• Journal of Environmental Impact Assessment
• /
• v.28 no.4
• /
• pp.373-386
• /
• 2019

In The study, is to investigate the spatial characteristics of the Miho stream, which is the main tributary of the Geum River system, and to identify the main factors influencing the water quality using water quality analysis and multivariate analysis. The survey subjects were selected as 7 main sites in the Miho stream water system, From 2012 to 2017, 16 items including weather temperature and weather data were used for multivariate analysis. As a result of the water quality analysis, the average concentration of BOD and COD for 6 years was 3grade (normal) compared with the water quality environmental standard (river) of conditions. The concentrations of nitrogen and phosphorus were highest at th upstream site, then decreased and then increased again by the hydrogeological and geomorphological effect. Cluster analysis of spatial and water quality characteristics, it was evaluated as three clusters and the pollution sources is the greatest impact. As a result of principal component analysis and factor analysis on each cluster and mainstream, three to four major components were extracted. Main stream and the Cluster 1, Cluster 3 first principal factor included nitrogen and seasonal factors,first factor of Cluster 2 included nitrogen and water temperature. Nitrogen is the principal factor which affects water quality in Miho stream.

• Journal of Korean Society of Rural Planning
• /
• v.21 no.4
• /
• pp.35-43
• /
• 2015

The purpose of the research is to analyze damages of TYLCV (Tomato Yellow Leaf Curl Virus) in the context of climate changes and to find the spatial distribution of the damages and characteristics of regions. A TYLCV is generally known for a plant disease related to temperature. Its occurrence rate increases when temperature rises. This disease first occurred in 2008 and rapidly spread nationwide. Due to the spread of a TYLCV, a number of Tomato farms in Korea were damaged severely. To analyze damages of the pest in the context of climate changes, this research estimated production loss under the current situation and RCP scenarios. Additionally, Hot Spot Analysis, LISA, and Cluster analysis were conducted to find spatial distribution and properties of largely damaged regions under RCP scenarios. The results explained that additional production loss was estimated differently by regions with the same temperature rising scenario. Also, largely damaged regions are spatially clustered and factors causing large damages were different across regional cluster groups. It means that certain regions can be damaged more than others by diseases and pests. Furthermore, pest management policy should reflect the properties of each region such as climate conditions, cultivate environment and production technologies. The findings from this research can be utilized for developing rural management plans and pest protection policies.

• Architectural research
• /
• v.13 no.3
• /
• pp.3-10
• /
• 2011

The Characteristics of space are determined by several factors; however, the element that determines the physical characteristic of floors, walls, and ceiling is the structure. This study constructs a wall to analyze the direct effect that the layout of an exhibition wall has on the element of the wall followed by the structural process and visibility of descriptive analysis and examples of art museums that the shift from a perceptional wall to an experiential wall affected circulation. For elements and formation methods of the wall, first, it is made up of open and closed type exhibition spaces, and it can give abundance in qualitative space rather than a quantitative aspect. Secondly, the directivity of space changes according to the development of the visible axis, thus, directly affects the change in visibility. Thirdly, the difference between spatial structure and visual structure is the difference between the visual axis and spatial structure. The wall formation type followed by the combination method, the simple visible structure, which is the type that possesses the simple combination (Room, Zone, Cluster), repeatedly uses the same size of units of space that is orderly and has few spatial axes and the classification of simple type and simple cluster type, which has few visible axes, also exists. Also, with the complex structure of the maze type it displays the reiterated form of the cluster, which is the space with disorderly combination and has much visible axes and spatial axes. Also, these can be divided into three types: 1) Maze Cluster Type, 2) Cross Road Type, and 3) Open Flexible Type. These wall types lead the various changes in circulation, and even each of the arrangement qualities of the exhibitions should be researched according to its exhibition place type.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
• /
• 2003.11a
• /
• pp.9-14
• /
• 2003

The major reason that spatial data warehousing has attracted a great deal of attention in business GIS in recent years is due to the wide availability of huge amounts of spatial data and the imminent need for turning such data into useful geographic information. Therefore, this research has been focused on designing and implementing the pilot tested system for spatial decision making. The purpose of the system is to predict targeted marketing area by discriminating the customers by using both transaction quantity and the number of customer using credit card in department store. Focused on the analysis methodology, the case study is aiming to use GIS and clustering for knowledge discovery. The system is a key section of the research of multi-dimensional and spatio-temporal analysis in the internet environment.

• Journal of Korean Society of Rural Planning
• /
• v.25 no.3
• /
• pp.1-9
• /
• 2019

Population is important as a fundamental element of local industry and economy, and census data is essential to regional planning and policy making. Although there have been many researches on population and regional planning, there are few studies on population considering spatial unit. In this study, the population of three spatial scales were compared in order to establish the spatial unit suitable for the rural planning. The study area is Gangwon, Chungcheong-Nam, Chungcheong-Buk, Jeolla-Nam, Jeolla-Buk, Gyeonsang-Nam, Gyeonsang-Buk and Jeju province. Population were compared using statistical data analysis, GIS visualization, and spatial statistics. The mean, maximum, minimum, and variance of population were calculated and the coefficient of variation according to spatial unit was compared. The mean, maximum, minimum, and variance of population were calculated and the coefficient of variation according to spatial unit was compared. As the results, the census output area unit is difficult to interpret spatial analysis results. Administrative district unit has the limit that includes areas where the population does not live. The grid unit is well suited to the geographical characteristics but has many disadvantages of the grid with small population. Therefore, It is necessary to complement the limits of the Eup and Myeon-dong administrative district through the grid unit data.

