A multistage hierarchical clustering technique, which is an unsupervised technique, was suggested in this paper for classifying large remotely-sensed imagery. The multistage algorithm consists of two stages. The 'local' segmentor of the first stage performs region-growing segmentation by employing the hierarchical clustering procedure of CN-chain with the restriction that pixels in a cluster must be spatially contiguous. The 'global' segmentor of the second stage, which has not spatial constraints for merging, clusters the segments resulting from the previous stage, using the conventional agglomerative approach. Using simulation data, the proposed method was compared with another hierarchical clustering technique based on 'mutual closest neighbor.' The experimental results show that the new approach proposed in this study considerably increases in computational efficiency for larger images with a low number of bands. The technique was then applied to classify the land-cover types using the remotely-sensed data acquired from the Korean peninsula.
Journal of the Korean Association of Geographic Information Studies
/
v.25
no.2
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pp.30-47
/
2022
This study analyzed the characteristics of cold air flow according to spatial types in urban areas of Changwon-si, Gyeongsangnam-do. The spatial types were classified by cluster analysis considering the land use map, building information, and topographic characteristics produced on the Changwon biotope map. The amount of cold air and wind speed were derived by KLAM_21 modeling. As a result, spatial types were classified into a total of 14 types considering the density and height of buildings, land use types, and topographic characteristics. Cold air flow was found to generate cold air in the valley of the forest area outside urban area, move through roads and open spaces, and accumulate in the low-lying national industrial complex, and then spread cold air throughout the urban areas. There was a lot of cold air flow in the tall building area, and the cold air accumulation was less in the slope and ridge areas. The results of this study were able to understand the characteristics of cold air flow according to building density, land use type, and topography, which will be usefully used as basic data for urban wind road construction to mitigate climate and improve air quality in urban areas.
Around Tongyeong coasts which located in southern coast of Korea composed to the complex coastal line and scattered by small islands. It also has been distributed to a complicated bathymetric structure by several types of channels. This study carried to analyze the spatial characteristics of macrobenthic community and benthic environmental variance on sub-tidal area based on multivariate statistics tools. Sediment composition varied from muddy sand to mud, and along the channels, it composed to a heterogeneous bottoms mixed by shell fragment, cobbles and mud. Organic contents on the surface sediment varied 1.1-3.9%. Total of 272 species, $33,349\;ind./m^2$ of macrobenthos identified in all of sample area. Polychaetes also prevailed among the specimen. L. longifolia, P. pinnata dominated based on density. Considering on the biomass, echinoderm S. lacunosa, A. tricoides listed. Closer to the coastal area, the density and diversity were higher. Community structure based on cluster analysis was discriminated into three groups. Each group was also characterized by geographical state such as depth, sediment composition. In addition, when applied to the bathymetric data, the channel, which composed to the mixed sediment, made a role of limited factor which characterized to benthic community. Because the specimen around the channel have been affected on the diverse sediment mixture. Most of benthic studies in the southern coast of Korea focused to the condition of benthic organic pollution spatially, because along the coast, it also developed a aquaculture ground and industrial complex. But, as results, most of the area, it turn out the less polluted areas nevertheless similar environment situation. It supposed that benthic community affect to the bottom sediment composition by physical characteristics.
