• Journal of the Economic Geographical Society of Korea
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• v.15 no.3
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• pp.437-455
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• 2012

Korea has recently constructed a number of renewable photovoltaic power plants in Jeolla province as an effort to provide environment-friendly energy. However, several problems appeared in the power plant locations because they were not appropriately chosen ignoring social-environmental perspectives. Consequently, locations of both currently existing photovoltaic power plants require an social and environmental evaluations. This study aims to provide appropriate photovoltaic power plants locations and evaluation of current photovoltaic power plants in Jeolla province. By presenting location analysis of photovoltaic power plants, this study would minimize environmental and social side effects regarding photovoltaic power plants. Kriging and Analytic Network Process (ANP) are applied as methodology. ANP generates correct weights in combining spatial data, so that the result would present optimal locations. In addition environmentally sensitive regions were excluded in the analysis process. The results show that South and West coastal areas have a number of appropriate locations for photovoltaic power plants. In addition, evaluating currently running photovoltaic power plant locations, total 23 out 81 are turned out to be inappropriately located. This study is expected to contribute avoiding social and environmental conflicts in photovoltaic power plant locations and present criteria in evaluating photovoltaic power plants.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.3D
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• pp.407-415
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• 2008

This study presents the methodology to link with aerial photos for advancing the accuracy of topographic survey data that is used to calculate water volume in urban stream. First, GIS spatial interpolation technique as Inverse Distance Weight (IDW) and Kriging was applied to construct the terrain morphology to the sand-bar and grass area using cross-sectional survey data, and also validation point data was used to estimate the accuracy of created topographic data. As the result of comparison, IDW ($d^{-2}_{ij}$, 2nd square number) in Sand-bar area and Kriging Spherical model in grass area showed more efficient results in the construction of topographic data of river boundary. But the differences among interpolation methods are very slight. Image classification method, Minimum Distance Method (MDM) was applied to extract sand-bar and grass area that are located to river boundary efficiently and the elevation value of extracted layers was allocated to the water level point value. Water volume with topographic data from aerial photos shows the advanced accuracy of 13% (in sand-bar) and 12% (in grass) compared to the water volume of original terrain data. Therefore, terrain analysis method in river linking with aerial photos is efficient to the monitoring about sand-bar and grass area that are located in the downstream of Dam in flooding season, and also it can be applied to calculate water volume efficiently.

• Korean Journal of Soil Science and Fertilizer
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• v.43 no.6
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• pp.968-974
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• 2010

We assessed the feasibility of discrete wavelet transform (DWT) applied for the spectral processing to enhance the estimation performance quality of soil organic matters using visible-near infrared spectra and mapped their distribution via block Kriging model. Continuum-removal and $1^{st}$ derivative transform as well as Haar and Daubechies DWT were used to enhance spectral variation in terms of soil organic matter contents and those spectra were put into the PLSR (Partial Least Squares Regression) model. Estimation results using raw reflectance and transformed spectra showed similar quality with $R^2$ > 0.6 and RPD> 1.5. These values mean the approximation prediction on soil organic matter contents. The poor performance of estimation using DWT spectra might be caused by coarser approximation of DWT which not enough to express spectral variation based on soil organic matter contents. The distribution maps of soil organic matter were drawn via a spatial information model, Kriging. Organic contents of soil samples made Gaussian distribution centered at around 20 g $kg^{-1}$ and the values in the map were distributed with similar patterns. The estimated organic matter contents had similar distribution to the measured values even though some parts of estimated value map showed slightly higher. If the estimation quality is improved more, estimation model and mapping using spectroscopy may be applied in global soil mapping, soil classification, and remote sensing data analysis as a rapid and cost-effective method.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.141-141
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• 2016

