• Journal of the Korean Society of Environmental Restoration Technology
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• v.25 no.1
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• pp.41-55
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• 2022

Social interest in the fine particulate matter has increased significantly since the 2010s, and various efforts have been made to reduce it through environmental plans and policies. To support such environmental planning, in this study, spatial cluster characteristics of fine particulate matter (PM2.5) concentrations were analyzed in the metropolitan area to identify high-risk areas spatially, and the correlation with local environmental characteristics was also confirmed. The PM2.5 concentration for the recent 5 years (2016-2020) was targeted, and representative spatial statistical methods Getis-Ord Gi^* and Local Moran's I were applied. As a result of the analysis, the cluster form was different in Getis-Ord Gi^* and Local Moran's I, but they show high similarity in direction, therefore complementary results could be obtained. In the high concentration period, the hotspot concentration of the Getis-Ord Gi* method increased, but in Local Moran's I, the HH region, the high concentration cluster, showed a decreasing trend. Hotspots of the Getis-Ord Gi^* technique were prominent in the Pyeongtaek-Hwaseong and Yeoju-Icheon regions, and the HH cluster of Local Moran's I was located in the southwest, and the LL cluster was located in the northeast. As in the case of the metropolitan area, in the results of Seoul, there was a phenomenon of division between the northeast and southwest regions. The PM2.5 concentration showed a high correlation with the elevation, vegetation greenness and the industrial area ratio. During the high concentration period, the relation with vegetation greenness increased, and the elevation and industrial area ratio increased in the case of the annual average. This suggests that the function of vegetation can be maximized at a high concentration period, and the influence of topography and industrial areas is large on average. This characteristic was also confirmed in the basic statistics for each major cluster. The spatial clustering characteristics of PM2.5 can be considered in the national land and environmental plan at the metropolitan level. In particular, it will be effective to utilize the clustering characteristics based on the annual average concentration, which contributes to domestic emissions.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2003.04a
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• pp.100-100
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• 2003

The purpose of this study is to reveals spatial relationships between landslides and geospatial data set, map the landslide susceptibility using the relationships and verify the landslide susceptibility using the landslide occurrence data in Bosun area in 1998. Landslide locations were detected from aerial photography and field survey and topography, soil, forest, and land use data sets were constructed as a spatial database using GIS. As the landslide occurrence factors, slope, aspect, curvature and type of topography, texture, material, drainage and effective thickness of soil, type, age, diameter and density of wood and land use were used. Is extract the relationship between landslides and geospatial database, Bayesian probability methods, likelihood ratio and weight of evidence, were applied and the ratio and contrast value that is W$\^$＋/- W$\^$-/ were calculated. The landslide susceptibility index was calculated by summation of the likelihood ratio and contrast value and the landslide susceptibility maps were generated using the index. As a result, it is expected that spatial relationships between landslides and geospatial database is helpful to explain the characteristics of landslide and the landslide susceptibility map is used to reduce associated hazards, and to plan land use and construction.

• Spatial Information Research
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• v.16 no.3
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• pp.373-383
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• 2008

LiDAR, unlike satellite imagery and aerial photographs, which provides irregularly distributed three-dimensional coordinates of ground surface, enables three-dimensional modeling. In this study, urban area was classified based on 3D information collected by LiDAR. Morphological and spatial properties are determined by the ratio of ground and non-ground point that are estimated with the number of ground reflected point data of LiDAR raw data. With this information, the residential and forest area could be classified in terms of height and density of trees. The intensity of the signal is distinguished by a statistical method, Jenk's Natural Break. Vegetative area (high or low density) and non-vegetative area (high or low density) are classified with reflective ratio of ground surface.

• Journal of Korean Society of Rural Planning
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• v.30 no.4
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• pp.73-84
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• 2024

This study aims to present a case for establishing rural spatial planning in the population sector by examining the spatial distribution changes and identifying common regional characteristics based on age-specific population structures. To achieve this, the study analyzes the population distribution of Sangju-si, focusing on the changes in total population, the proportion of the working-age population, and the proportion of the elderly population through spatial autocorrelation analysis. The results reveal that the population of Sangju-si has been declining in the northwest and west, with a noticeable concentration of population in the eastern areas. The working-age population ratio is higher in the eastern region, while the western region, despite having a small overall population, shows particularly low proportions of working-age individuals. In terms of the elderly population ratio, regions surrounding the eastern area exhibit relatively higher proportions of elderly compared to the eastern area. The western region, with its smaller population, shows a qualitatively higher proportion of elderly individuals, indicating a serious aging issue. This appears to be a result of the concentration of younger working-age populations in and around the eastern region, leading to a lower proportion of elderly in those areas. Although this analysis is limited to population structure, it reveals an imbalance in the development between the eastern and western regions of Sangju-si. To address this imbalance and foster balanced development, specific strategies such as job creation and enhanced service delivery are needed for the western region, which appears to be relatively underdeveloped.

