial linear interpolation method to substitute linear interpolation method which widely used in transportation engineering to impute the missing daily traffic volume. We layout daily traffic volume which is time series data over the virtual lattice space to consider the spatial correlation. We used Moran Index to evaluate the spatial correlations among daily traffic volume in same week and same date traffic volume by week considering the circularity of daily traffic volume. For real application, we used daily traffic volume on November, 2004 provided by Korea Institute of Construction Technology(KICT) and transformed daily traffic volume to 4 times 7 virtual lattice space to reflect the spatial correlation. Finally we showed that the spatial linear interpolation method has good performance for missing data imputation based on MAPE, RMSE, and Theil's U criteria.

• Journal of Korea Water Resources Association
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• v.43 no.12
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• pp.1083-1091
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• 2010

Distributed hydrologic models typically require spatial estimates of precipitation interpolated from sparsely located observational points to the specific grid points. However, widely used estimation schemes fail to describe the realistic variability of daily precipitation field. We compare and contrast the performance of statistical methods for the spatial estimation of precipitation in two hydrologically different basins, and propose a two-step process for effective daily precipitation estimation. The methods assessed are: (1) Inverse Distance Weighted Average (IDW); (2) Multiple Linear Regression (MLR); (3) Climatological MLR; and (4) Locally Weighted Polynomial Regression (LWP). In the suggested simple two-step estimation process, precipitation occurrence is first generated via a logistic regression model before applying IDW scheme (one of the local scheme) to estimate the amount of precipitation separately on wet days. As the results, the suggested method shows the better performance of daily rainfall interpolation which has spatial differences compared with conventional methods. And this technique can be used for streamflow forecasting and downscaling of atmospheric circulation model effectively.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.26 no.3
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• pp.282-287
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• 1990

In this paper, it has been analysed that the stability and the effectivity of the solution using traditional transfer matrix method. And applying the false-position method to these, the convergence characteristics of the solution has been also analysed. As a result, the frontal transfer matrix method is superior to traditional transfer matrix method in the stability and the accuracy of the solution in high frequency region but in the economical efficiency and the effectivity of the calculation, traditional transfer matrix method is more desiable. Also, it is clear that $\omega-Det$ curve using the frontal transfer matrix method is discontinuous.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.1980-1984
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• 2006

융설 모형을 이용하여 융설 기간 동안의 하천유출량을 모의하기 위해서는 융설 관련 매개변수의 정립이 반드시 필요하다. 우리나라의 경우 관측 자료의 부족으로 인하여 적설분포, 적설심, 적설면적감소곡선과 같은 융설 관련 매개변수의 추출이 불가능 하였다. 본 연구에서는 1997년부터 2003년까지의 겨울철(11월-4월) NOAA/AVHRR 위성영상을 이용하여 한반도의 적설분포도를 추출하고 기상청의 69개소 유인지상기상관측소의 기상자료 중 최심적설심 자료로서 공간내삽법을 통하여 동일한 기간의 최심적설심 분포도를 작성한 후 적설분포도와 중첩하여 남한의 적설심 분포도를 추출하였다. 또한, 적설면적감소곡선은 소양강댐과 충주댐 유역으로 대상으로 평균기온과 적설면적과의 상관관계로부터 각 연도별 선형회귀식을 추출하여 적설면적감소곡선을 작성하였다.

• Proceedings of the KIEE Conference
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• 2006.07a
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• pp.14-15
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• 2006

A saturation of magnetic flux in the core may occur when a large primary current flows when the iron-cored current transformer is used. This saturation makes the distorted secondary current of the CT. the distorted secondary current may cause the mal-operation or operation time delay of protective relays. CT compensation algorithm using The LSQ(Least Square) fitting method has a problem. It needs to acquire enough data for executing this algorithm without an error. In this paper, an enhanced algorithm using interpolation based LSQ(Least Square) Fitting Method is proposed. The Lagrange Interpolation Method is used for the interpolation and CT is simulated by EMTP. The results show that the proposed algorithm can accurately compensate a distorted secondary current more than existing Algorithm when the saturation severely occurs.

• Proceedings of the KSRS Conference
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• 2006.03a
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• pp.31-35
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• 2006

융설 모형을 이용하여 융설 기간 동안의 하천유출량을 모의하기 위해서는 융설 관련 매개변수의 정립이 반드시 필요하다. 우리나라의 경우 관측 자료의 부족으로 인하여 적설분포, 적설심, 적설면적감소곡선과 같은 융설 관련 매개변수의 추출이 불가능 하였다. 본 연구에서는 1997년부터 2003년까지의 겨울철(11월-4월) NOAA/AVHRR 위성영상을 이용하여 한반도의 적설분포도를 추출하고 기상청의 69개소 유인지상기상관측소의 기상자료 중 최심적설심 자료로서 공간내삽법을 통하여 동일한 기간의 최심적설심 분포도를 작성한 후 적설분포도와 중첩하여 남한의 적설심 분포도를 추출하였다. 또한, 적설면적감소곡선은 소양강댐과 충주댐 유역으로 대상으로 평균기온과 적설면적과의 상관관계로부터 각 연도별 선형회귀식을 추출하여 적설면적감소곡선을 작성하였다.

• Proceedings of the KSRS Conference
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• 2007.03a
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• pp.301-304
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• 2007

본 연구에서는 폐탄광 지역에서 발생하는 지반침하에 영향을 주는 주요 요인들을 추출하기 위하여 다변량 통계분석 방법의 하나인 주성분분석(Principle Component Analysis : PCA)기법과 지리정보시스템 (Geographic Information System : GIS)을 이용하였다. 이를 위해 연구지역에서 수행한 지표지질조사， 정밀조사, 실내암석시험 등으로부터 취득된 자료를 데이터베이스로 구축하고, 지반침하 위험지역 분포를 공간적으로 해석할 수 있는 지질, 토지이용, 경사도， 지표로부터 지하 갱도까지의 심도, 갱도의 지표상 위치로부터의 수평거리, 지하수심도, 투수계수, RMR(Rock Mass Rating) 값을 분석대상으로 선정하였다. 각 요인들이 연구지역 전체에 걸쳐 분포하도록 GIS의 공간분석 기법의 하나인 표면분석(Surface Analysis), 버퍼링기법(Buffering) 및 내삽법(Interpolation)을 이용하여 래스터 데이터베이스로 구축하고 이로부터 추출된 자료들을 입력값으로 하는 주성분분석을 수행하였다. 주성분분석 결과 폐탄광 지역의 지반침하에 영향을 주는 주요인을 추출하는 것이 가능하였으며, 연구지역은 지질 및 지반강도 관련 요인이 침하발생의 가장 큰 요인인 것으로 분석되었다.