• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.9
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• pp.1818-1825
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• 2017

An Acoustic Doppler Current Profiler(ADCP) measures the current velocity and analyzes the degree of turbulence using Doppler effects of ultrasonic waves. Therefore, the autocorrelation or FFT spectrum estimates are obtained for extraction of current velocity in each spatial region. However, if the correlation method does not satisfy the assumption that the return signal spectra are symmetric Gaussian, the large bias errors can occur. Also, the accurate estimation of autocorrelation or FFT spectrum is difficult due to the short acquisition interval when the rapid changes of current velocity occur. Thus, in this paper, the estimation method of the autoregressive spectrum peak is suggested for the accurate current velocity measurement of both symmetric and asymmetric spectra. It is shown that estimation quality can be improved using the suggested method comparing with the conventional methods. Many return signals under the various environment are simulated and the results are compared and analyzed for evaluation of the suggested method.

• Journal of the Korean Data and Information Science Society
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• v.27 no.5
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• pp.1155-1168
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• 2016

This paper considers a probability density estimation problem of climate values. In particular, we focus on estimating probability densities of summer extreme temperature over South Korea. It is known that the probability density of climate values at one location is similar to those at near by locations and one doesn't follow well known parametric distributions. To accommodate these properties, we use a mixture of conditional autoregressive species sampling model, which is a nonparametric Bayesian model with a spatial dependency. We apply the model to a dataset consisting of summer maximum temperature and minimum temperature over South Korea. The dataset is obtained from University of East Anglia.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.4
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• pp.162-174
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• 2012

To visualize the characteristics of vertical seawater temperature data, in the ocean having 3D spatial characteristics, 2D thematic maps like horizontal seawater temperature distribution map at each depth layer and 3D volume model using 3D spatial interpolation are used. Although these methods are useful to understand oceanographic phenomena visually, there is a limit to analyze the spatial pattern of vertical temperature distribution or the relationship between vertical temperature characteristics and other oceanic factors (seawater chemistry, marine organism, climate change, etc). Therefore, this study aims to determine the spatial distribution characteristics of vertical temperature profiles in the South Sea of Jeju by quantifying the characteristics of vertical temperature profiles by using an algorithm that can extract the thermocline parameters, such as mixed layer depth, maximum temperature gradient and thermocline thickness. For this purpose spatial autocorrelation index (Moran's I) was calculated including mapping of spatial distribution for three parameters representing the vertical temperature profiles. Also, after grouping study area as four regions by using cluster analysis with three parameters, the characteristics of vertical temperature profiles were defined for each region.

• Journal of the Korean Association of Geographic Information Studies
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• v.12 no.1
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• pp.12-25
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• 2009

The aim of this study is to analyze the periodical and spatial characteristics of urban crime and to find out the factors that affect the crime occurrence. For these, crime data of Masan City was examined and crime occurrence pattern is ploted on a map using crime density and criminal hotspot analysis. The spatial relationship of crime occurrence and factors affecting crime were also investigated using ESDA (Exploratory Spatial Data Analysis) and SAR (Spatial Auto-Regression) model. As a result, it was found that crimes had strong tendency of happening during a certain period of time and with spatial contiguity. Spatial contiguity of crimes was made clear through the spatial autocorrelation analysis on 5 major crimes. Especially, robbery revealed the highest spatial autocorrelation. However as a autocorrelation model, Spatial Error Model(SEM) had statistically the highest goodness of fit. Moreover, the model proved that old age population ratio, property tax, wholesale-retail shop number, and retail & wholesale number were statistically significant that affect crime occurrence of 5 most major crimes and theft crime. However population density affected negatively on assault crime. Lastly, the findings of this study are expected to provide meaningful ideas to make our cities safer with U-City strategies and services.

• Journal of Korean Society for Geospatial Information Science
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• v.23 no.3
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• pp.77-84
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• 2015

The key objective of this research is to review the effectiveness of spatial regression to identify the influencing factors of spatial distribution patterns of floating population. To this end, global and local spatial autocorrelation test were performed using seoul floating population survey(2014) data. The result of Moran's I and Getis-Ord $Gi^*$ as used in the analysis derived spatial heterogeneity and spatial similarities of floating population patterns in a statistically significant range. Accordingly, Geographically Weighted Regression was applied to identify the relationship between land use attributes and population floating. Urbanization area, green tract of land of micro land cover data were aggregated in to $400m{\times}400m$ grid boundary of Seoul. Additionally public transportation variables such as intersection density transit accessibility, road density and pedestrian passage density were adopted as transit environmental factors. As a result, the GWR model derived more improved results than Ordinary Least Square(OLS) regression model. Furthermore, the spatial variation of applied local effect of independent variables for the floating population distributions.