Classification of spatial units into meaningful sets is an important procedure in spatial analysis. It is crucial in characterizing and identifying spatial structures. But traditional classification methods such as cluster analysis require an exact database and impose a clear-cut boundary between classes. Scrutiny of realistic classification problems, however, reveals that available infermation may be vague and that the boundary may be ambiguous. The weakness of conventional methods is that they fail to capture the fuzzy data and the transition between classes. Fuzzy subsets theory is useful for solving these problems. This paper aims to come to the understanding of theoretical foundations of fuzzy spatial analysis, and to find the characteristics of fuzzy classification methods. It attempts to do so through the literature review and the case study of urban classification of the Cities and Eups of Kyung-Nam Province. The main findings are summarized as follows: 1. Following Dubois and Prade, fuzzy information has an imprecise and/or uncertain evaluation. In geography, fuzzy informations about spatial organization, geographical space perception and human behavior are frequent. But the researcher limits his work to numerical data processing and he does not consider spatial fringe. Fuzzy spatial analysis makes it possible to include the interface of groups in classification. 2. Fuzzy numerical taxonomic method is settled by Deloche, Tranquis, Ponsard and Leung. Depending on the data and the method employed, groups derived may be mutually exclusive or they may overlap to a certain degree. Classification pattern can be derived for each degree of similarity/distance $\alpha$. By takina the values of $\alpha$ in ascending or descending order, the hierarchical classification is obtained. 3. Kyung-Nam Cities and Eups were classified by fuzzy discrete classification, fuzzy conjoint classification and cluster analysis according to the ratio of number of persons employed in industries. As a result, they were divided into several groups which had homogeneous characteristies. Fuzzy discrete classification and cluste-analysis give clear-cut boundary, but fuzzy conjoint classification delimit the edges and cores of urban classification. 4. The results of different methods are varied. But each method contributes to the revealing the transparence of spatial structure. Through the result of three kinds of classification, Chung-mu city which has special characteristics and the group of Industrial cities composed by Changwon, Ulsan, Masan, Chinhai, Kimhai, Yangsan, Ungsang, Changsungpo and Shinhyun are evident in common. Even though the appraisal of the fuzzy classification methods, this framework appears to be more realistic and flexible in preserving information pertinent to urban classification.
The Journal of The Korea Institute of Intelligent Transport Systems
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v.14
no.2
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pp.39-53
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2015
The paper analyzes factors to affect pedestrian volumes by land-use type using 2012 Seoul Pedestrian Survey. First of all, five groups were classified based on land-use types around survey points such as residential, commercial, industrial and green uses, using k-average cluster analysis. Then, differences in average pedestrian volumes by group were compared for a day and time of day. In addition, multiple regression analysis was employed to identify factors to affect pedestrian volumes, considering physical features, land use types, public transportation accessibility, and socio-economic indices as independent variables by spatial hierarchy. Model results show that the walkway width positively influenced on pedestrian volumes for all groups, whereas other variables differently affected by group. Our results can be used as basic data for establishing polices with respect to pedestrian road design and improvement as well as estimating pedestrian demand by land-use type.
Journal of the Economic Geographical Society of Korea
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v.16
no.2
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pp.233-246
/
2013
This paper investigates both the spatial patterns of aging population and its formal regional structure in 2010. The results are as follows: first, aging index shows high values in remote mountainous and coastal regions while showing relatively low values in Capital Region and large provincial cities. Aging index has low negative correlation with such variables as population increasing rate, ratio of youth population, ratio of apartments, and ratio of newly built housing. However, aging index shows high positive correlation with variables including ratio of single unit house, ratio of aged peoples' house ownerships, ratio of welfare recipients, ratio of old housing, and number of public healthcare facilities. Secondly, four factors are identified from factor analysis including aging factor, welfare factor, economic vitality factor, and new town factor. The aging level of a region is negatively related to the strong level of those factors. Thirdly, cluster analysis results in four different types of formal regions including rural mountainous coastal type, rural non-capital region type, large metropolitan type, and provincial industrial city type.
Visible Infrared Imaging Radiometer Suite Day-Night Band (VIIRS-DNB) data provides a much higher capability for observing and quantifying nighttime light (NTL) brightness in comparison with Defense Meteorological Satellite-Operational Linescan System (DMSP-OLS) data. In South Korea, there is little research on the detection of NTL brightness change using VIIRS-DNB data. This study analyzed the spatial distribution and change of NTL brightness between 2013 and 2016 using VIIRS-DNB data, and detected its spatial relation with possible influencing factors using regression models. The intra-year seasonality of NTL brightness in 2016 was also studied by analyzing the deviation and change clusters, as well as the influencing factors. Results are as follows: 1) The higher value of NTL brightness in 2013 and 2016 is concentrated in Seoul and its surrounding cities, which positively correlated with population density and residential areas, economic land use, and other factors; 2) There is a decreasing trend of NTL brightness from 2013 to 2016, which is obvious in Seoul, with the change of population density and area of industrial buildings as the main influencing factors; 3) Areas in Seoul, and some surrounding areas have high deviation of the intra-year NTL brightness, and 71% of the total areas have their highest NTL brightness in January, February, October, November and December; and 4) Change of NTL brightness between summer and winter demonstrated a significantly positive relation with snow cover area change, and a slightly and significantly negative relation with albedo change.
