• Spatial Information Research
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• v.13 no.3 s.34
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• pp.253-260
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• 2005

The aim of this study is to analyze the temporal and spatial distribution aspects of red tide using GIS techniques. The damage caused by red tide appears various aspects according to the species, concentration and spatial distribution of red tide plankton. Therefore, in order to prevent the damage of red tide it is important to understand the distribution characteristics of red tide by each species according to time and space. In this perspective, we analyzed the beginning outbreak area, spatial occurrence frequency and spatial migration of red tide. The spatial data used by this study was constructed by digitizing the red tide quick report and coupled with various attributes such as species, concentration and water temperature for construction of red tide database. We used various spatial analysis methods such as union, intersect, tracking, buffer and spatial interpolation for analyzing temporal and spatial characteristics of red tide. From the result of these spatial analyses, we could get the spatial information on the temporal and spatial distribution characteristics of red tide at the Southern Sea.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.2
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• pp.295-307
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• 2021

The Korean Peninsula is surrounded on three sides by the East Sea, West Sea and South Sea which are connected to many rivers and streams, thereby facilitating easy inflow of debris from land. Furthermore, excessive debris inflow to the sea because of active fishing and various recreational activities. Debris entering the sea are weighted over time and settle in the seabed, thus, making direct monitoring of debris impossible and its collection difficult. Uncollected submerged marine debris affects the seabed ecosystem and water quality and can cause ghost fishing and ship accidents, especially due to waste net ropes and waste fishing gears. Therefore, understanding the debris distribution characteristics is necessary to assist quick collection of these debris (waste net ropes and waste fishing gears). Thus, this study conducted a survey of debris deposited in the seas of 39 ports. Furthermore, distribution characteristics and compositions of submerged marine debris were identified by a map prepared through GIS-based spatial analysis of the East Sea. Consequently, 58% of waste tires in the East Sea were concentrated in breakwaters and ship berthing facilities. Moreover, 26 % of waste plastics were distributed outside the port. Identifying the distinct distribution characteristics of submerged marine debris was difficult; however, compared with others, the distribution of waste plastics was possible outside the port. The findings of this study can serve as baseline data to assist the collection of submerged marine debris using the distribution characteristics.

• Journal of the Economic Geographical Society of Korea
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• v.16 no.1
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• pp.1-16
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• 2013

This study investigates the spatial distribution characteristics of Korean fashion industries during the last decade, in which the economic geography of fashion industries has changed dynamically with economic globalization and "thus resulted in increased" demand "of" diversification. In particular, this study examines the spatial distribution patterns of fashion industries in the Seoul metropolitan area where fashion industries are highly agglomerated. For the purpose, this study applies Moran's I Index of spatial autocorrelation analysis for seven functional sectors of fashion industries related to fashion production. The global and local agglomeration patterns are examined for each functional sector. The results clarify the distinction in the spatial agglomeration patterns among the seven functional sectors of fashion industries in the Seoul Metropolitan area. Logit models are developed to examine the interrelationships among functional sectors in their spatial agglomeration distribution patterns. By conducting binary logistic regression analysis, we find out how the spatial agglomeration of each functional sector is related to the others.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.4
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• pp.162-174
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• 2012

To visualize the characteristics of vertical seawater temperature data, in the ocean having 3D spatial characteristics, 2D thematic maps like horizontal seawater temperature distribution map at each depth layer and 3D volume model using 3D spatial interpolation are used. Although these methods are useful to understand oceanographic phenomena visually, there is a limit to analyze the spatial pattern of vertical temperature distribution or the relationship between vertical temperature characteristics and other oceanic factors (seawater chemistry, marine organism, climate change, etc). Therefore, this study aims to determine the spatial distribution characteristics of vertical temperature profiles in the South Sea of Jeju by quantifying the characteristics of vertical temperature profiles by using an algorithm that can extract the thermocline parameters, such as mixed layer depth, maximum temperature gradient and thermocline thickness. For this purpose spatial autocorrelation index (Moran's I) was calculated including mapping of spatial distribution for three parameters representing the vertical temperature profiles. Also, after grouping study area as four regions by using cluster analysis with three parameters, the characteristics of vertical temperature profiles were defined for each region.