• Journal of Korean Society of Rural Planning
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• v.9 no.3 s.20
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• pp.35-39
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• 2003

In this study, the longevity index was suggested for researches about social and environmental effects to human immorality and criteria for defining longevity area were developed using statistical analysis. Candidates indexes based on researches about the tend of human death ratio were investigated. As a result statistical analysis, ratio of population over 85 yearn old and over 65 years was selected as a longevity index. Statistical analysis on the longevity distribution at each district showed that 'eup' and 'myun' are appropriate spatial unit to study social and geographical characteristics of longevity. The spatial analysis using the $ArcView^{TM}$ with the suggested index shows the time dependent variances of degree of immorality and spatial relationship between degree of immorality and human migration.

• Journal of The Geomorphological Association of Korea
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• v.26 no.2
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• pp.1-14
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• 2019

This study analyzed the relativity between block stream and talus distributions by employing a likelihood ratio approach. Possible distribution sites for each debris slope landform were extracted by applying a spatial integration model, in which we combined fuzzy set model, Bayesian predictive model, and logistic regression model. Moreover, to verify model performance, a success rate curve was prepared by cross-validation. The results showed that elevation, slope, curvature, topographic wetness index, geology, soil drainage, and soil depth were closely related to the debris slope landform sites. In addition, all spatial integration models displayed an accuracy of over 90%. The accuracy of the distribution potential area map of the block stream was highest in the logistic regression model (93.79%). Eventually, the accuracy of the distribution potential area map of the talus was also highest in the logistic regression model (97.02%). We expect that the present results will provide essential data and propose methodologies to improve the performance of efficient and systematic micro-landform studies. Moreover, our research will potentially help to enhance field research and topographic resource management.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.6 no.2
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• pp.42-52
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• 1988

The main object of this study is to prove the effectiveness of Landsat data in detecting the stressed areas in forest by extracting these areas. And also to choose the effective bands for this type of survey and to reduce the effect of shadow in forest to improve the accuracy of classification are the other objects. In this study Landsat-5 TM data is used and image processing techniques such as spatial filtering and ratio are taken to reduce the effect of shadow and to improve the classification accuracy. As a result following conclusions are obtained. First, Landsat TM data is useful to detect the stressed areas in forest. Second, when detecting the stressed area, band 4 and 5 are the most effective. Third, spatial filtering and ratio are useful to reudce the effect of shadow and improve the classification accuracy. Especially, ratio has great effect on improving the classification accuracy between forest and other areas.

• 한국디지털정책학회:학술대회논문집
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• 2005.11a
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• pp.291-298
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• 2005

This paper is an analysis of the Category Individual Residence urban spatial structure along the National Route 20 (Koushu-Kaido), one of the major roads in Japan, and the degree of differences between locations and its changes between the points of time. The analysis was based on the GIS technique. Whilst, previous studies were based on municipal boundaries or mesh units as sources of data, GIS allowed the use of variable geographical units, Roadside zone, Inner zone, North zone, South zone, Blocks. As an example to apply the technology of GIS, 1986's sand 1991's building polygon data of the Urban Planning Bureau of Tokyo Metropolitan Government are used. The layers referred to the analyses is the building polygons with the amount of stories, building area, floor area and the material of the building. Two statistical analysis are executed; one is the test of the regional equality about the number of story of building, building area, floor area and fireproof building ratio.

• Proceedings of the Korea Water Resources Association Conference
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• 2007.05a
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• pp.178-182
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• 2007

In this study, we evaluated current raingauge network of Soyanggang dam region applying spatial-correlation analysis and Entropy theory to recommend an optimized raingauge network. In the process of analysis, correlation distance of raingauge stations is estimated and evaluated via spatial-correlation method and entropy method. From this correlation distances, respective influencing radii of each dataset and each methods is assessed. The result of correlation and entropy analysis has estimated correlation distance of 25.546km and influence radius of 7.206km, deducing a decrease of network density from $224.53km^2$ to $122.47km^2$ which satisfy the recommended minimum densities of $250km^2$ in mountainous regions(WMO, 1994) and an increase of basin coverage from 59.3% to 86.8%. As for the elevation analysis the relative evaluation ratio increased from 0.59(current) to 0.92(optimized) resulting an obvious improvement.