• Journal of Information Processing Systems
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• v.17 no.3
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• pp.645-657
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• 2021

Along with the rapid development of the economy, the urban scale has extended rapidly, leading to the formation of different types of urban function districts (UFDs), such as central business, residential and industrial districts. Recognizing the spatial distributions of these districts is of great significance to manage the evolving role of urban planning and further help in developing reliable urban planning programs. In this paper, we propose an automatic UFD division method based on big data analysis of point of interest (POI) data. Considering that the distribution of POI data is unbalanced in a geographic space, a dichotomy-based data retrieval method was used to improve the efficiency of the data crawling process. Further, a POI spatial feature analysis method based on the mean shift algorithm is proposed, where data points with similar attributive characteristics are clustered to form the function districts. The proposed method was thoroughly tested in an actual urban case scenario and the results show its superior performance. Further, the suitability of fit to practical situations reaches 88.4%, demonstrating a reasonable UFD division result.

• Journal of the Korean Institute of Landscape Architecture
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• v.31 no.1
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• pp.54-65
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• 2003

The results of the research were as follows: The entire space of the village was based on natural formation in its initial formation stage. The traditional location conditions and environment were equipped with the possibility and conditions for the development of the village. Spatial boundaries were mostly divided by natural topography. The quantify of lots diminished in spatial structural factors, while the division of roads by hierarchy in terms of size became explicit. Alleys, as the minimum hierarchial nit, were degraded. The residence unit was focused on economic efficiency. Communal use facilities showed an external relations trend as central facilities. The land, unit residence and communal facilities approached the high hierarchial roads. The communal facilities showed relatively higher independence compared to the residence units. The spatial structural changes followed traditional life style in the initial stage of village formation; however, social elements mainly impacted on the changes. Since reform opening, economic elements were major causes of changes, while construction conditions, life style, and awareness of structures impacted upon the changes. Thus, the economic element is the major change element in the Korean Villages, even though other elements will also become diverse.

• Journal of Korean Society of Rural Planning
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• v.11 no.3 s.28
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• pp.59-67
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• 2005

According to diverse studies in population migration, there has been a strong age-dependent population distribution in Korea. It is shown that a particular age-group tends to reside in a particular locale or community and the effect possesses usually statistical significance. We quantitatively address this issue: how certain division of age group resides in different region of the country, and investigate possible cause of this migration pattern for different age groups. In this study, population migration trend at age groups of 20s, 30s, 40s and 50s has been analyzed incorporating a spatial econometrics model that accounts for diverse statistical pitfalls such as spatial autocorrelation and spatial dependency. We found that migration trend for different age group corresponds to regional characteristics differently. The study concludes with some policy implications and suggests a need of further study.

• Journal of Forest and Environmental Science
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• v.34 no.6
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• pp.419-428
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• 2018

Spatial point-patterns analyses were conducted to provide insight into the ecological process behind competition and mortality in two lodgepole pine (Pinus contorta Dougl. ex Loud. var. latifolia Engelm.) stands, one in the Lower Foothills, and the other in the Upper Foothills natural subregions in the boreal forest of Alberta, Canada. Spatial statistical tests were applied to live and dead trees and included Clark-Evans nearest neighbor statistic (R), nearest neighbor distribution function (G(r)), and a variant of Ripley's K function (L(r)). In both lodgepole pine plots, the results indicated that there was significant regularity in the spatial point-pattern of the surviving trees which indicates that competition has been a key driver of mortality and forest dynamics in these plots. Dead trees generally showed a clumping pattern in higher density patches. There were also significant bivariate relationships between live and dead trees, but the relationships differed by natural subregion. In the Lower Foothills plot there was significant attraction between live and dead tees which suggests mainly one-sided competition for light. In contrast, in the Upper Foothills plot, there was significant repulsion between live and dead trees which suggests two-sided competition for soil nutrients and soil moisture.

• Journal of Information Processing Systems
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• v.16 no.4
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• pp.750-759
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• 2020

The wide application of various integrated location-based services (LBS social) and tourism application (app) has generated a large amount of trajectory space data. The trajectory data are used to identify popular tourist attractions with high density of tourists, and they are of great significance to smart service and emergency management of scenic spots. A hot spot analysis method is proposed, based on spatial clustering of trajectory stop points. The DBSCAN algorithm is studied with fast clustering speed, noise processing and clustering of arbitrary shapes in space. The shortage of parameters is manually selected, and an improved method is proposed to adaptively determine parameters based on statistical distribution characteristics of data. DBSCAN clustering analysis and contrast experiments are carried out for three different datasets of artificial synthetic two-dimensional dataset, four-dimensional Iris real dataset and scenic track retention point. The experiment results show that the method can automatically generate reasonable clustering division, and it is superior to traditional algorithms such as DBSCAN and k-means. Finally, based on the spatial clustering results of the trajectory stay points, the Getis-Ord Gi* hotspot analysis and mapping are conducted in ArcGIS software. The hot spots of different tourist attractions are classified according to the analysis results, and the distribution of popular scenic spots is determined with the actual heat of the scenic spots.

• Nuclear Engineering and Technology
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• v.54 no.9
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• pp.3488-3493
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• 2022

Accelerator driven subcritical systems have long been discussed as facilities which can be used for solving the nuclear waste problem. The physics of these systems is very different from conventional reactors and new techniques had to be developed for reactivity monitoring. One such technique is the Area Ratio Method which studies the response of a subcritical system upon insertion of a large number of neutron pulses. An issue associated with this technique is the spatial dependence of measured reactivity which is intrinsic to the sub criticality of the system since the reactor does not operate on the fundamental mode and measured reactivity depends on the detector position. This is generally addressed by defining Bell-Glasstone spatial correction factor. This factor upon multiplication with measured reactivity gives the correct reactivity which is independent of detector location. Monte Carlo Methods are used for evaluating these factors. This paper presents a complete three dimensional map of spatial correction factors for BRAHMMA subcritical system. In addition, the dataset obtained also helps in identifying detector locations where the correction factor is close to unity, thereby implying no correction if the detector is used at those locations.

