• Journal of Korean Society of Forest Science
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• v.95 no.6
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• pp.663-671
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• 2006

This study was performed for exploring the spatial distribution pattern of Pinus densiflora and Quercus spp. in Korea. Firstly, the spatial distribution map of Pinus densiflora and Quercus spp. was prepared in grid of $100m{\times}100m$ at national level, using digital forest type map and actual vegetation map. And thematic maps for topography, climate, and soil were also prepared in the raster form of $100m{\times}100m$. Through GIS based spatial analysis of the digital distribution map of Pinus densiflora and Quercus spp. and thematic maps, the spatial characteristics of Pinus densiflora and Quercus spp. distribution was explored in relation to the environmental factors such as topography, climate, and soil. And the occurrence frequency models of Pinus densiflora and Quercus spp. were derived. Pinus densiflora occurs more often than Quercus spp. at low elevation, low slope gradient, and high temperature areas. In addition, Pinus densiflora is mainly distributed at shallow and well-drained loamy soil from igneous rocks. In contrast, Quercus spp. is more common at shallow and well-drained loamy soil from metamorphic rocks. As a result, the prediction model for the spatial distribution of Pinus densiflora and Quercus spp. by topographical variables has proven successful with high statistical significance. The result of this study can contribute to rational management of Pinus densiflora and Quercus spp. stand in Korea, considering environmental factors such as topography, climate, and soil.

• Journal of the Korean Geographical Society
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• v.46 no.3
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• pp.319-330
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• 2011

In this study, a soil moisture estimation model was proposed using the ground observation data of soil moisture, precipitation, surface temperature, MODIS NDVI and artificial neural networks. The model was calibrated and verified on the Yongdam dam watershed which has reliable ground soil moisture networks. The test statistics of calibration sites, Jucheon, Bugui, Sangjeon, showed that the correlation coefficients between observations and estimations are about 0.9353 and RMSE is about 1.4957%. Also that of the verification site, Cheoncheon2, showed that the correlation coefficient is about 0.8215 and RMSE is about 4.2077%. The soil moisture estimation model was applied to estimate the spatial distribution of soil moisture in the Yongdam dam watershed and results showed improved spatial soil moisture distribution since the model used satellite information of NDVI and artificial neural networks which can represent the nonlinear relationships between data well. The model should be useful to estimate wide range soil moisture information.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 1998.11a
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• pp.20-25
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• 1998

In order to support effective decision-making related to inter-sewage planning, this study proposes the spatial distribution method of inter-sewage treatement area using spatial analysis of GIS, Communication system of database, spatial interaction of Gravity model. Evalution Indexs are consist of economic, social/political and environmental condition value which are explained by the analysis of AHP algorithm ,based on opinion of related experts. Network module in Arc/Info is applied in order to find out minimum pipeline root in Miho river watershed, one of the sub-basin of Geum river basin. This value also is utilized for the construction of cost decay function in gravity model.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.61-64
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• 2005

The purpose of this paper is to take a closer look at an area having shorted emergence facilities and to determine optional candidate sites instead of vulnerable area by using GIS spatial analysis. Newly determined new candidate is performed by concerning spatial efficiency and spatial equity for a public service. It was determined through using the analyzing of the physical accessibility measure, the Location-Allocation, sort of classic model in spatial statistics and general network analysis. The area of this research has been used in administrative boundary of Young-Dong in Gangneung including 13 emergency, medical hospitals, 46 fire-stations and sub-fire stations. In general terms, what all this show is that the way we are approached for geographical view from using GIS spatial analyzing technique of determined location and allocation problem by the social, economical, political factor and simple administrative discrimination at the meantime. At the same time, with problem occurred in the space it is possible to make an Effective proposal or means, policy, decision for new candidate location-allocation suggesting optimum model.

