• 제목/요약/키워드: Distribution of Spatial Data

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한국 지적학 연구분야 공동저술활동의 공간분포패턴연구 (A Study on the Spatial Distribution Patterns of Co-authoring Activities in the Korean Cadastral Research Field)

  • 김윤기
    • 지적과 국토정보
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    • 제50권2호
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    • pp.203-219
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    • 2020
  • 본 연구의 주된 목적은 한국 지적 과학 분야 공동 저술 활동의 공간분포패턴을 식별하는 것이다. 분석 결과 소수의 연구자들이 한국 지적 공동 저작 네트워크에서 중요한 역할을 수행 한 것으로 나타났다. 특히 일부 저자는 네트워크의 다른 노드에 막대한 영향을 미쳤을 뿐만 아니라 연구자 간 중재자 역할을 충실히 수행하였다. 또한 한국 지적학 공동 저술 네트워크의 영향력 있는 연구자들은 특정 지역에 집중되어 있었다. 게다가, 연구자들 사이의 거리는 제한된 범위에서 공동 저작 결정에 영향을 미쳤다. 본 연구는 공간 분석 기법을 사용하여 공동 저작 활동의 공간 분포 패턴을 식별했다는 점에서 기존의 연구들과 큰 차이가 있다. 그러나 본 연구는 공동 저작 활동의 공간 분포 패턴을 식별하기 위해 2019년도 데이터만을 사용했다는 점에서 한계를 지니고 있다. 이러한 한계들은 우리가 향후 연구에서 복수 년도 자료를 이용하여 공동 저작 활동의 공간 분포 패턴을 분석한다면 극복할 수 있을 것이다.

Spatial Prediction Based on the Bayesian Kriging with Box-Cox Transformation

  • Choi, Jung-Soon;Park, Man-Sik
    • Communications for Statistical Applications and Methods
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    • 제16권5호
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    • pp.851-858
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    • 2009
  • In the last decades, there has been much interest in climate variability because its change has dramatic effects on humanity. Especially, the precipitation data are measured over space and their spatial association is so complicated. So we should take into account such a spatial dependency structure while analyzing the data. However, in linear models for analyzing the data, data sets show severely skewed distribution. In the paper, we consider the Box-Cox transformation to satisfy the normal distribution prior to the analysis, and employ a Bayesian hierarchical framework to investigate the spatial patterns. The data set we considered is monthly average precipitation of the third quarter of 2007 obtained from 347 automated monitoring stations in Contiguous South Korea.

공간 자료를 이용한 대기오염이 순환기계 건강에 미치는 영향 분석 (A Study on the effects of air pollution on circulatory health using spatial data)

  • 박진옥;최일수;나명환
    • 품질경영학회지
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    • 제44권3호
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    • pp.677-688
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    • 2016
  • Purpose: In this study, we examine the effects of circulatory diseases mortality in South Korea 2005-2013 using the air pollution index, Methods: We cluster the region of high risk mortality by SaTScan$^{TM}$9.3.1 and compare this result with the regional distribution of air pollution. We use the Geographically Weighted Regression (GWR) to consider the spatial heterogeneity of data collected by administrative district in order to estimate the model. As GWR is spatial analysis techniques utilizing the spatial information, regression model estimated for each region on the assumption that regression coefficients are different by region. Results: As a result of estimating model of the collected air pollution index, circulatory diseases mortality data combined with the spatial information, GWR was found to solve the problem of spatial autocorrelation and increase the fit of the model than OLS regression model. Conclusion: GWR is used to select the air pollution affecting the disease each year, the K-means cluster analysis discover the characteristics of the distribution of air pollution by region.

A mathematical spatial interpolation method for the estimation of convective rainfall distribution over small watersheds

  • Zhang, Shengtang;Zhang, Jingzhou;Liu, Yin;Liu, Yuanchen
    • Environmental Engineering Research
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    • 제21권3호
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    • pp.226-232
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    • 2016
  • Rainfall is one of crucial factors that impact on our environment. Rainfall data is important in water resources management, flood forecasting, and designing hydraulic structures. However, it is not available in some rural watersheds without rain gauges. Thus, effective ways of interpolating the available records are needed. Despite many widely used spatial interpolation methods, few studies have investigated rainfall center characteristics. Based on the theory that the spatial distribution of convective rainfall event has a definite center with maximum rainfall, we present a mathematical interpolation method to estimate convective rainfall distribution and indicate the rainfall center location and the center rainfall volume. We apply the method to estimate three convective rainfall events in Santa Catalina Island where reliable hydrological data is available. A cross-validation technique is used to evaluate the method. The result shows that the method will suffer from high relative error in two situations: 1) when estimating the minimum rainfall and 2) when estimating an external site. For all other situations, the method's performance is reasonable and acceptable. Since the method is based on a continuous function, it can provide distributed rainfall data for distributed hydrological model sand indicate statistical characteristics of given areas via mathematical calculation.

