• Title/Summary/Keyword: Geographic variation

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City center Regeneration in Busan Metropolitan Using GIS (GIS를 활용한 부산시 도심재생에 관한 연구)

  • Kim, Heung-Kwan;Yeo, Sung-Jun
    • Journal of the Korean Association of Geographic Information Studies
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    • v.10 no.1
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    • pp.205-217
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    • 2007
  • Donut phenomenon of city centers has resulted from the decreasing residential population and the fluid population with curved commercial function, but the analysis can bring other problems owing to the simplified method. And As the survey and the analysis the research can offer the characteristic methods for regeneration in the city of Busan. To figure out the functional regions of city center the research has analyzed 15 Dongs in city center of the three years of 1996, 2000 and 2004 to find out the donut phenomenon and the regeneration of city center. The survey has chosen 20 variation factors using factor analysis and cluster analysis. Major factors in each year are shown 3 factors, presenting 84.2%, 87.1% and 85.5% of the accumulated explanation rate. These factors explain residential centered, commercial centered, and management centered factor. The results are as following. First, it is necessary to plan the regeneration of the total city center owing to the total donut phenomenon regarding the functions. Second, the methods to regenerate city centers should be established according to the various regional characterizations.

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Analysis on the Spatial Accessibility of Mental Health Institutions Using GIS in Gangwon-Do (GIS를 이용한 정신의료기관의 공간적 접근성 분석 - 강원도지역을 대상으로)

  • Park, Ju Hyun;Park, Young Yong;Lee, Kwang-Soo
    • Korea Journal of Hospital Management
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    • v.23 no.2
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    • pp.28-41
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    • 2018
  • Purpose: This study purposed to analyze the spatial accessibility of mental health institutions in Ganwon-Do using Geographic Information System and to suggest policy implications. Methodology: Network analysis was applied to assess the spatial accessibility of mental health institutions in Gangwon-Do. To perform the network analysis, network data set was built using administrative district map, road network, address of mental health institutions in Gangwon-Do. After building network data set, Two network analysis methods, 1) Service area analysis, 2) Origin Destination cost matrix were applied. Service area analysis calculated accessive areas that were within specified time. And using Origin Destination cost matrix, travel time and road travel distance were calculated between centroids of Eup, Myeon, Dong and the nearest mental health institutions. Result: After the service area analysis, it is estimated that 19.63% of the total areas in Gangwon-Do takes more than 60 minutes to get to clinic institutions. For hospital institutions, 23.08% of the total areas takes more than 60 minutes to get there. And 59.96% of Gangwon-do takes more than 30 minutes to get to general hospitals. The result of Origin-Destination cost matrix showed that most Eup Myeon Dong in Gangwon-Do was connected to the institutions in Wonju-si, Chuncheon-si, Gangneung-si. And it showed that there were large regional variation in time and distance to reach the institutions. Implication: Results showed that there were regional variations of spatial accessibility to the mental health institutions in Gangwon-Do. To solve this problem, Several policy interventions could be applied such as mental health resources allocation plan, telemedicine, providing more closely coordinated services between mental health institutions and community mental health centers to enhance the accessibility.

Geographic Variation of Flowering Response to Daylength in Perilla frutescens var. frutescens in East Asia

  • Lee, Ju-Kyong;Ohmi Ohnishi
    • KOREAN JOURNAL OF CROP SCIENCE
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    • v.46 no.5
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    • pp.395-400
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    • 2001
  • We investigated the variations of the flowering response to daylength in Perilla crop (var. frutescens). Seventeen accessions of Perilla crop and one accession of weedy type of var. crispa from China, Korea and Japan were cultivated under three daylength conditions, i.e., short-days, natural daylength and long-days. Most accessions of Perilla crop from China, Korea and Japan were divided into three types, early maturing type, intermediate maturing type and late maturing type by their natural flowering habit. In most of the accessions used, the flowering habit was significantly accelerated by short-day conditions and was delayed by long-day conditions. All the accessions of Perilla crops flowered within 57 days under the 10 hrs light treatment, whereas they did not flower at all even at 170 days after sowing under the 16 hrs light treatment. Thus, this finding suggested that there is a relationship between the types of flowering response to daylength and the geographical distribution which determines the planting season in traditional cultivation practices of Perilla crops. Positive correlation was observed between days to flowering and plant height or internode number in both the short-day and natural daylength conditions. Whereas, correlation was negative between days to flowering and inflorescence length or floret number in natural daylength condition, but it was positive in the short-day condition. Therefore, the daylength condition is considered as the most important environmental factor for flowering habit and morphological characters of Perilla crops. Flowering habit is considered as an important key character for the study of geographical differentiation of Perilla crop in East Asia.