• Journal of the Korean Geographical Society
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• v.51 no.4
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• pp.525-539
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• 2016

This study attempts to predict the changes in the spatial distribution of occupational employment in Korea by applying Markov Chain Model. For the purpose we analyze the job-related migration pattern and estimate the transition probability with the last six years job-related migration data. By applying the Chapman-Kolmogorov equation based on the transition probability, we predict the changes in the spatial distribution of occupational employment for the next ten years. The result reveals that the employment of professional jobs is predicted to increase at every city and region except Seoul, while the employment of elementary labor jobs is predicted to increase slightly in Seoul. In particular, Gangwon-do and Chuncheongdo are predicted to increase in the employment of all occupational jobs.

• Korean Journal of Remote Sensing
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• v.36 no.1
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• pp.83-92
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• 2020

The purpose of this work was to apply geographical information system (GIS) for geostatistical analyzing by selecting a semi-variogram model to quantify the spatial correlation of the population distribution with residential neighborhoods in the both sides of Mosul city. Two hundred and sixty-eight sample sites in 240 ㎢ are adopted. After determining the population distribution with respect to neighborhoods, data were inserted to ArcGIS10.3 software. Afterward, the datasets was subjected to the semi-variogram model using ordinary kriging interpolation. The results obtained from interpolation method showed that among the various models, Spherical model gives best fit of the data by cross-validation. The kriging prediction map obtained by this study, shows a particular spatial dependence of the population distribution with the neighborhoods. The results obtained from interpolation method also indicates an unbalanced population distribution, as there is no balance between the size of the population neighborhoods and their share of the size of the population, where the results showed that the right side is more densely populated because of the small area of residential homes which occupied by more than one family, as well as the right side is concentrated in economic and social activities.

• Journal of Veterinary Clinics
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• v.36 no.1
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• pp.23-29
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• 2019

While research findings suggest that the highly pathogenic avian influenza (HPAI) is the leading cause of economic loss in Korean poultry industry with an estimated cumulative impact of $909 million since 2003, identifying the environmental and anthropogenic risk factors involved remains a challenge. The objective of this study was to identify areas at high risk for potential HPAI outbreaks according to the likelihood of HPAI virus detection in wild birds. This study integrates spatial information regarding HPAI surveillance with relevant demographic and environmental factors collected between 2003 and 2018. The Maximum Entropy (Maxent) species distribution modeling with presence-only data was used to model the spatial risk of HPAI virus. We used historical data on HPAI occurrence in wild birds during the period 2003-2018, collected by the National Quarantine Inspection Agency of Korea. The database contains a total of 1,065 HPAI cases (farms) tied to 168 unique locations for wild birds. Among the environmental variables, the most effective predictors of the potential distribution of HPAI in wild birds were (in order of importance) altitude, number of HPAI outbreaks at farm-level, daily amount of manure processed and number of wild birds migrated into Korea. The area under the receiver operating characteristic curve for the 10 Maxent replicate runs of the model with twelve variables was 0.855 with a standard deviation of 0.012 which indicates that the model performance was excellent. Results revealed that geographic area at risk of HPAI is heterogeneously distributed throughout the country with higher likelihood in the west and coastal areas. The results may help biosecurity authority to design risk-based surveillance and implementation of control interventions optimized for the areas at highest risk of HPAI outbreak potentials.

• Journal of Environmental Science International
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• v.7 no.6
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• pp.817-825
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• 1998

A three-dimensional ecosystem model is applied to the Suyoung Bay, located at the southeastern part of Korea, to study of the material distribution in the time scale of several tens days. The model has included of the DIN(Dissolved Inorganic Nitrogen), DIP(Dissolved Inorganic Phosphate), phytoplankton, zooplankton and detritus, and also was coupled with the physical processes. The spatial distribution of chlorophyll-a and primary productivity in the model is determined by the physical and chemical-biological parameters. The horizontal distributions of the DIN, DIP and chlorophyll-a are decreased from the coast to the off-shore, though the nutrients show some more complicated pattern than the chlorophyll-a. The nutrient contents in the off-shore are low, and thus a relatively low productivity(chlorophyll-a) are presented. On the whole, the distribution of the results of model are smoother than the observed ones and some small scale variation in the observed data cannot be reproduced by the model due to the resolution limits of model. However, the basic pattern and the quantitavities has been reproduced by the model well.

