• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2017.04a
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• pp.160-160
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• 2017

자동화 기술을 통한 한국형 스마트팜의 발전이 비약적으로 이루어지고 있는 가운데 무인화를 위한 지능적인 스마트 시설환경 관찰 및 분석에 대한 요구가 점점 증가 하고 있다. 스마트 시설환경에서 취득 가능한 시계열 데이터는 온도, 습도, 조도, CO2, 토양 수분, 환기량 등 다양하다. 시스템의 경계가 명확함에도 해당 속성의 특성상 타임도메인과 공간도메인 상에서 정확한 추정 또는 예측이 난해하다. 시설 환경에 접목이 증가하고 있는 지능형 관리 기술 구현을 위해선 시계열 공간 데이터에 대한 신속하고 정확한 정량화 기술이 필수적이라 할 수 있다. 이러한 기술적인 요구사항을 해결하고자 시도되는 다양한 방법 중에서 공간 분해능 향상을 위한 다지점 계측 메트릭스를 실험적으로 구성하였다. $50m{\times}100m$의 단면적인 연동 딸기 온실을 대상으로 $3{\times}3{\times}3$의 3차원 환경 인자 계측 매트릭스를 설치하였다. 1 Hz의 주기로 4가지 환경인자(온도, 습도, 조도, CO2)를 계측하였으며, 계측 하는 시점과 동시에 병렬적으로 공간통계법을 이용하여 미지의 지점에 대한 환경 인자들을 실시간으로 추정하였다. 선행적으로 50 cm 공간 분해능에 대응하기 위하여 Kriging interpolation법을 횡단면에 대하여 분석한 후 다시 종단면에 대하여 분석하였다. 3 Ghz에 해당하는 연산 능력을 보유한 컴퓨터에서 1초 동안 획득한 데이터에 대한 분석을 마치는데 소요되는 시간이 15초 내외로 나타났다. 이는 해당 알고리즘의 매우 높은 시간 복잡도(Order of $O=O^3$)에 기인하는 것으로 다양한 시설 환경의 관리 방법론에 적절히 대응하기에 한계가 있다 할 수 있다. 실시간으로 시간 복잡도가 높은 연산을 수행하기 위한 기술적인 과제를 해결하고자, 근래에 관심이 증가하고 있는 NVIDIA 사에서 제공하는 CUDA 엔진과 Apple사의 제안을 시작으로 하여 공개 소프트웨어 개발 컨소시엄인 크로노스 그룹에서 제공하는 OpenCL 엔진을 비교 분석하였다. CUDA 엔진은 GPU(Graphics Processing Unit)에서 정보 분석 프로그램의 연산 집약적인 부분만을 담당하여 신속한 결과를 산출할 수 있는 라이브러리이며 해당 하드웨어를 구비하였을 때 사용이 가능하다. 반면, OpenCL은 CUDA 엔진이 특정 하드웨어에서 구동이 되는 한계를 극복하고자 하드웨어에 비의존적인 라이브러리를 제공하는 것이 다르며 클러스터링 기술과 연계를 통해 낮은 하드웨어 성능으로 인한 단점을 극복하고자 하였다. 본 연구에서는 CUDA 8.0(https://developer.nvidia.com/cuda-downloads)버전과 Pascal Titan X(NVIDIA, CA, USA)를 사용한 방법과 OpenCL 1.2(https://www.khronos.org/opencl/)버전과 Samsung Exynos5422 칩을 장착한 ODROID-XU4(Hardkernel, AnYang, Korea)를 사용한 방법을 비교 분석하였다. 50 cm의 공간 분해능에 대응하기 위한 4차원 행렬($100{\times}200{\times}5{\times}4$)에 대하여 정수 지수화를 위한 Quantization을 거쳐 CUDA 엔진과 OpenCL 엔진을 적용한 비교한 결과, CUDA 엔진은 1초 내외, OpenCL 엔진의 경우 5초 내외의 연산 속도를 보였다. CUDA 엔진의 경우 비용측면에서 약 10배, 전력 소모 측면에서 20배 이상 소요되었다. 따라서 우선적으로 OpenCL 엔진 기반 하드웨어 가속 기술 최적화 연구를 통해 스마트 시설환경 실시간 시뮬레이션 기술 도입을 위한 기술적 과제를 풀어갈 것이다.