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The Application of Satellite Data to Land Surface Process Parameterization in ARPS Model (ARPS 모형 지면 과정 모수화에 위성 자료의 응용)

  • Ha, Kyung-Ja;Suh, Ae-Sook;Chung, Hyo-Sang
    • Journal of the Korean Association of Geographic Information Studies
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    • v.1 no.1
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    • pp.99-108
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    • 1998
  • In order to represent the surface characteristics in local meteorological model, soil type, vegetation index, surface roughness length, surface albedo and leaf area index should be prescribed on the surface process parameterization. In this study, the $1^{\circ}/1^{\circ}leaf$ area index, surface roughness length, and snow free surface albedo and fine mesh NDVI with seasonal variation derived from the satellite observation were applied to the land surface process parameterization. From comparison between with and without satellite data in the interactions between biosphere and atmosphere, land and atmosphere, the sensitivity of the simulated heat, energy and water vapor fluxes, ground temperature, wind, canopy water content, specific humidity, and precipitation fields were investigated.

GPS Data Collection and Application for the Analysis of Car Following Behavior (차량의 추종행태 분석을 위한 GPS 자료의 수집과 적용)

  • Woo, Yong-Han
    • Journal of the Korean Association of Geographic Information Studies
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    • v.3 no.4
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    • pp.11-21
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    • 2000
  • The travel behavior should be analysed microscopically for the traffic management of urban street. The car following theory which found out the correlation between the lead and the following vehicles is being widely used as basic data in many fields. As the vehicle position and its speed information can be received by GPS, this technique is recently applying to the various fields. For the case study the travel data were collected with two vehicles equipped with GPS receiver. The moving distance was calculated by the collected location data every 2 seconds and the speed variation was checked. And this study analysed and compared the acceleration and deceleration speed between the lead and the following vehicle. Finally, Regression model about the relationship between the acceleration and deceleration speed and the acceleration and deceleration distance was constructed. This model could be helpful for the road design and the regulation for the safe traffic management.

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Mapping the Geographic Variations of the Low Birth Weight cases in South Korea: Bayesian Approaches (우리나라 저체중아 출생의 공간적 변동성 지도화: 베이지언적 접근)

  • Roh, Young-hee;Park, Key-ho
    • Journal of the Korean Geographical Society
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    • v.51 no.3
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    • pp.367-380
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    • 2016
  • This study reviewed and compared methods for mapping aggregated low birth weight (LBW) and geographic variations in LBW in South Korea. Based on this review, we produced LBW maps in South Korea. Standardized mortality/morbidity ratios (SMRs) and crude mortality rates have been widely used for many years in epidemiological research. However, SMR-based maps are likely to be affected by sample size of unit area. Therefore, this study adopted a model-based approach using Bayesian estimates to reduce noisy variability in the SMR. By using a Bayesian model, we can calculate a statistically reliable RR values. We used the full Bayes estimator, as well as empirical Bayes estimators. As a result, variations in the two Bayes models were similar. The SMR-based statistics had the largest variation. The result maps can be used to identify regions with a high risk of LBW in South Korea.

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Spatial Analysis of Major Atmospheric Aerosol Species Using Earth Observing Satellite Data (지구관측 위성자료를 이용한 주요 대기 에어러솔 성분의 공간분포 분석)

  • Lee, Kwon-Ho
    • Journal of the Korean Association of Geographic Information Studies
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    • v.14 no.2
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    • pp.109-127
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    • 2011
  • Atmospheric aerosols, small particles in the atmosphere, are one of the important parameters in climate change and human health. Additionally, accurate estimates of aerosol species are increasingly important in environmental impact assessment studies. Recent advances in global satellite remote sensing provide powerful tool for air quality monitoring. This study explores the potential usage of satellite derived data such as atmospheric aerosols for air quality monitoring as well as climate change study. The objectives of this study is to understand the general features of the global distribution of type dependent aerosols. A detailed spatio-temporal variability of the each different satellite dataset shows the variation of the global zonal average and specific geographical regions where the strong emission sources are located. Especially, significantly large aerosol amounts are observed in Asia and Africa because of the desert dust storm, anthropogenic and biomass burning emissions.