• Journal of the Korean Association of Geographic Information Studies
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• v.19 no.2
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• pp.73-85
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• 2016

Systematic and efficient forestry management is required because of the long-term low profitability of timber production and forest products. In this situation, non-timber forest products can be the solution to secure stable sources of income for workers in the forestry field. However, the existing studies for non-timber forest products focus on effective production and economic analysis and provide plans for increasing the income and improving the marketing system. Therefore, this research intends to analyze the spatial distribution as well as quantitative concentration of non-timber forest production. To achieve this goal, this study examined the regional concentration and dispersion of non-timber forest production in 2001, 2007, and 2014 using the coefficient of localization(CL) and location quotient(LQ) and investigated the change in spatial distribution using spatial statistics. The production of chestnuts generally showed a concentrated pattern in 2014 based on the outputs of the CL and LQ, but the result of spatial autocorrelation indicated a decrease in the spatial concentration. In addition, astringent persimmon showed more concentration from the output of CL than oak mushroom, but Moran's I suggests the opposite. Therefore, it is necessary to examine the spatial distribution to understand and improve the marketing system and intensify the production of forest products.

• Journal of the Economic Geographical Society of Korea
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• v.12 no.3
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• pp.248-259
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• 2009

This paper analyzes the interactions among regional labor markets in Korea. Specifically, we focus on the job market externality between neighboring regions. To estimate the job matching functions, we construct panel data on unemployment, vacancies and hires for the period of January 2004 through December 2007 for 15 cities and provinces in Korea. We employ various spatial econometric techniques to avoid the problem of spatial autocorrelation which frequently arises when dealing with regional data. Main findings are as follows. First, estimation results are consistent with conventional job matching theory. That is, as the number of job searchers and vacancies increase, the number of hires also rises. And it is relatively easier for firms to hire workers than for job seekers to find jobs. Second, it is found that, other things equal, the possibility of job matching is higher in large metropolitan areas than rural areas. Finally, the findings show that the number of job searchers in neighboring areas is negatively correlated with the number of hires in the area. Likewise, the number of vacancies in neighboring areas is positively correlated with number of hires in the area. These provide clear evidence on the existence of regional spillover effects.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.3
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• pp.39-53
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• 2014

The Korean population is aging rapidly and a disproportionate share of older people(aged 65 and older) lives in rural areas. The rural population is aging more rapidly than the population in urban area. However, the majority of studies on aging population focuses on an urban area rather than a rural area. Rural areas have been alienated from the priority of the national policy. For these reasons, this study is to show the level of population aging and to analyze the spatial spillover patterns of aging population in rural areas for the establishment of localized policy on population aging. The main findings of this study can be summarized as follows. First, the level of population aging varies in different localities such as socio-economic and locational characteristics. Secondly, there are distinct differences between hot spot region(clustering of high aging index) and cold spot region(clustering of low aging index) in spatio-temporal spillover patterns. This study intends to suggest an useful information to establish the area-specific policy on aging population through the results of analysis.

• Journal of the Economic Geographical Society of Korea
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• v.9 no.3
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• pp.318-340
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• 2006

In the last decade, there has been a widespread interest in knowledge production activities as a new engine of endogeneous growth. In the knowledge-based economy, there has been a growing importance of the patent as the index of knowledge production. Much literature suggests that knowledge production activities tend to be spatially concentrated and formed the clusters in the advanced economies. The purpose of this paper is to analyze spatial-temporal patterns of knowledge production activities in Korea based on a data set of patents from 1981-2000. This paper uses spatial statistical methods and GIS to explore the spatial dimensions of knowledge production activities in Korea. Through this research, it was found that knowledge production activities were unevenly distributed. The knowledge production activity measured by patent counts is highly concentrated in a limited number of cities. The top 10 cities accounted for 68.5% of the total number of patents in the period of 1981-2000, suggesting the existence of a strong concentration of knowledge production activities in Korea. The locations of knowledge production activities by themselves represented a strong spatial autocorrelation. The concentration of knowledge production activities in Korea is spatially correlated to the concentration of adjacent neighboring cities. The location of knowledge production activities is not free from a spatial context and spillover of knowledge production activities are heavily bounded within geographic limits, forming a spatial cluster. There appear some quite a large spatial cluster around the seoul metropolitan area.

• Journal of the Economic Geographical Society of Korea
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• v.23 no.2
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• pp.125-146
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• 2020

There is an increasing need to foster new industries at the local level. This study aims to analyze the spatial patterns of new industries in Korea from 2007-2017 and to figure out its determinants of agglomeration in 2017. Through this study, it is found that new industries are unevenly distributed around Seoul Metropolitan Area(SMA). The regional disparity between SMA and non-SMA is prominent. Furthermore, new industries represent a strong spatial positive autocorrelation, showing a strong concentration on a few regions in Korea. This study explores the determinants on agglomeration of new industries with spatial statistical model. From the results of spatial error model, it is indicated that the number of graduate students, the ratio of technology based start-ups, and the number of elementary, middle, and high schools have a significant effect on new industries. In addition, the specialization and the diversity of industrial structure on knowledge-based manufacturing industries and knowledge-based service industries have been statistically significant. This study provides implications that non-SMA needs policies with respect to attracting talented people, developing human resources, and improving regional environment in order to improve regional competitiveness in promoting new industries.