• 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 of Rural Planning
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• v.14 no.2
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• pp.13-23
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• 2008

In this paper, we estimated the economic impacts of Korea-EU FTA on the agricultural sector in GyeongGi-Do. In particular, we estimated the economic impacts of agricultural production decrease resulting from Korea-EU FTA for 31 sub-regions in GyeongGi-Do by 15 industrial sectors. We employ a regional economic impact model combining a regional input-output model with a spatial allocation model. We found that the size of inter-industrial impacts are quite different across regions. Our results suggest the importance of agricultural and industrial policy considering the impacts of industrial sectors at the regional level.

• Journal of Korean Society on Water Environment
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• v.23 no.6
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• pp.872-880
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• 2007

For effective management of sediment-related diffuse pollution, it is of utmost importance to estimate spatial variation of sediment transport processes within a catchment. A mathematical model can play a critical role in estimating sediment transport processes at the catchment scale provided that the model structure is appropriate for representing major sediment transport processes of the catchment of interest. This paper introduces a distributed catchment model River Basin Water Quality Simulator (RBWQS) and presents some results of its application to a small rural catchment in Korea. The model has been calibrated and validated for a wet period using hourly hydrographs and sediment concentrations observed at the catchment outlet. Based on the model simulation results, the spatial variation of sediment transport processes across the catchment and the effects of paddy fields and small reservoirs on hydrology and sediment transport have been analyzed at the catchment scale.

• Journal of the Korean Data and Information Science Society
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• v.27 no.5
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• pp.1225-1239
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• 2016

We investigate pediatric tumor incidence data collected by the Florida Association for Pediatric Tumor program using various models commonly used in disease mapping analysis. Particularly, we consider Poisson normal models with various conditional autoregressive structure for spatial dependence, a zero-in ated component to capture excess zero counts and a spatio-temporal model to capture spatial and temporal dependence, together. We found that intrinsic conditional autoregressive model provides the smallest Deviance Information Criterion (DIC) among the models when only spatial dependence is considered. On the other hand, adding an autoregressive structure over time decreases DIC over the model without time dependence component. We adopt weighted ranks squared error loss to identify high risk regions which provides similar results with other researchers who have worked on the same data set (e.g. Zhang et al., 2014; Wang and Rodriguez, 2014). Our results, thus, provide additional statistical support on those identied high risk regions discovered by the other researchers.

• Journal of Korea Spatial Information System Society
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• v.10 no.4
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• pp.59-66
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• 2008

GeoSensor network means sensor network infra and related software of specific form monitoring a variety of circumstances over geospatial. And these GeoSensor network is implemented by mixing data stream with spatial attribute, spatial relation. But, until a recent date sensor network system has been concentrated on a store and search method of sensor data stream except for a spatial information. In this paper, we propose a definition of spatial data stream and its join strategy model at GeoSensor network, which combine data stream with spatial data. Spatial data stream s defining in this paper are dynamic spatial data stream of a moving object type and static spatial data stream of a fixed type. Dynamic spatial data stream is data stream transmitted by moving sensor as GPS, while static spatial data stream is generated by joining a data stream of general sensor and a relation with location values of these sensors. This paper propose joins of dynamic spatial data stream and static spatial data stream, and cost models estimating join cost. Finally, we show verification of proposed cost models and performance by join strategy.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.20 no.6
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• pp.133-149
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• 2017

As cities face increasing problems such as aging, environmental pollution and growth limits, we have been trying to incorporate sustainability into urban planning and related policies. However, it is very difficult to generate a 'sustainable spatial plans' because there are trade-offs among environmental, society, and economic values. This is a kind of non-linear problem, and has limitations to be solved by existing qualitative expert knowledge. Many researches from abroad have used the meta heuristic optimization algorithms such as Genetic Algorithms(GAs), Simulated Annealing(SA), Ant Colony Optimization(ACO) and so on to synthesize competing values in spaces. GAs is the most frequently applied theory and have been known to produce 'good-enough plans' in a reasonable time. Therefore we collected the research on 'spatial optimization model based GAs' and analyzed in terms of 'study area', 'optimization objective', 'fitness function', and 'effectiveness/efficiency'. We expect the results of this study can suggest that 'what problems the spatial optimization model can be applied to' and 'linkage possibility with existing planning methodology'.

