• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.6
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• pp.141-156
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• 2023

This study aims to improve understanding of freight movement, crucial for logistics facility investment and policy making. It addresses the limitations of traditional freight truck traffic data, aggregated only at city and county levels, by developing a new methodology. This method uses trip chain data for more detailed, facility-level analysis of freight truck movements. It employs DTG (Digital Tachograph) data to identify individual truck visit locations and creates H3 system-based polygons to represent these visits spatially. The study also involves an algorithm to dynamically determine the optimal spatial resolution of these polygons. Tested nationally, the approach resulted in polygons with 81.26% spatial fit and 14.8% error rate, offering insights into freight characteristics and enabling clustering based on traffic chain characteristics of freight trucks and visited facility types.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.2
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• pp.63-70
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• 2016

A housing market in an urban area is not just a single market but a combination of regionally different submarkets. This study begins with a critical mind that previous researches did not consider the spatial autocorrelation of each area where the housings are located. The clustering analysis of housing submarket which considers spatial autocorrelation is performed as it follows. First, 4 housing market attribute variables are reducted to 1 variable by principle component analysis. Then, after calculating $Gi^*max$ by AMOEBA, 7 housing submarkets which have similar characteristics based on $Gi^*max$ are classified. The characteristics of each submarket are investigated, then political implication is deduced as the following. Different level of housing policy should be made to each cluster because each cluster has different level of spatial autocorrelation.

• Journal of the Korea Society of Computer and Information
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• v.24 no.8
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• pp.137-142
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• 2019

This paper proposed bitmap based spatial data transmission scheme in need of rapid transmission through network in mobile environment that use and creation of data are frequently happen. Former researches that used clustering algorithms, focused on providing service using spatial data can cause delay since it doesn't consider the transmission speed. This paper guaranteed rapid service for user by convert spatial data to bit, leads to more transmission of bit of MTU, the maximum transmission unit. In the experiment, we compared arithmetically default data composed of 16 byte and spatial data converted to bitmap and for simulation, we created virtual data and compared its network transmission speed and conversion time. Virtual data created as standard normal distribution and skewed distribution to compare difference of reading time. The experiment showed that converted bitmap and network transmission are 2.5 and 8 times faster for each.

• Korean Journal of Remote Sensing
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• v.27 no.3
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• pp.289-301
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• 2011

In this paper an attempt has been made to classify Asia land cover considering climatic and vegetative characteristics. The sub-class clustering based on the 13 MODIS land cover classes (except water) over Asia was performed with the climate map and the NOVI derived from SPOT 5 VGT D10 data. The unsupervised classification for the sub-class clustering was performed in each land cover class, and total 74 clusters were determined over the study area. Via these clusters, the annual variations (from 1999 to 2007) of precipitation rate and temperature were analyzed as an example by a simple linear regression model. The various annual variations (negative or positive pattern) were represented for each cluster because of the various climate zones and NOVI annual cycles. Therefore, the detailed land cover map as the classification result by the sub-class clustering in this study can be useful information in modelling works for requiring the detailed climatic and vegetative information as a boundary condition.

• Journal of the Korean institute of surface engineering
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• v.55 no.3
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• pp.164-172
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• 2022

Hot-dip galvanized steel(GI) is widely used throughout the industry as a corrosion resistance material. Corrosion of steel is a common phenomenon that results in the gradual degradation under various environmental conditions. Corrosion monitoring is to track the degradation progress for a long time. Corrosion on steel plate appears as discoloration and any irregularities on the surface. This study developed a quantitative evaluation method of the rust formed on GI steel plate using a superpixel-based DBSCAN clustering method and k-means clustering from the corroded area in a given image. The superpixel-based DBSCAN clustering method decrease computational costs, reaching automatic segmentation. The image color of the rusty surface was analyzed quantitatively based on HSV(Hue, Saturation, Value) color space. In addition, two segmentation methods are compared for the particular spatial region using their histograms.

• Journal of the Economic Geographical Society of Korea
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• v.8 no.1
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• pp.107-130
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• 2005

The purpose of this study were to examine the spatial distribution and locational characteristics of the Internet movie industry, to seize the value chains of the Internet movie industry and distribution structure of the internet movies, and to analyze the vertical-horizontal linkages of the Internet movie firms and their spatial clustering. Recently, the Internet movie industry has developed rapidly due to the development of techniques related to movie contents, the broadband Internet and a wide expansion of the high speed communication network and the increase of demands on movie contents. It has been found that 74$\%$ of the Internet movie industry was concentrated in Seoul. Especially this industry was quite agglomerated in several dongs of Gangnam-gu such as Yoeksam, Nonhyeon, Daechi and Samseung. The proximity of the same or similar business firms was the primary locational factors that influenced on the Internet movie industry, followed by other factors such as convenience of transportation, the reputation of the place, and proximity of technically supporting firms. The Internet movie industry had the valve chain composed of 'contents suppliers $\rightarrow$ contents distributors $\rightarrow$ service providers', However, there were also a complex network of the VOD copyright owner, VOD syndicator, and service providers in each category of the value chain. This research clearly revealed that the localized clustering has been formed with the movie contents providers, technically supporting firms, client firms, and cooperative-affiliated business firms related to the Internet movie industry, Additionally, a very intimate network has been established within the clustering, inducing the enlargement of the market and decrease of costs, the co-sharing of tacit knowledge, and the synergy effect.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.8
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• pp.1155-1160
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• 2013

The rapid growth of smart phones has made location-based services (LBSs) widely available. However, the use of LBS can raise privacy issues, as LBS can allow adversaries to violate the location privacy of users. There has been a considerable amount of research on preserving user location privacy. Most of these studies try to preserve location privacy by achieving what is known as location K-anonymity. In this paper, we propose a hierarchical clustering-based spatial cloaking algorithm for LBSs. The proposed algorithm constructs a tree using a modified version of agglomerative hierarchical clustering. The experimental results show, in terms of the ASR size, that the proposed algorithm is better than Hilbert Cloak and comparable to RC-AR (R-tree Cloak implementation of Reciprocal with an Asymmetric R-tree split). In terms of the ASR generation time, the proposed algorithm is much better in its performance than RC-AR and similar in performance to Hilbert Cloak.

• Journal of the Korean Data and Information Science Society
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• v.27 no.5
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• pp.1193-1201
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• 2016

In epidemiology or etiology, we are often interested in identifying areas of elevated risk, so called, hot spot or cluster. Many existing clustering methods only tend to a result if there exists any clustering pattern in study area. Recently, however, lots of newly introduced clustering methods can identify the location, size, and shape of clusters and test if the clusters are statistically significant as well. In this paper, one of most commonly used clustering methods, scan statistic, and its implementation SaTScan software, which is freely available, will be introduced. To exemplify the usage of SaTScan software, we used cancer data from the SEER program of National Cancer Institute of U.S.A.We aimed to help researchers and practitioners, who are interested in spatial cluster detection, using female lung cancer mortality data of the SEER program.

• 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.

• Journal of Korea Multimedia Society
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• v.4 no.3
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• pp.197-204
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• 2001

In order to increase the performance of spatial database systems, a spatial indexing method is necessary to manage spatial objects efficiently in both dynamic and static environments. A spatial indexing method considering a spatial locality is required to increase the retrieval performance. And the spatial locality is related to the location property of objects. The previous spatial indexing methods did not consider the circular location property of objects. In this paper, we introduce the CR-Tree that is a spatial index structure for clustering spatially adjacent objects in which a search space is constructed with the circular and linear domains. Using a spatial index structure considered a circular location property of objects, we show that high hit ratio and bucket utilization are increased through the simulation.