수중음향을 이용한 해초 서식처(Seagrass Habitats)의 공간 및 수직 분포 추정 (Estimating Spatial and Vertical Distribution of Seagrass Habitats Using Hydroacoustic System)

  • 강돈혁;조성호;라형술;김종만;나정열;명정구
    • Ocean and Polar Research
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    • 제28권3호
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    • pp.225-236
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    • 2006
  • Seagrass meadows are considered as critical habitats for a wide variety of marine organisms in coastal and estuarine ecosystems. In many cases, studies on the spatial/temporal distribution of seagrass have depended on direct observations using SCUBA diving. As an alternative method fur studying seagrass distribution, an application of hydroacoustic technique has been assessed for mapping seagrass distribution in Dongdae Bay, on the south coast of Korea, in September 2005. Data were collected using high frequency transducer (420 kHz split-beam), which was installed with towed body system. The system was linked to DGPS to make goo-referenced data. Additionally, in situ seagrass distribution has been observed using underwater cameras and SCUBA diving at four stations in order to compare with acoustic data. Acoustic survey was conducted along 23 transects with 3-4 blot ship speed. Seagrass beds were vertically limited to depths less than 3.5m and seagrass height ranged between 55 and 90cm at the study sites. Dense seagmss beds were mainly found at the entrance of the bay and at a flat area around the center of the bay. Although the study area was a relatively small, the vertical and spatial distributions of the seagrass were highly variable with bathymetry and region. Considering dominant species, Zostera marina L., preliminary estimation of seagrass biomass with acoustic and direct sampling data was approximately $56.55g/m^2$, and total biomass of 104 tones (coefficient variation: 25.77%) was estimated at the study area. Hydroacoustic method provided valuable information to understand distribution pattern and to estimate seagrass biomass.

Prediction of rock fragmentation and design of blasting pattern based on 3-D spatial distribution of rock factor

  • 심현진;한창연;남현우
    • 지반과기술
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    • 제3권3호
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    • pp.15-22
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    • 2006
  • The optimum blasting pattern to excavate a quarry efficiently and economically can be determined based on the minimum production cost, which is generally estimated according to rock fragmentation. Therefore, it is a critical problem to predict fragment size distribution of blasted rocks over an entire quarry. By comparing various prediction models, it can be ascertained that the result obtained from Kuz-Ram model relatively coincides with that of field measurements. Kuz-Ram model uses the concept of rock factor to signify conditions of rock mass such as block size, rock jointing, strength and others. For the evaluation of total production cost, it is imperative to estimate 3-D spatial distribution of rock factor for the entire quarry. In this study, a sequential indicator simulation technique is adopted for estimation of spatial distribution of rock factor due to its higher reproducibility of spatial variability and distribution models than Kriging methods. Further, this can reduce the uncertainty of predictor using distribution information of sample data. The entire quarry is classified into three types of rock mass and optimum blasting pattern is proposed for each type based on 3-D spatial distribution of rock factor. In addition, plane maps of rock factor distribution for each ground level are provided to estimate production costs for each process and to make a plan for an optimum blasting pattern.

