• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.4
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• pp.112-128
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• 2014

This study aims to analyse the variation of spatial accessibility pattern based on 2SFCA(2 Step Floating Catchment Area) by changing its parameter values. The general pattern of the result of 2SFCA analysis shows that the spatial accessibility value is decreased by growing base population, while the spatial accessibility value is increased by growing PPR(Provider to Population Ratio). The three characteristics of local pattern in the Gumi City are founded by cluster analysis on the sensitive analysis procedure. Firstly, the variation of the accessibility values is insignificant in the fringe area of the Gumi City. Secondly, the variation of the accessibility values is diverse in the surrounding area of the welfare facilities. Especially, Dong areas are more sensitive to PPR variation, while others are more sensitive to base population variation. Thirdly, the larger parameter values, the more the spatial accessibility of the central areas, where elder people can access welfare facilities more easily, is improved. It needs to choose parameter values with caution to analyse spatial accessibility based on 2SFCA.

• Journal of the Korean Regional Science Association
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• v.34 no.2
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• pp.35-47
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• 2018

This research aims to examine the spatial patterns of vacant housings and the factors determining housing vacancy in Daegu using individual-level building DB. The results of the spatial pattern analysis showed a donut shaped-spatial concentration of vacant housings in the central areas of the city. The results of logistic regression analysis revealed that not only individual building characteristics, such as building area, number of floors, and building age, but also socio-economic characteristics of community, such as urban redevelopment district, number of adjacent vacancies, recent population change, and ratio of elderly, are important factors affecting housing vacancies.

• Journal of Korean Society for Geospatial Information Science
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• v.23 no.1
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• pp.39-45
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• 2015

The housing market is transformed by a variety of socio-economic characteristics, also appeared differently according to regional characteristics. This study aims to draw out the change factors influencing on the housing market structure and to analyze the drawn factors' distribution pattern by area. For this purpose, First, targeting 251 areas in the units of city, county and districts nationwide, this study drew out demographic, socio-economic variables influencing on the housing market structure for 5 years ranging 2005 to 2010. For that, the factor analysis was conducted. Second, this study grasped the change factors of the housing market structure's spatial patterns using the kriging method, a spatial statistical method. Third, this study used the Moran I, one of spatial autocorrelation analysis methods in order to grasp whether the factors had statistically significant concentration or dispersion or showed a random distribution pattern.

• Journal of Korean Society for Geospatial Information Science
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• v.17 no.3
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• pp.41-48
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• 2009

This study investigated the characteristics of spatial expansion/centralization and the spatial structural change of urban. The data used in analysis were urban population, employment, building floor area, and land price. The analysis was performed for the data of 1995, 2000, and 2005 during 10 years after 1995. The method of research was as follows; The movement of mean center and standard distance/standard deviation ellipse was estimated to investigate the urban growth change. The result of Moran's I analysis showed a clustered pattern, not a dispersed pattern, however; the effect was not significant. The town area requires the well-ordered urban planning such as land use. The contours map demonstrates that a monopole structure was generally transformed into a multicentralization structure. The development of mutural connection axis among central street roads was fragile.

• Journal of Positioning, Navigation, and Timing
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• v.4 no.2
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• pp.87-95
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• 2015

In this study, the temporal and spatial variation in precipitable water vapor (PWV) was analyzed for typhoon Ewiniar which had made landfall in the Korean peninsula in 2006. To make a contour map of PWV, zenith total delay (ZTD) was calculated using about 60 GPS permanent stations in Korea, and the pressure and temperature data of nearby AWS stations were interpolated and applied to the equation for calculating the PWV. While Typhoon Ewiniar was migrating north from the southern coast to the eastern coast of Korea, the PWV migrated showing a spatial distribution similar to that of rainfall. Also, the fluctuating pattern of the normalized PWV was analyzed, and the moving speed of the PWV was estimated using the delay time of the increase/decrease pattern in the eight-test stations. The result indicated that the moving speed of the PWV was about 35 km/h, which was similar to the average moving speed of the typhoon (38.9 km/h).