미계측 지역에서의 토양수분을 예측하기 위하여 조건부합성방법을 한반도에 적용하여 비교 분석하였다. 토양수분 자료는 농촌진흥청에서 제공하는 지상관측 자료와 GCOM-W1 위성의 Advanced Microwave Scanning Radiometer2 (AMSR2) 센서의 자료를 사용하였다. 위성관측 토양수분자료의 오차를 제거하기 위하여 지상관측자료에 정규화 하였고, 정규화된 위성관측 자료와 지상관측자료를 조건부합성 방법을 이용하여 합성하였다. 조건부 합성방법의 성능을 평가하기 위하여 leave-one-out 교차검증 방법을 사용하였고, 분석 결과 지상관측자료에 위성자료를 합성한 조건부합성방법이 지상관측자료만을 사용한 크리깅 방법에 비해 우세하게 나타났다. 또한 각 관측지점에서의 조건부합성 방법을 이용한 토양수분 예측 성능을 공간분포 시켜 지역적인 특성을 분석한 결과 관측소의 밀도와 지형적인 특성이 조건부합성방법의 성능에 영향을 미치는 것으로 나타났다. 본 연구의 결과는 원격탐사기법으로 관측된 토양수분 자료의 공간적인 특성을 고려하여 지상 관측 자료와 합성하는 것이 토양수분 공간보간성능을 향상 시킬 수 있다는 것을 의미한다.

• Korean Journal of Remote Sensing
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• v.28 no.1
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• pp.129-143
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• 2012

This paper demonstrates the effectiveness of advanced spatial modeling techniques for environmental monitoring and impact assessment through a case study of Chernobyl nuclear accident occurred in 1986. Land-cover types changed after the accident are analysed by a post classification comparison method using bi-temporal Landsat TM data acquired in 1986 and 1992 near the accident site. Spatial modeling including various kriging algorithms are also applied to analyze the relationships between Cesium concentrations in soil and thyroid cancer incidence rates in Belarus, which was greatly damaged by the accident. The change detection results clearly showed the decrease of croplands and the increase of abandoned lands, and concrete structures were newly built around the nuclear plant to prevent the spread of radioactive contamination. In Belarus, high Cesium concentrations were observed in southern areas with high thyroid cancer risk estimated by Poisson kriging. Geographically weighted regression, which could account for geographic variations of independent variables including Cesium concentrations and distances from the Chernobyl nuclear power plant, was applied to extract the relationships between the independent variables and the thyroid cancer risk. The estimated risk values showed a correlation coefficient value of 0.98 with respect to the thyroid cancer risk values, which implied that the thyroid cancer risk in Belarus was affected by the accident. In conclusion, it is expected that advanced spatial modeling techniques applied in this study would be useful for environmental impact assessment and public health research.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.10
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• pp.393-405
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• 2020

Various geotechnical information is required to evaluate the stability of the ground and a foundation once liquefaction occurs due to earthquakes, such as the soil strength and groundwater level. The results of the Standard Penetration Test (SPT) conducted in Korea are registered in the National Geotechnical Information Portal System. If geotechnical information for a non-drilled area is needed, geostatistics can be applied. This paper is about the feasibility of obtaining ground information by the Empirical Bayesian Kriging (EBK) method and the Inverse Distance Weighting Method (IDWM). Esri's ArcGIS Pro program was used to estimate these techniques. The soil strength parameter of the drilling area and the level of groundwater obtained from the standard penetration test were cross-validated with the results of the analysis technique. In addition, Multichannel Analysis of Surface Waves (MASW) was conducted to verify the techniques used in the analysis. The Buk-gu area of Pohang was divided into 1.0 km×1.0 km and 110 zones. The cross-validation for the SPT N value and groundwater level through EBK and IDWM showed that both techniques were suitable. MASW presented an approximate section area, making it difficult to clearly grasp the distribution pattern and groundwater level of the SPT N value.