• Journal of the Korean Geotechnical Society
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• v.20 no.2
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• pp.131-141
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• 2004

For geotechnical applications, engineers use data obtained from a site investigation to interpret the structure and potential behavior of the subsurface. In most cases, these data consist of samples that represent 1/100,000 or less of the total volume of soil. These samples and associated field and lab testing provide the information used to estimate soil parameter values. The resulting values are estimated ones and there exists some likelihood that actual soil conditions are significantly different from the estimates. This may be the case even if the sampling and interpretation procedures are performed in accordance with standard practice. Although these efforts have been made to characterize the uncertainty associated with geotechnical parameters, there is no commonly accepted method to evaluate quantitatively the quality of an investigation plan as a whole or the relative significance of individual sampling points or potential sampling points.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.4
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• pp.1-18
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• 2022

Currently, the Korea Meteorological Administration evaluates the meteorological drought by region using SPI6(standardized precipitation index 6), which is a 6-month cumulative precipitation standard. However, SPI is an index calculated only in consideration of precipitation at 69 weather stations, and the drought phenomenon that appears for complex reasons cannot be accurately determined. Therefore, the purpose of this study is to calculate and compare SPI considering only precipitation and SDCI (Scaled Drought Condition Index) considering precipitation, vegetation index, and temperature in Gyeonggi. In addition, the advantages and disadvantages of the station data-based drought index and the satellite image-based drought index were identified by using results calculated through the comparison of SPI and SDCI. MODIS(MODerate resolution Imaging Spectroradiometer) satellite image data, ASOS(Automated Synoptic Observing System) data, and kriging were used to calculate SDCI. For the duration of precipitation, SDCI1, SDCI3, and SDCI6 were calculated by applying 1-month, 3-month, and 6-month respectively to the 8 points in 2014. As a result of calculating the SDCI, unlike the SPI, drought patterns began to appear about 2-month ago, and drought by city and county in Gyeonggi was well revealed. Through this, it was found that the combination of satellite image data and station data increased efficiency in the pattern of drought index change, and increased the possibility of drought prediction in wet areas along with existing dry areas.

• Journal of the Korean Association of Geographic Information Studies
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• v.18 no.2
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• pp.174-189
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• 2015