Analysis of Molecular Variance and Population Structure of Sesame (Sesamum indicum L.) Genotypes Using Simple Sequence Repeat Markers

  • Asekova, Sovetgul;Kulkarni, Krishnanand P.;Oh, Ki Won;Lee, Myung-Hee;Oh, Eunyoung;Kim, Jung-In;Yeo, Un-Sang;Pae, Suk-Bok;Ha, Tae Joung;Kim, Sung Up
    • Plant Breeding and Biotechnology
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    • v.6 no.4
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    • pp.321-336
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    • 2018
  • Sesame (Sesamum indicum L.) is an important oilseed crop grown in tropical and subtropical areas. The objective of this study was to investigate the genetic relationships among 129 sesame landraces and cultivars using simple sequence repeat (SSR) markers. Out of 70 SSRs, 23 were found to be informative and produced 157 alleles. The number of alleles per locus ranged from 3 - 14, whereas polymorphic information content ranged from 0.33 - 0.86. A distance-based phylogenetic analysis revealed two major and six minor clusters. The population structure analysis using a Bayesian model-based program in STRUCTURE 2.3.4 divided 129 sesame accessions into three major populations (K = 3). Based on pairwise comparison estimates, Pop1 was observed to be genetically close to Pop2 with $F_{ST}$ value of 0.15, while Pop2 and Pop3 were genetically closest with $F_{ST}$ value of 0.08. Analysis of molecular variance revealed a high percentage of variability among individuals within populations (85.84%) than among the populations (14.16%). Similarly, a high variance was observed among the individuals within the country of origins (90.45%) than between the countries of origins. The grouping of genotypes in clusters was not related to their geographic origin indicating considerable gene flow among sesame genotypes across the selected geographic regions. The SSR markers used in the present study were able to distinguish closely linked sesame genotypes, thereby showing their usefulness in assessing the potentially important source of genetic variation. These markers can be used for future sesame varietal classification, conservation, and other breeding purposes.

Discontinuity in GNSS Coordinate Time Series due to Equipment Replacement

  • Sohn, Dong-Hyo;Choi, Byung-Kyu;Kim, Hyunho;Yoon, Hasu;Park, Sul Gee;Park, Sang-Hyun
    • Journal of Positioning, Navigation, and Timing
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    • v.11 no.4
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    • pp.287-295
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    • 2022
  • The GNSS coordinate time series is used as important data for geophysical analysis such as terrestrial reference frame establishment, crustal deformation, Earth orientation parameter estimation, etc. However, various factors may cause discontinuity in the coordinate time series, which may lead to errors in the interpretation. In this paper, we describe the discontinuity in the coordinate time series due to the equipment replacement for domestic GNSS stations and discuss the change in movement magnitude and velocity vector difference in each direction before and after discontinuity correction. To do this, we used three years (2017-2019) of data from 40 GNSS stations. The average magnitude of the velocity vector in the north-south, east-west, and vertical directions before correction is -12.9±1.5, 28.0±1.9, and 4.2±7.6 mm/yr, respectively. After correction, the average moving speed in each direction was -13.0±1.0, 28.2±0.8, and 0.7±2.1 mm/yr, respectively. The average magnitudes of the horizontal GNSS velocity vectors before and after discontinuous correction was similar, but the deviation in movement size of stations decreased after correction. After equipment replacement, the change in the vertical movement occurred more than the horizontal movement variation. Moreover, the change in the magnitude of movement in each direction may also cause a change in the velocity vector, which may lead to errors in geophysical analysis.

A Study on Building Identification from the Three-dimensional Point Cloud by using Monte Carlo Integration Method (몬테카를로 적분을 통한 3차원 점군의 건물 식별기법 연구)

  • YI, Chaeyeon;AN, Seung-Man
    • Journal of the Korean Association of Geographic Information Studies
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    • v.23 no.4
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    • pp.16-41
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    • 2020
  • Geospatial input setting to represent the reality of spatial distribution or quantitative property within model has become a major interest in earth system simulation. Many studies showed the variation of grid resolution could lead to drastic changes of spatial model results because of insufficient surface property estimations. Hence, in this paper, the authors proposed Monte Carlo Integration (MCI) to apply spatial probability (SP) in a spatial-sampling framework using a three-dimensional point cloud (3DPC) to keep the optimized spatial distribution and area/volume property of buildings in urban area. Three different decision rule based building identification results were compared : SP threshold, cell size, and 3DPC density. Results shows the identified building area property tend to increase according to the spatial sampling grid area enlargement. Hence, areal building property manipulation in the sampling frameworks by using decision rules is strongly recommended to increase reliability of geospatial modeling and analysis results. Proposed method will support the modeling needs to keep quantitative building properties in both finer and coarser grids.