• Economic and Environmental Geology
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• v.55 no.4
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• pp.353-366
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• 2022

Spatial estimation of geoscience data (geo-data) is challenging due to spatial heterogeneity, data scarcity, and high dimensionality. A novel spatial estimation method is needed to consider the characteristics of geo-data. In this study, we proposed the application of Gaussian Mixture Model (GMM) among machine learning algorithms with multivariate data for robust spatial predictions. The performance of the proposed approach was tested through soil chemical concentration data from a former smelting area. The concentrations of As and Pb determined by ex-situ ICP-AES were the primary variables to be interpolated, while the other metal concentrations by ICP-AES and all data determined by in-situ portable X-ray fluorescence (PXRF) were used as auxiliary variables in GMM and ordinary cokriging (OCK). Among the multidimensional auxiliary variables, important variables were selected using a variable selection method based on the random forest. The results of GMM with important multivariate auxiliary data decreased the root mean-squared error (RMSE) down to 0.11 for As and 0.33 for Pb and increased the correlations (r) up to 0.31 for As and 0.46 for Pb compared to those from ordinary kriging and OCK using univariate or bivariate data. The use of GMM improved the performance of spatial interpretation of anthropogenic metals in soil. The multivariate spatial approach can be applied to understand complex and heterogeneous geological and geochemical features.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.18 no.4
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• pp.67-72
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• 2010

In this study, performance analysis and design optimization is carried out for a multi-rate spring brake system, which is used in a cable ride to stop the arriving passengers in safe and comfortable manner. Mathematical model for the spring is developed toward the objective of minimizing the impact at the arrival while satisfying the constraint of limited distance at the stop. Matlab code is utilized to examine parameters affecting the performance of the brake system. The results are validated by a commercial software RecurDyn. Kriging meta model is used to reduce the computational cost of the analysis. Optimization is conducted by RecurDyn, from which the design parameters are determined that minimizes the impact at the stop.

• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.788-789
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• 2015

본 논문에서는 사이클로트론 전자석의 설계과정을 체계화하고, 자기장 최적화 과정을 순차적 근사화 기법을 이용하여 설계를 진행하였다. 설계하는 전자석은 방사성동위원소생산을 목적으로하는 PET(Positron Emission Tomography) 사이클로트론 이며, 크기를 줄이고 동위원소의 효율적인 생산을 위해 에너지대역은 10MeV로 선정하였다. 설계과정은 실험계획법 중 하나인 LHS(Latin Hypercube Sampling) 기법을 통해 샘플 데이터를 구성하고, 이를 바탕으로 크리깅을 이용해 근사모델을 구성한다. 근사 모델과 진화 알고리즘을 이용해 목적에 맞는 최적의 형상을 찾을 수 있다. 이러한 과정을 반복함으로써 점진적으로 목적에 부합하는 형상을 찾을 수 있다. 각각의 형상의 성능을 판단하는 목적함수를 단계별로 규칙을 정함으로써 결과의 신뢰도를 높인다. 이로써 시간적 효율을 증대시키고 전문지식이 부족한 설계자도 고성능의 형상을 얻을 수 있다. 최적화과정은 STEP1과 STEP2로 나누어 진행되며, STEP1에서는 초기사이클로트론 전자석을 설계하고, 자기장 최적화를 진행한다. STEP2에서는 빔 시뮬레이션 및 분석을 통하여 최적화를 진행하고, 최종적으로 전자석모델을 완성한다.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.25 no.12
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• pp.654-659
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• 2013

This paper presents a numerical optimization of louvered fins to enhance the JF factor in terms of the design parameters, including the fin pitch, the number of louvers, the louver angle, the fin thickness, and the re-direction louver length. We carried out a parametric study to select the three most important parameters affecting the JF factor, which were the fin pitch, number of louvers, and the louver angle. We optimally designed the louvered fin by using 3rd-order full factorial design, the kriging method, and a micro genetic algorithm. Consequently, the JF factor of the optimum model increased by 16% compared to that of the base model. Moreover, the optimum model reduced the pressure drop by 17% with a comparable heat transfer rate.