• Tunnel and Underground Space
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• v.15 no.4 s.57
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• pp.264-274
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• 2005

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 levels is provided to estimate production costs for each process and to make a plan for an optimum blasting pattern.

• Journal of Distribution Research
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• v.15 no.4
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• pp.61-85
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• 2010

Introduction: Diffusion is process by which an innovation is communicated through certain channel overtime among the members of a social system(Rogers 1983). Bass(1969) suggested the Bass model describing diffusion process. The Bass model assumes potential adopters of innovation are influenced by mass-media and word-of-mouth from communication with previous adopters. Various expansions of the Bass model have been conducted. Some of them proposed a third factor affecting diffusion. Others proposed multinational diffusion model and it stressed interactive effect on diffusion among several countries. We add a spatial factor in the Bass model as a third communication factor. Because of situation where we can not control the interaction between markets, we need to consider that diffusion within certain market can be influenced by diffusion in contiguous market. The process that certain type of retail extends is a result that particular market can be described by the retail life cycle. Diffusion of retail has pattern following three phases of spatial diffusion: adoption of innovation happens in near the diffusion center first, spreads to the vicinity of the diffusing center and then adoption of innovation is completed in peripheral areas in saturation stage. So we expect spatial effect to be important to describe diffusion of domestic discount store. We define a spatial diffusion model using multinational diffusion model and apply it to the diffusion of discount store. Modeling: In this paper, we define a spatial diffusion model and apply it to the diffusion of discount store. To define a spatial diffusion model, we expand learning model(Kumar and Krishnan 2002) and separate diffusion process in diffusion center(market A) from diffusion process in the vicinity of the diffusing center(market B). The proposed spatial diffusion model is shown in equation (1a) and (1b). Equation (1a) is the diffusion process in diffusion center and equation (1b) is one in the vicinity of the diffusing center. $$\array{{S_{i,t}=(p_i+q_i{\frac{Y_{i,t-1}}{m_i}})(m_i-Y_{i,t-1})\;i{\in}\{1,{\cdots},I\}\;(1a)}\\{S_{j,t}=(p_j+q_j{\frac{Y_{j,t-1}}{m_i}}+{\sum\limits_{i=1}^I}{\gamma}_{ij}{\frac{Y_{i,t-1}}{m_i}})(m_j-Y_{j,t-1})\;i{\in}\{1,{\cdots},I\},\;j{\in}\{I+1,{\cdots},I+J\}\;(1b)}}$$ We rise two research questions. (1) The proposed spatial diffusion model is more effective than the Bass model to describe the diffusion of discount stores. (2) The more similar retail environment of diffusing center with that of the vicinity of the contiguous market is, the larger spatial effect of diffusing center on diffusion of the vicinity of the contiguous market is. To examine above two questions, we adopt the Bass model to estimate diffusion of discount store first. Next spatial diffusion model where spatial factor is added to the Bass model is used to estimate it. Finally by comparing Bass model with spatial diffusion model, we try to find out which model describes diffusion of discount store better. In addition, we investigate the relationship between similarity of retail environment(conceptual distance) and spatial factor impact with correlation analysis. Result and Implication: We suggest spatial diffusion model to describe diffusion of discount stores. To examine the proposed spatial diffusion model, 347 domestic discount stores are used and we divide nation into 5 districts, Seoul-Gyeongin(SG), Busan-Gyeongnam(BG), Daegu-Gyeongbuk(DG), Gwan- gju-Jeonla(GJ), Daejeon-Chungcheong(DC), and the result is shown