The objective of this study was to reconstruct spatial information using the results of the investigation and evaluation of the health of the living organisms, habitat, and water quality at the investigation points for the aquatic ecosystem health of the Nakdong River basin, to support the rational decision making of the aquatic ecosystem preservation and restoration policies of the Nakdong River basin using spatial analysis techniques, and to present efficient management methods. To analyze the aquatic ecosystem health of the Nakdong River basin, punctiform data were constructed based on the position information of each point with the aquatic ecosystem health investigation and evaluation results of 250 investigation sections. To apply the spatial analysis technique, the data need to be reconstructed into areal data. For this purpose, spatial influence and trends were analyzed using the Kriging interpolation(ArcGIS 10.1, Geostatistical Analysis), and were reconstructed into areal data. To analyze the spatial distribution characteristics of the Nakdong River basin health based on these analytical results, hotspot(Getis-Ord Gi, $G^*_i$), LISA(Local Indicator of Spatial Association), and standard deviational ellipse analyses were used. The hotspot analysis results showed that the hotspot basins of the biotic indices(TDI, BMI, FAI) were the Andong Dam upstream, Wangpicheon, and the Imha Dam basin, and that the health grades of their biotic indices were good. The coldspot basins were Nakdong River Namhae, the Nakdong River mouth, and the Suyeong River basin. The LISA analysis results showed that the exceptional areas were Gahwacheon, the Hapcheon Dam, and the Yeong River upstream basin. These areas had high bio-health indices, but their surrounding basins were low and required management for aquatic ecosystem health. The hotspot basins of the physicochemical factor(BOD) were the Nakdong River downstream basin, Suyeong River, Hoeya River, and the Nakdong River Namhae basin, whereas the coldspot basins were the upstream basins of the Nakdong River tributaries, including Andong Dam, Imha Dam, and Yeong River. The hotspots of the habitat and riverside environment factor(HRI) were different from the hotspots and coldspots of each factor in the LISA analysis results. In general, the habitat and riverside environment of the Nakdong River mainstream and tributaries, including the Nakdong river upstream, Andong Dam, Imha Dam, and the Hapcheon Dam basin, had good health. The coldspot basins of the habitat and riverside environment also showed low health indices of the biotic indices and physicochemical factors, thus requiring management of the habitat and riverside environment. As a result of the time-series analysis with a standard deviation ellipsoid, the areas with good aquatic ecosystem health of the organisms, habitat, and riverside environment showed a tendency to move northward, and the BOD results showed different directions and concentrations by the year of investigation. These aquatic ecosystem health analysis results can provide not only the health management information for each investigation spot but also information for managing the aquatic ecosystem in the catchment unit for the working research staff as well as for the water environment researchers in the future, based on spatial information.

• Journal of the Korean Association of Geographic Information Studies
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• v.8 no.3
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• pp.107-120
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• 2005

In Korea, MOCT and KOWACO published a standard for lineament map drawings, "The Handbook for the Drawing and Management of Hydrogeologic Map" in 2003. According to this guideline, hydrogeologic and related thematic maps should include characteristics of groundwater quality and quantity. These maps are generally drawn with ArcView GIS 3.x software. The activities of well notation on groundwater level map and Stiff diagram drawings on groundwater quality map require a great deal of efforts because hundreds or thousands of well data, water level data and hydrogeochemical data are produced through many kinds of investigations. As well, lineament density map is very important to survey and explore groundwater in a deep aquifer. In this study we developed some modules for well notation, Stiff diagram drawings, and lineament density value calculation with Avenue$^{TM}$ script and it was revealed that they can be very useful and easy for drawing groundwater thematic maps.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.13 no.6
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• pp.64-76
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• 2014

This study identified the causes of errors that could take place in the estimation process of vehicle miles traveled and quantified the effects of each of those causes on the estimation accuracy of vehicle miles traveled via error rate to propose an efficient way to estimate vehicle miles traveled. The study proceeded as follows: first, the study established survey data of vehicle miles traveled in the pilot test areas to test the accuracy of a method to estimate vehicle miles traveled. Second, the causes of errors with the estimation of vehicle miles traveled were categorized into errors with the sample size, sampling methods, and homogeneous link setting methods. In addition, many different methodologies were set to minimize errors with the estimation of vehicle miles traveled according to each of the causes. Third, error rates of estimation of vehicle miles traveled were compared and analyzed according to each of the methodologies. Finally, a toy network was established to propose a way of estimating vehicle miles traveled by taking the local characteristics into consideration. The study finds its significance in that it proposed an efficient way to estimate vehicle miles traveled through an experiment and planning approach and made use of survey data of vehicle miles traveled to test estimation accuracy. The proposed way of estimating vehicle miles traveled by taking into account the local characteristics will make a contribution to the estimation of vehicle miles traveled by the areas in future along with the level of data offered in the study.