• Journal of Environmental Impact Assessment
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• v.20 no.6
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• pp.891-905
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• 2011

Climate vulnerability index is usually defined as a function of the climate exposure, sensitivity, and adaptive capacity, which requires adequate selection of proxy variables of each variable. We selected and used 9 proxy variables related to climate exposure in the literature, and diagnosed the adequacy of them for application in Korean peninsula. The selected proxy variables are: four variables from temperature, three from precipitation, one from wind speed, and one from relative humidity. We collected climate data over both previous year (1981~2010) and future climate scenario (A1B scenario of IPCC SERES) for 2020, 2050, and 2100. We introduced the spatial and temporal diagnostic statistical parameters, and evaluated both spatial and time variabilities in the relative scale. Of 9 proxy variables, effective humidity indicated the most sensitive to climate change temporally with the biggest spatial variability, implying a good proxy variable in diagnostics of climate change vulnerability in Korea. The second most sensitive variable is the frequency of strong wind speed with a decreasing trend, suggesting that it should be used carefully or may not be of broad utility as a proxy variable in Korea. The A1B scenario of future climate in 2020, 2050 and 2100 matches well with the extension of linear trend of observed variables during 1981~2010, indicating that, except for strong wind speed, the selected proxy variables can be effectively used in calculating the vulnerability index for both past and future climate over Korea. Other local variabilities for the past and future climate in association with climate exposure variables are also discussed here.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.8A
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• pp.592-599
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• 2009

In this paper, we consider multiuser multi-input/multi-output antenna systems with zero-forcing receivers in downlink. In this case, to exploit multiuser diversity, spatial-division multiple access (SDMA) system allows to assign different users to a part of transmit antennas at the base station whereas spatial-division multiplexing (SDM) system assigns all antennas to single user's data stream. In this paper, we present analytical frameworks to evaluate performance of these systems. We first analyze the performance of these two systems by deriving closed-form expressions of achievable throughput. Numerical results show that the derived expressions are very tight. In addition, we approximate the capacity expression of SDM and SDMA systems and compare the SDM with the optimal case.

• Atmosphere
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• v.23 no.4
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• pp.413-424
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• 2013

Urban Heat Island (UHI) intensity is one of vital parameters in studying urban boundary layer meteorology as well as urban planning. Because the UHI intensity is defined as air temperature difference between urban and rural sites, an objective sites selection criterion is necessary for proper quantification of the spatial variations of the UHI intensity. This study quantified the UHI intensity and its spatial pattern, and then analyzed their connections with urban structure and metabolism in Seoul metropolitan area where many kinds of land use and land cover types coexist. In this study, screen-level temperature data in non-precipitation day conditions observed from 29 automatic weather stations (AWS) in Seoul were analyzed to delineate the characteristics of UHI. For quality control of the data, gap test, limit test, and step test based on guideline of World Meteorological Organization were conducted. After classifying all stations by their own local climatological properties, UHI intensity and diurnal temperature range (DTR) are calculated, and then their seasonal patterns are discussed. Maximum UHI intensity was $4.3^{\circ}C$ in autumn and minimum was $3.6^{\circ}C$ in spring. Maximum DTR appeared in autumn as $3.8^{\circ}C$, but minimum was $2.3^{\circ}C$ in summer. UHI intensity and DTR showed large variations with different local climate zones. Despite limited information on accuracy and exposure errors of the automatic weather stations, the observed data from AWS network represented theoretical UHI intensities with difference local climate zone in Seoul.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.37 no.6
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• pp.469-477
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• 2004

This study examined distributional patterns of Asterias amurensis in Tongyeong, the central South Sea of Korea. The density of the sea star was estimated at 10 chosen sites in the inner and the outer parts of the Tongyeong coast from December 2000. The mean density of the species in this area was $2.4ind./m^{2}$. The seasonal surveys conducted at 3 arbitrary chosen sites (i.e., sea cage, reef and soft sediment) also showed that the abundance of the species at the sea cage site $(density:\;3.6\;ind./m^{2};\;biomass:\;250.7\;gwwt/m^{2})$ was significantly higher than at the reef site $(density:\;1.7\;ind./m^{2};\;biomass:\;63.5\;gwwt/m^{2})$ and the soft sediment site $(density:\;0.4\;ind./m^{2};\;biomass:\;18.9\;gwwt/m^{2})$. Densities were higher at sea cages areas than at reefs and soft bottom sites. At sea cage site, A. amurensis population exhibited a strong aggregated distributional pattern. In contrast, at reef and soft bottom sites, A. amurensis population showed a random distributional pattern. The spatial difference in prey species and its abundance was the primary factor determining the spatial heterogeneity of the sea star in its behavior characteristics. Experiments on the feeding preference indicated that A. amurensis had a strong selectivity on its prey, but this selectivity varied between populations living in different sites. In particular, A. amurensis populations at the reef site showed a strong selectivity on various sessile and mobile animals living in reef areas, suggesting that these animal groups may play a role as "windows for the survival of A. amurensis". These results suggest that the distribution of A. amurensis in Tongyeong is closely associated with abundance of prey species and the bottom composition.