• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.414-414
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• 2017

토양수분은 지면환경에서 일어나는 수문 및 에너지 순환을 이해하는 데 있어 중요한 기상인자이다. 토양수분 현장관측은 땅속에 매설된 센서에 의해 상당히 정확하게 이루어지만, 관측점 수가 충분치 않아 공간적 연속성을 확보하지 못하는 어려움이 존재한다. 이에 광역적 및 연속적 관측이 가능한 마이크로파 위성센서가 토양수분 정보 획득을 위한 보조수단으로서 그 중요성이 부각되고 있다. 마이크로파 위성센서는 구름 등 기상조건의 제약을 받지 않으며, 1978년 이래 현재까지 여러 위성에 의해 25 km 및 10 km 해상도의 전지구 토양수분자료가 생산되어 왔다. 마이크로파 센서를 이용한 토양수분자료는 동일지점에 대하여 하루 2회 정도 산출되므로 적절한 시간분해능을 가지지만, 공간해상도가 최고 10 km로서 지역규모의 수문분석에 적용하기에는 충분치 않다. 이러한 토양수분자료의 공간해상도 문제 해결을 위하여 다양한 지면환경요소를 활용한 통계적 다운스케일링이 대안으로 제시되었다. 최근의 선행연구들은 대부분 방정식을 이용한 결합모형을 통해 통계적 다운스케일링을 수행하였는데, 회귀식과 같은 선형결합뿐 아니라 신경망이나 기계학습 등의 비선형결합에서도, 불가피하게 발생할 수밖에 없는 잔차(residual)로 인하여 다운스케일링 전후의 공간분포 패턴이 달라져버리는 문제를 안고 있었다. 회귀분석에 잔차의 공간내삽을 결합시킨 회귀크리깅(regression kriging)은 잔차보정을 통해 이러한 문제를 해결함으로써 다운스케일링 전후의 공간분포 일관성을 보장하는 기법이다. 이 연구에서는 회귀크리깅을 이용하여 일자별 AMSR2(Advanced Microwave Scanning Radiometer 2) 토양수분 자료를 10 km에서 1 km 해상도로 다운스케일링하고, 다운스케일링 전후의 자료패턴 일관성을 평가한다. 지면온도(LST), 지면온도상승률(RR), 식생온도건조지수(TVDI)는 일자별로 DB를 구축하였고, 식생지수(NDVI), 수분지수(NDWI), 지면알베도(SA)는 8일 간격으로 DB를 구축하였다. 이러한 8일 간격의 자료를 일자별로 변환하기 위하여 큐빅스플라인(cubic spline)을 이용하여 시계열내삽을 수행하였다. 또한 상이한 공간해상도의 자료는 최근린법을 이용하여 다운스케일링 목표해상도인 1 km에 맞도록 변환하였다. 우선 저해상도 스케일에서 추정치를 산출하기 위해서는 저해상도 픽셀별로 이에 해당하는 복수의 고해상도 픽셀을 평균화하여 대응시켜야 하며, 이를 통해 6개의 설명변수(LST, RR, TVDI, NDVI, NDWI, SA)와 AMSR2 토양수분을 반응변수로 하는 다중회귀식을 도출하였다. 이식을 고해상도 스케일의 설명변수들에 적용하면 고해상도 토양수분 추정치가 산출되는데, 이때 추정치와 원자료의 차이에 해당하는 잔차에 대한 보정이 필요하다. 저해상도 스케일로 존재하는 잔차를 크리깅 공간내삽을 통해 고해상도로 변환한 후 이를 고해상도 추정치에 부가해주는 방식으로 잔차보정이 이루어짐으로써, 다운스케일링 전후의 자료패턴 일관성이 유지되는(r>0.95) 공간상세화된 토양수분 자료를 생산할 수 있다.

• The Journal of Engineering Geology
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• v.29 no.3
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• pp.265-277
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• 2019

Changes in the amount, intensity, frequency, and type of precipitation, in conjunction with global warming and climate change, critically impact groundwater recharge and associated groundwater level fluctuations. Monthly gravity levels by the Gravity Recovery and Climate Experiment (GRACE) are acquired to monitor total water storage changes at regional and global scales. However, there are inherent difficulties in quantitatively relating the GRACE observations to groundwater level data due to the difficulties in spatially representing groundwater levels. Here three local interpolation methods (kriging, inverse distance weighted, and natural neighbor) were implemented to estimate the areal distribution of groundwater recharge changes in South Korea during the 2002-2016 period. The interpolated monthly groundwater recharge changes are compared with the GRACE-derived groundwater storage changes. There is a weak decrease in the groundwater recharge changes over time in both the GRACE observations and groundwater measurements, with the rate of groundwater recharge change exhibiting mean and median values of -0.01 and -0.02 cm/month, respectively.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.2
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• pp.377-386
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• 2021