• World Technopolis Review
• /
• v.6 no.2
• /
• pp.130-147
• /
• 2017

This paper aims to identify the spatial concentrations and linkage properties of industrial clusters in the Chungbuk Province region in Korea using a three-step approach, which is composed of the cluster index, Getis-Ord's $Gi^*$, and qualitative input-output analysis. The results of the study reveal: a) what industrial sectors are concentrated and where they are; b) where the spatially interdependent industries are; and c) how the industrial sectors of the identified clusters in different locations are vertically interconnected. In addition, the degree of strength of the interindustry linkages between industrial clusters are assessed. Based on the findings, some plausible industrial policies are suggested.

• Spatial Information Research
• /
• v.20 no.4
• /
• pp.17-27
• /
• 2012

This study was performed to evaluate the spatial distribution of heavy metals using principal component analysis and Ordinary Kriging technique in the Gangwon Mine site. In the soils from the sub soil, the contents of Zn and Ni in the PC1 were gradually dispersed from south to north direction, while the components of Cd and Hg in the PC2 showed an increase significantly from middle-south area in the Gangwon Mine site. According to the cluster analysis, pollutant metals of As and Cu were presented a strong spatial autocorrelation structure in cluster D. The concentration of As was 0.83mg/kg and shown to increase from the south to north direction. The spatial distribution maps of the soil components using geostatistical method might be important in future soil remediation studies and help decision-makers assess the potential health risk affects of the abandoned mining sites.

• Journal of Environmental Science International
• /
• v.11 no.12
• /
• pp.1281-1289
• /
• 2002

This study was conducted to evaluate water quality in the Keum River using multivariate analysis. The analysis data in Keum river made use of surveyed data by the ministry of environment from January 1994 to December 2001. Thirteen water quality parameter were determined on each sample. The results was summarized as follow; Water quality in the Keum River could be explained up to 71.39% by four factors which were included in loading of organic matter and nutrients by the tributaries (32.88%), seasonal variation (16.09%), loading of pathogenic bacteria by domestic sewage of Gapcheon (13.39%) and internal metabolism in estuary as lakes(9.03%). For spatial variation of factor score, four group was classified by each factor characterization. Station 1 and 2 was influenced by Daechung dam, station 3 was affected by domestic sewage of Gapcheon, station 10~12 was affected by estuary dyke and the rest station. The result of cluster analysis by station was classified into four group that has different water quality characteristics. In monthly cluster analysis, three group was classified according to seasonal characteristic. Also, in yearly cluster analysis, three group was classified. It is necessary to control the pollutant loadings by Gapcheon inflow domestic sewage in Daejeon city for the sake of water quality management of Keum river.

• Journal of Korean Society for Geospatial Information Science
• /
• v.25 no.1
• /
• pp.29-36
• /
• 2017

In this paper, we implement a spatial big data analysis prototype based on Spark which is an in-memory system and compares the performance by the spatial split algorithm on this basis. In cluster computing environments, big data is divided into blocks of a certain size order to balance the computing load of big data. Existing research showed that in the case of the Hadoop based spatial big data system, the split method by spatial is more effective than the general sequential split method. Hadoop based spatial data system stores raw data as it is in spatial-divided blocks. However, in the proposed Spark-based spatial analysis system, there is a difference that spatial data is converted into a memory data structure and stored in a spatial block for search efficiency. Therefore, in this paper, we propose an in-memory spatial big data prototype and a spatial split block storage method. Also, we compare the performance of existing spatial split algorithms in the proposed prototype. We presented an appropriate spatial split strategy with the Spark based big data system. In the experiment, we compared the query execution time of the spatial split algorithm, and confirmed that the BSP algorithm shows the best performance.

• Journal of Korean Society of Rural Planning
• /
• v.26 no.1
• /
• pp.101-112
• /
• 2020

Recently, public awareness regarding mountain villages' landscapes is increasing. Thus, this study aimed to provide standards for conservation, management and creation of mountain village landscape by characterizing and classifying those exist. 286 mountain villages' data were collected and 19 variables - extracted from GIS spatial information and statistic data of mountain villages, chosen as right sources according to former studies - were utilized to conduct factor and cluster analysis. As a result of the factor analysis, 7 characteristics of the mountain villages' landscapes were defined - 'Location', 'Cultivation', 'Ecology·Nature', 'Tourism', 'Residence', 'Recreation'. The K-means cluster analysis categorized the mountain villages' landscapes into four types - 'Residential', 'Touristic', 'General', 'Environmentally protected'. The classification was examined to be appropriate by field assessment, and basic guidelines of mountain village landscape management were set. The results of this study are expected to be utilized planning and implementing regarding mountain village landscape in the future.