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Spatial Pattern of Larix gmelini in a Spruce-fir Valley Forest of Xiaoxing'an Mountains, China

  • Jin, Guangze;Liu, Liang;Liu, Zhili;Kim, Ji-Hong
    • 한국산림과학회지
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    • 제99권5호
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    • pp.720-725
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    • 2010
  • On the basis of vegetation data in the 9.12 ha (380 m ${\times}$ 240 m) permanent sample plot of the spruce-fir valley forest in Liangshui National Reserve of Xiaoxing'an Mountains, the study was conducted to evaluate spatial distribution pattern and spatial association by using point pattern analysis for living and dead trees of Larix gmelini by DBH size class. The number of L. gmelini were counted as 59 living stems/ha (6.42 $m^2$/ha of basal area) and 34 dead stems/ha (2.86 $m^2$/ha of basal area). The distributional curve of diameter class exhibited bimodal shape. The analysis of spatial distribution patterns of all living larch stems noted the clumped distribution on the whole. The size of larch aggregates of dead stems was decreased as diameter class was increased. The distribution of dead stems became gradually randomized with decreased clumped size as the scale increased. Living stems and dead stems of the larch had positive spatial association at most of scales, illustrating that the occurrence of mortality of the larch tree was closely related to the distribution pattern of living larch trees.

Power Comparison of Independence Test for the Farlie-Gumbel-Morgenstern Family

  • Amini, M.;Jabbari, H.;Mohtashami Borzadaran, G.R.;Azadbakhsh, M.
    • Communications for Statistical Applications and Methods
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    • 제17권4호
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    • pp.493-505
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    • 2010
  • Developing a test for independence of random variables X and Y against the alternative has an important role in statistical inference. Kochar and Gupta (1987) proposed a class of tests in view of Block and Basu (1974) model and compared the powers for sample sizes n = 8, 12. In this paper, we evaluate Kochar and Gupta (1987) class of tests for testing independence against quadrant dependence in absolutely continuous bivariate Farlie-Gambel-Morgenstern distribution, via a simulation study for sample sizes n = 6, 8, 10, 12, 16 and 20. Furthermore, we compare the power of the tests with that proposed by G$\ddot{u}$uven and Kotz (2008) based on the asymptotic distribution of the test statistics.

GIS를 이용한 적조의 시-공간적 분포 분석 (The Temporal and Spatial Distribution Analysis of Red Tide using GIS)

  • 정종철
    • Spatial Information Research
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    • 제13권3호
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    • pp.253-260
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    • 2005
  • 본 연구의 목적은 GIS기술을 이용하여 적조의 시공간적인 분포를 분석하는 것이다. 적조에 의해 발생하는 피해는 적조 생물종에 따라 다양하게 나타난다 때문에 적조의 피해를 저감하기 위해서는 시-공간적인 적조 생물종의 분포특성을 파악하는 것이 중요하다. 이러한 관점에서 우리는 최초의 적조발생지역, 공간적 발생빈도, 적조의 이동 등을 분석하였다. 본 연구에서 사용된 공간자료는 적조 속보 보고에 의해 공간분포를 디지타이징하였고, 적조데이터베이스를 구축하기 위해 적조 생물종, 생물 밀도, 수온 등의 다양한 속성자료를 구성하였다. 적조의 시-공간적 분포 특성을 분석하기 위해 다양한 공간분석기법을 적용하였다. 이러한 공간분석 결과로부터 남해에서의 시-공간 적이 적조 공간 정보를 얻을 수 있었다.

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EOF와 CSEOF를 이용한 한반도 강수의 변동성 분석 (Investigation of Korean Precipitation Variability using EOFs and Cyclostationary EOFs)

  • 김광섭;순밍동
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2009년도 학술발표회 초록집
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    • pp.1260-1264
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    • 2009
  • Precipitation time series is a mixture of complicate fluctuation and changes. The monthly precipitation data of 61 stations during 36 years (1973-2008) in Korea are comprehensively analyzed using the EOFs technique and CSEOFs technique respectively. The main motivation for employing this technique in the present study is to investigate the physical processes associated with the evolution of the precipitation from observation data. The twenty-five leading EOF modes account for 98.05% of the total monthly variance, and the first two modes account for 83.68% of total variation. The first mode exhibits traditional spatial pattern with annual cycle of corresponding PC time series and second mode shows strong North South gradient. In CSEOF analysis, the twenty-five leading CSEOF modes account for 98.58% of the total monthly variance, and the first two modes account for 78.69% of total variation, these first two patterns' spatial distribution show monthly spatial variation. The corresponding mode's PC time series reveals the annual cycle on a monthly time scale and long-term fluctuation and first mode's PC time series shows increasing linear trend which represents that spatial and temporal variability of first mode pattern has strengthened. Compared with the EOFs analysis, the CSEOFs analysis preferably exhibits the spatial distribution and temporal evolution characteristics and variability of Korean historical precipitation.

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