The A60 class deck penetration piece is a fire-resistant system installed on a horizontal compartment to prevent flame spreading and protect lives in fire accidents in ships and offshore plants. This study deals with approximate optimization using discrete variables for the fire resistance design of an A60 class deck penetration piece using different surrogate models and a genetic algorithm. Transient heat transfer analysis was performed to evaluate the fire resistance design of the A60 class deck penetration piece. For the approximate optimization of the piece, the length, diameter, material type, and insulation density were applied to discrete design variables, and temperature, productivity, and cost constraints were considered. The approximate optimum design problem based on the surrogate models was formulated such that the discrete design variables were determined by minimizing the weight of the piece subjected to the constraints. The surrogate models used in the approximate optimization were the response surface model, Kriging model, and radial basis function-based neural network. The approximate optimization results were compared with the actual analysis results in terms of approximate accuracy. The radial basis function-based neural network showed the most accurate optimum design results for the fire resistance design of the A60 class deck penetration piece.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.1
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• pp.434-439
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• 2019

Recently, interest in urban temperature change and ground surface temperature change has been increasing due to weather phenomenon due to global warming, heat island phenomenon caused by urbanization in urban areas. In Korea, weather data such as temperature and precipitation have been collected since 1904. In recent years, there are 96 ASOS stations and 494 AWS weather observation stations. However, in the case of terrestrial networks, terrestrial meteorological data except measurement points are predicted through interpolation because they provide point data for each installation point. In this study, to improve the resolution of ground surface temperature measurement, the surface temperature using satellite image was calculated and its applicability was analyzed. For this purpose, the satellite images of Landsat 8 OLI TIRS were obtained for Seoul Metropolitan City by seasons and transformed to surface temperature by applying NASA equation to the thermal bands. The ground measurement data was based on the temperature data measured by AWS. Since the AWS temperature data is station based point data, interpolation is performed by Kriging interpolation method for comparison with Landsat image. As a result of comparing the satellite image base surface temperature with the AWS temperature data, the temperature difference according to the season was calculated as fall, winter, summer, based on the RMSE value, Spring, in order of applicability of Landsat satellite image. The use of that attribute and AWS support starts at $2.11^{\circ}C$ and RMSE ${\pm}3.84^{\circ}C$, which reflects information from the extended NASA.

• Journal of the Korea Convergence Society
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• v.12 no.3
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• pp.187-196
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• 2021

The paper deals with comparative study for characteristics of approximation of design space according to various approximate models and sensitivity analysis using orthogonal array experiments in structure design of active type DSF which was developed for float-over installation of offshore plant. This study aims to propose the orthogonal array experiments based design methodology which is able to efficiently explore an optimum design case and to generate the accurate approximate model. Thickness sizes of main structure member were applied to the design factors, and output responses were considered structure weight and strength performances. Quantitative effects on the output responses for each design factor were evaluated using the orthogonal array experiment. Best design case was also identified to improve the structure design with weight minimization. From the orthogonal array experiment results, various approximate models such as response surface model, Kriging model, Chebyshev orthogonal polynomial model, and radial basis function based neural network model were generated. The experiment results from orthogonal array method were validated by the approximate modeling results. It was found that the radial basis function based neural network model among the approximate models was able to approximate the design space of the active type DSF with the highest accuracy.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.1
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• pp.150-163
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• 2022

Recently, the gated community has been increasing due to various reasons such as demand for differentiated areas and security, but various problems have been raised, including regional conflicts, traffic restrictions and disconnection of surrounding areas. Therefore, this study empirically considered what kind of spatial effect the gated community has on the surrounding area by analyzing the vitality using floating population big data and analyzing pedestrian accessibility using network analysis and social network analysis. As a result, it was found that the overall vitality in the study area was greatly affected by the land use and the building use. However, focusing on apartment complexes, even in the same land use, when the form of the complex is open to the outside, there is a lot of floating population, so the vitality is high. In terms of accessibility, assuming that the gated community is open, it was found that as the physical connectivity improved, there were more roads for pedestrians to choose from, and the accessibility improved as traffic and exchanges occurred in the disconnected space. The value of improving property rights and residential environment is also precious, but it is necessary to review how to reflect the improvement of local permeability in enhancing the publicness of cities and the value and direction of communities that can coexist with the region.