• Journal of Environmental Science International
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• v.23 no.7
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• pp.1213-1221
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• 2014

In the background of rapid urbanization and frequent earthquakes, earthquake disaster prevention planning has become an important topic of current research. Universities are irreplaceable disaster shelter, as they are public institutions with a lot of open space. This article puts forward the concept of "disaster prevention campus". With the refuge behavioral and psychological characteristics of people in the campus when the earthquake happens, it integrated uses GIS spatial analysis technique, takes Shandong Agricultural University as an example, and studies the spatial pattern of earthquake disaster prevention planning in campus from five aspects. The aspects include building distribution, population distribution, analysis of service radius, infrastructure configuration and choice of the optimal refuge path. On the basis of researches above, reform proposals and specific strategies are put forward to build the safe and harmonious disaster prevention campus.

• IE interfaces
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• v.24 no.4
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• pp.447-456
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• 2011

Identifying the major moving patterns of shoppers' movements in the selling floor has been a longstanding issue in the retailing industry. With the advent of RFID technology, it has been easier to collect the moving data for a individual shopper's movement. Most of the previous studies used the traditional clustering technique to identify the major moving pattern of customers. However, in using clustering technique, due to the spatial constraint (aisle layout or other physical obstructions in the store), standard clustering methods are not feasible for moving data like shopping path should be adjusted for the analysis in advance, which is time-consuming and causes data distortion. To alleviate this problems, we propose a new approach to spatial pattern clustering based on longest common subsequence (LCSS). Experimental results using the real data obtained from a grocery in Seoul show that the proposed method performs well in finding the hot spot and dead spot as well as in finding the major path patterns of customer movements.

• The KIPS Transactions:PartB
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• v.15B no.6
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• pp.533-542
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• 2008

Background subtraction from video data is one of the most important task in various realtime machine vision applications. In this paper, a new scheme for background subtraction based on the hexagonal pixel sampling is proposed. Generally it has been found that hexagonal spatial sampling yields smaller quantization errors and remarkably improves the understanding of connectivity. We try to apply the hexagonally sampled image to the LBP based non-parametric background subtraction algorithm. Our scheme makes it possible to omit the bilinear pixel interpolation step during the local binary pattern generation process, and, consequently, can reduce the computation time. Experimental results revealed that our approach based on hexagonal spatial sampling is very efficient and can be utilized in various background subtraction applications.

• Journal of The Geomorphological Association of Korea
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• v.23 no.2
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• pp.61-70
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• 2016

This study intended to analyze the spatial distribution of two types of weeding song (Short Bang-a and Sangsa ryu) and how geomorphic elements influence the propagation of the songs in Chungcheongbuk-do area. The distribution of the two types of song was mapped as point data. According to the result, both types showed similar distribution pattern. In order to figure out the reason of this similarity, the distribution pattern of songs was analyzed at various scales based on geomorphic elements including river, mountain and lineament. The result showed that most of distribution pattern of songs followed the lineament direction. Also, the spatial continuity among mountain that was formed by large and small lineament in various directions could be the path of the cultural diffusion. If the lineament with same direction does not intersect other lineament that have different direction, spatial continuity would be blocked. Consequently it was confirmed that propagation of songs has not spread smoothly.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.2078-2093
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• 2019

Visual smoke recognition is a challenging task due to large variations in shape, texture and color of smoke. To improve performance, we propose a novel smoke recognition method by combining dual-encoded features that are extracted from both spatial and Curvelet domains. A Curvelet transform is used to filter an image to generate fifty sub-images of Curvelet coefficients. Then we extract Local Binary Pattern (LBP) maps from these coefficient maps and aggregate histograms of these LBP maps to produce a histogram map. Afterwards, we encode the histogram map again to generate Dual-encoded Local Binary Patterns (Dual-LBP). Histograms of Dual-LBPs from Curvelet domain and Completed Local Binary Patterns (CLBP) from spatial domain are concatenated to form the feature for smoke recognition. Finally, we adopt Gaussian Kernel Optimization (GKO) algorithm to search the optimal kernel parameters of Support Vector Machine (SVM) for further improvement of classification accuracy. Experimental results demonstrate that our method can extract effective and reasonable features of smoke images, and achieve good classification accuracy.