Journal of the Korean association of regional geographers
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v.19
no.1
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pp.45-59
/
2013
This paper was to examine the spatial characteristics on the mobile industry's value chain based on the structure of value chain, the process of development, and the industrial linkages of mobile industry in Daegu-Gyeongbuk region. The mobile industry's value chain in Daegu-Gyeongbuk region consists of the infrastructure, mobile device, platform & embedded SW, and mobile contents sector. Among these sectors, the leading value chain sector in mobile governance is the mobile device sectors, especially the finished products sector. These sectors have developed by policies as well as networks with large enterprises such as Samsung and LG, and it forms a hub-and-spoke cluster. The infrastructure and mobile device sector are located in Gumi, Gyeongbuk, the embedded SW and mobile contents sectors are located in Daegu, which means decentralized agglomeration. The sectors of infrastructure and mobile device form the strong forward-backward linkages with firms in Daegu-Gyeongbuk region. For the embedded SW sector, the forward-backward linkages are active with firms located in Seoul metropolitan area. For mobile contents sector, the backward linkages are formed with firms in Daegu and the forward linkages are formed with firms in Seoul metropolitan area.
Journal of the Korea Academia-Industrial cooperation Society
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v.14
no.1
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pp.464-469
/
2013
After city of Busan has been entered to the aging society in 2000, the city has the highest aging rate among 7 representative cities in 2011. Moreover, while entire population and number of average household are decreasing, over 65 years old of elderly population is rapidly increasing. So, it is possible to enter the super-aged society, where aging rate would be about 20% after 2020. The purpose of this study is that older housing-related analysis is consisted of dong-unit, and this led microscopic analysis has become necessary. Surveys from 2000 through 2010, census aggregate (output area) unit of spatial analysis was conducted. Take advantages of this, aging population and area, soaring area, high-density areas, such as the region of interest were primary extracted, and microscopic location and spatial distribution patterns were analyzed. Upon analysis, aging population is concentrated in the city and adjacent area, the highlands, and 10 years of increasing rate was more than 30 times in certain aggregate. Regarding the characteristic of these areas, the original city center, Busan, especially concentrated and intensified in aging population. Also, 2000 to 2010, the overall distribution pattern of Busan has identified aging population that is increasingly being distributed. This is the result, which is confronted with previous research result. Entering a super aged-society for the future is accordance with migration of social costs and improve the quality of life of elderly. And this could be the basic information to use the spatial dimension for the corresponding.
Journal of the Korean Association of Geographic Information Studies
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v.24
no.3
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pp.58-72
/
2021
In July 2021, UNCTAD classified Korea as a developed country. After the Korean War in the 1950s, economic development was promoted despite difficult conditions, resulting in epoch-making national growth. However, in order to respond to the rapidly changing global economy, it is necessary to continuously study the domestic industrial ecosystem and prepare strategies for continuous change and growth. This study analyzed the industrial ecosystem of the automobile industry where it is possible to obtain transaction data between companies by applying complexity spatial network analysis. For data, 295 corporate data(node data) and 607 transaction data (link data) were used. As a result of checking the spatial distribution by geocoding the address of the company, the automobile industry-related companies were concentrated in the Seoul metropolitan area and the Southeastern(Dongnam) region. The node importance was measured through degree centrality, betweenness centrality, closeness centrality, and eigenvector centrality, and the network structure was confirmed by identifying density, distance, community detection, and assortativity and disassortivity. As a result, among the automakers, Hyundai Motor, Kia Motors, and GM Korea were included in the top 15 in 4 indicators of node centrality. In terms of company location, companies located in the Seoul metropolitan area were included in the top 15. In terms of company size, most of the large companies with more than 1,000 employees were included in the top 15 for degree centrality and betweenness centrality. Regarding closeness centrality and eigenvector centrality, most of the companies with 500 or less employees were included in the top 15, except for automakers. In the structure of the network, the density was 0.01390522 and the average distance was 3.422481. As a result of community detection using the fast greedy algorithm, 11 communities were finally derived.
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