• 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 Geotechnical Society
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• v.38 no.3
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• pp.35-42
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• 2022

The N-value from the Standard Penetration Test (SPT), which is one of the representative in-situ test, is an important index that provides basic geological information and the depth of the bearing layer for the design of geotechnical structures. In the aspect of time and cost-effectiveness, there is a need to carry out a representative sampling test. However, the various variability and uncertainty are existing in the soil layer, so it is difficult to grasp the characteristics of the entire field from the limited test results. Thus the spatial interpolation techniques such as Kriging and IDW (inverse distance weighted) have been used for predicting unknown point from existing data. Recently, in order to increase the accuracy of interpolation results, studies that combine the geotechnics and deep learning method have been conducted. In this study, based on the SPT results of about 22,000 holes of ground survey, a comparative study was conducted to predict the depth of the bearing layer using deep learning methods and IDW. The average error among the prediction results of the bearing layer of each analysis model was 3.01 m for IDW, 3.22 m and 2.46 m for fully connected network and PointNet, respectively. The standard deviation was 3.99 for IDW, 3.95 and 3.54 for fully connected network and PointNet. As a result, the point net deep learing algorithm showed improved results compared to IDW and other deep learning method.

• Journal of Environmental Health Sciences
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• v.50 no.1
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• pp.6-15
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• 2024

Background: People's activities have been restricted due to the COVID-19 pandemic. These changes in activity patterns may lead to a decrease in fine particulate matter (PM_2.5) concentrations. Additionally, the level of population exposure to PM_2.5 may be changed. Objectives: This study aimed to analyze the impact of population movement and meteorological factors on the distribution of PM_2.5 concentrations before and after the outbreak of COVID-19. Methods: The study area was Guro-gu in Seoul. The research period was selected as January to March 2020, a period of significant population movement changes caused by COVID-19. The evaluation of the dynamic population was conducted by calculating the absolute difference in population numbers between consecutive hours and comparing them to determine the daily average. Ambient PM_2.5 concentrations were estimated for each grid using ordinary kriging in Python. For the population exposure assessment, the population-weighted average concentration was calculated by determining the indoor to outdoor population for each grid and applying the indoor to outdoor ratio to the ambient PM_2.5 concentration. To assess the factors influencing changes in the ambient PM_2.5 concentration, a statistical analysis was conducted, incorporating population mobility and meteorological factors. Results: Through statistical analysis, the correlation between ambient PM_2.5 concentration and population movement was positive on both weekends and weekdays (r=0.71, r=0.266). The results confirmed that most of the relationships were positive, suggesting that a decrease in human activity can lead to a decrease in PM_2.5 concentrations. In addition, when population-weighted concentration averages were calculated and the exposure level of the population group was compared before and after the COVID-19 outbreak, the proportion of people exceeding the air quality standard decreased by approximately 15.5%. Conclusions: Human activities can impact ambient concentrations of PM_2.5, potentially altering the levels of PM_2.5 exposure in the population.

• Korean Journal of Soil Science and Fertilizer
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• v.22 no.3
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• pp.163-172
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• 1989

In order to study spatial variability of soil physical properties accross the land-partitioned boundary on Hwadong silt clay loam soil (Fine clayey, mixed, mesic family of Aquic Hapludalfs), all measured data were analyzed by means of kriging, fractile diagram, smooth frequency distribution, and autocorrelation. Sampling for soil particle size distribution analysis was made at 225 intersections of $15{\times}15$ grid with 10m interval. Field capacity, bulk density and saturated hydraulic conductivity were measured in situ at 594 intersections of $33{\times}18$ grid with 2.5m interval in only $6,000m^2$ reselected from $22,500m^2$ of sampling area for particle size distribution analysis. Sampled or measured soil depths were 0 to 10cm 25 to 35cm and 50 to 60cm at each intersections. The results are summarized as follows: 1. The coefficient of variance (CV) of various physical properties ranges from 4.8 to 128.8%. Saturated hydraulic conductivity is classified into the high variation group with CV greater than 100%, while the low variation group with CV smaller than 10% consists of bulk density. Other properties belong to the medium variation group with CV between 10 and 100%. 2. The appropriate number of soil samples for the determination of various physical properties with error smaller than 10% are calculated as one for bulk density, six for field moisture capacity, 16 for silt, 19 for clay, 69 for sand and 686 for saturated hydraulic conductivity. 3. Smooth frequency distribution and fractile diagram show that saturated hydraulic conductivity is in lognormal distribution while other physical properties are in normal distribution. 4. Serial correlation analysis reveals that the soil physical properties have spatial dependence between two nearest neighbouring grid points. Autocorrelation analysis of physical properties measured between the serial grid points in the direction of south to north following section boundary shows that the zone of influence showing stationarity ranges from 7.5 to 40m. In the direction of east to west across section boundary, the autocorrelogram of many physical properties shows peaks with the periodic interval of 30m, which are similar to the partitioned land width. This reveals that the land-partitioned boundary causes soil variability.