• Wind and Structures
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• v.16 no.5
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• pp.433-455
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• 2013

A phase delay spectrum model towards the representation of spatial coherence of stochastic wind fields is proposed. Different from the classical coherence functions used in the spectral representation methods, the model is derived from the comprehensive description of coherence of fluctuating wind speeds and from the thorough analysis of physical accounts of random factors affecting phase delay, building up a consistent mapping between the simulated fluctuating wind speeds and the basic random variables. It thus includes complete probabilistic information of spatial stochastic wind fields. This treatment prompts a ready and succinct scheme for the simulation of fluctuating wind speeds, and provides a new perspective to the accurate assessment of dynamic reliability of wind-induced structures. Numerical investigations and comparative studies indicate that the developed model is of rationality and of applicability which matches well with the measured data at spatial points of wind fields, whereby the phase spectra at defined datum mark and objective point are feasibly obtained using the numerical scheme associated with the starting-time of phase evolution. In conjunction with the stochastic Fourier amplitude spectrum that we developed previously, the time history of fluctuating wind speeds at any spatial points of wind fields can be readily simulated.

• Asia-Pacific Journal of Business
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• v.13 no.1
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• pp.277-288
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• 2022

Purpose - This study analyzed the determinants of local unemployment rate in Korea using panel data from 16 metropolitan cities and provinces from 2000 to 2018. Design/methodology/approach - We use a dynamic spatial panel model that considers characteristics of the regional unemployment rate such as the common factors effect, spatial dependence, and serial correlations. Findings - The local unemployment rate is affected by the past and present values of the national unemployment rate. And it is significantly affected by the past local unemployment rate and the past neighboring unemployment rate because spatial dependence and serial correlations are clearly present. In addition, when the industrial structure diversity and labor productivity were high, the regional unemployment rate decreased, and when the education level was high, the regional unemployment rate increased. Research implications or Originality - In order to reduce regional unemployment rate, it is necessary to plan and establish regional customized industrial structure policies under the stance of diversification rather than specializing the regional industrial structure and accompany improvement of the quality of education with the number of years of education. In addition, the redistribution of labor from low labor productivity sectors to high labor productivity sectors through technology development will help to reduce the local unemployment rate.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.11 no.1
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• pp.43-54
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• 2001

In this paper we study the use of polyinstantiation for spatial data, for the purpose of solving cover in topology channel in multilevel secure spatial database systems. Spatial database system with topological structure has a number of spatial analysis function using spatial data and neighbored one\`s each other. But. it has problems that information flow is occurred by topological relationship in spatial database systems. Geographic Information System(CIS) must be needed mandatory access control because there ,are many information flow through positioning information And topological relationship between spatial objects. Moreover, most GIS applications also graphe user interface(GUI). In addressing these problems, we design the MLS/SRDM(Multi Level Security/Spatial Relational Data Model) and propose polyinstantiation for spatial data for solving information flow that occurred by toplogical relationship of spatial data.

• Steel and Composite Structures
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• v.22 no.5
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• pp.1001-1018
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• 2016

The purpose of this paper is to compare the structural responses obtained from the stochastic analysis of a suspension bridge subjected to uniform and partially correlated seismic ground motions, using different spatial correlation functions commonly used in the earthquake engineering. The spatial correlation function employed in this study consists of a term that characterizes the loss of coherency. To account for the spatial variability of ground motions, the widely used four loss of coherency models in the literature has been taken into account in this study. Because each of these models has its own characteristics, it is intended to determine the sensitivity of a suspension bridge due to these losses of coherency models which represent the spatial variability of ground motions. Bosporus Suspension Bridge connects Europe to Asia in Istanbul is selected as a numerical example. The bridge has steel towers that are flexible, inclined hangers and a steel box-deck of 1074 m main span, with side spans of 231 and 255 m on the European and Asian sides, respectively. For the ground motion the filtered white noise model is considered and applied in the vertical direction, the intensity parameter of this model is obtained by using the S16E component of Pacoima Dam record of 1971 San Fernando earthquake. An analytically simple model called as filtered white noise ground motion model is chosen to represent the earthquake ground motion. When compared with the uniform ground motion case, the results obtained from the spatial variability models with partial correlation outline the necessity to include the spatial variability of ground motions in the stochastic dynamic analysis of suspension bridges. It is observed that while the largest response values are obtained for the model proposed by Harichandran and Vanmarcke, the model proposed by Uscinski produces the smallest responses among the considered partially correlated ground motion models. The response values obtained from the uniform ground motion case are usually smaller than those of the responses obtained from the partially correlated ground motion cases. While the response values at the flexible parts of the bridge are totally dominated by the dynamic component, the pseudo-static component also has significant contributions for the response values at the rigid parts of the bridge. The results also show the consistency of the spatial variability models, which have different characteristics, considered in this study.