• Geophysics and Geophysical Exploration
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• v.17 no.1
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• pp.28-33
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• 2014

We investigate the spatial distribution of highly conductive layer using the one-dimensional inversions of the new magnetotelluric (MT) measurements obtained at the mid-mountain (400 ~ 900 m in elevation) western area of Jeju Island and the previous MT data over Jeju Island, Korea. The conductive layer indicates the sedimentary layer comprised of Seoguipo Fomation and U Formation. There is a definite positive correlation between the top of conductive layer and the earth surface in elevation. On the contrary, the bottom of conductive layer has a negative correlation with the surface elevation. In other words, the conductive layer has a shape of convex lens, which is thickest in the central part. The basement beneath the conductive layer could be concave in the central part of Jeju Island. A kriging considering the correlation between the layer boundary and the surface elevation provides a reliable geoelectric structure model of Jeju Island. However, further studies, i.e. three-dimensional modeling and interpretation integrated with other geophysical or logging data, are required to reveal the possible presence of three-dimensional conductive body near the subsurface vent of Mt. Halla and the causes of the bias in the depths of layer estimated from MT and core log data.

• Journal of Korean Society of Forest Science
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• v.110 no.3
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• pp.322-340
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• 2021

Due to climate change and its consequential spring temperature rise, flowering time of Robinia pseudoacacia has advanced and a simultaneous blooming phenomenon occurred in different regions in South Korea. These changes in flowering time became a major crisis in the domestic beekeeping industry and the demand for accurate prediction of flowering time for R. pseudoacacia is increasing. In this study, we developed and compared performance of four different models predicting flowering time of R. pseudoacacia for the entire country: a Single Model for the country (SM), Modified Single Model (MSM) using correction factors derived from SM, Group Model (GM) estimating parameters for each region, and Local Model (LM) estimating parameters for each site. To achieve this goal, the bloom date data observed at 26 points across the country for the past 12 years (2006-2017) and daily temperature data were used. As a result, bloom dates for the north central region, where spring temperature increase was more than two-fold higher than southern regions, have advanced and the differences compared with the southwest region decreased by 0.7098 days per year (p-value=0.0417). Model comparisons showed MSM and LM performed better than the other models, as shown by 24% and 15% lower RMSE than SM, respectively. Furthermore, validation with 16 additional sites for 4 years revealed co-krigging of LM showed better performance than expansion of MSM for the entire nation (RMSE: p-value=0.0118, Bias: p-value=0.0471). This study improved predictions of bloom dates for R. pseudoacacia and proposed methods for reliable expansion to the entire nation.

• Economic and Environmental Geology
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• v.38 no.4 s.173
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• pp.435-450
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• 2005

The purpose of the study is to analyze the hydrogeochemical characteristics by multivariate statistical method, to interpret the hydrogeochemical processes for the new variables calculated from principal components analysis (PCA), and to infer the groundwater flow and circulation mechanism by applying the geostatistical methods for each element and principal component. Chloride and nitrate are the most influencing components for groundwater quality, and the contents of $NO_3$ increased by the input of agricultural activities show the largest variation. The results of PCA, a multivariate statistical method, show that the first three principal components explain $73.9\%$ of the total variance. PC1 indicates the increase of dissolved ions, PC2 is related with the dissolution of carbonate minerals and nitrate contamination, and PC3 shows the effect of cation exchange process and silicate mineral dissolution. From the results of experimental semivariogram, the components of groundwater are divided into two groups: one group includes electrical conductivity (EC), Cl, Na, and $NO_3$, and the other includes $HCO_3,\;SiO_2,$ Ca, and Sr. The results for spatial distribution of groundwater components showed that EC, Cl, and Na increased with approaching the coastal line and nitrate has close relationship with the presence of agricultural land. These components are also correlated with the topographic features reflecting the groundwater recharge effect. The kriging analysis by using principal components shows that PC 1 has the different spatial distribution of Cl, Na, and EC, possibly due to the influence of pH, Ca, Sr, and $HCO_3$ for PC1. It was considered that the linear anomaly zone of PC2 in western area was caused by the dissolution of carbonate mineral. Consequently, the application of multivariate and geostatistical methods for groundwater in the study area is very useful for determining the quantitative analysis of water quality data and the characteristics of spatial distribution.