• Journal of Digital Convergence
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• v.16 no.11
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• pp.45-55
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• 2018

The purpose of this study was to provide the necessary data to explore the development plans of consumer organizations by looking at the spatial distribution of consumer organizations. This is because community-based consumer organizations can propose concrete measures to solve consumer problems more effectively. In this study, data of 11 consumer organizations and 815 branches were collected and analyzed using local indicators of spatial distribution and spatial lag model. First, it was difficult to find patterns according to the geographical characteristics of the spatial distribution of consumer organizations. Second, consumer organizations were more distributed in areas with large populations and businesses and large areas. Third, there is a discrepancy between the demand and supply of consumer organizations when compared with the number of consumer counseling. Based on this, it is necessary to constantly seek concrete development plans by supplementing the qualitative data on the activities of consumer organizations.

• Journal of the Economic Geographical Society of Korea
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• v.14 no.1
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• pp.33-51
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• 2011

This study investigates the spatial characteristics of the provision of and demand for the private tutoring service industries and the consumer groups. For the purpose, we analyze the spatial characteristics of various types of tutoring institutes in the Seoul Metropolitan area. In particular, we exam the spatial distribution patterns of attendants of tutoring institutes by institution type as well as the resident population by attendant age group. By applying spatial autocorrelation analysis, we examine the spatial clustering patterns of tutoring institutes and attendants by type. The results show distinct differences in the spatial distribution patterns by tutoring institute type as well as by attendant age group. We found significant socio-economic variables which influence on the spatial distribution of tutoring institutes. Finally, we propose private tutoring service provision models constructed with these variables through multiple regression analysis.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.5
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• pp.539-544
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• 2016

The aim of this study is identifying characteristics of spatial distribution using submerged debris data on the bottom of sea ground. Marine debris is classified into floating and submerged debris. These are polluting marine environment, ecology and habitat by floating and submerged. Also it takes a lot of money when it is to process the waste flowing into the ocean. In this study, it is used data of submerged debris by side scan sonar on the bottom of sea ground in Pohang port. Submerged distribution map is made to identify spatial classified characteristics of SMD(submerged marine debris) using by position and weight per area of SMD.

• Spatial Information Research
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• v.14 no.2 s.37
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• pp.223-234
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• 2006

In order to examine spatio-temporal characteristics of coastal water quality, we applied GIS spatial analysis to the water quality data collected from observation points located on Korean coastal area during 1997$\sim$2004. The water quality parameters measured included: chlorophyll-a, pH, DO, COD, SS, dissolved inorganic nitrogen, dissolved inorganic phosphorous, salinity, temperature. The water quality data used in this paper was obtained only at selected sites even though they are potentially available at any location in a continuous surface. Thus, it is necessary to estimate the values at unsampled locations so as to analyze spatial distribution patterns of coastal water quality, Owing to this reason, we applied IDW(inverse distance weighted) interpolation method to water quality data and evaluated the usefulness of IDW method. After IDW interfolation method was applied, we divided the Korean coastal area into 46 sections and examined spatio-temporal patterns of each section using GIS visualization technique. As a result of evaluation, we can blow that IDW interpolation and GIS are useful for understanding spatial and temporal distribution characteristics of coastal water quality data which is collected from a wide area far many years.

• Journal of Cadastre & Land InformatiX
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• v.46 no.2
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• pp.269-281
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• 2016

The process of spatial big data, such as social media, is being paid more attention in the field of spatial information in recent years. This study, as an example of spatial big data analysis, analyzed the spatial and temporal distribution of Tweet data based on the location and time information. In addition, the characteristics of its spatial pattern by times were identified. Tweet data in Busan city are collected, processed, and analyzed to identify the characteristics of the temporal and spatial pattern. Then, the results of Tweet data analysis were compared with the characteristics of the land type. This study found that spatial pattern of tweeting in the city was associated with given time periods such as daytime and nighttime in both weekdays and weekends. The spatial distribution patterns of individual time periods were compared with the characteristics of the land for the spatially concentrated area. The results of this study showed that tweeted data would be related to different spatial distribution depending on the time, which potentially reflects the daily pattern and characteristics of the land type of urban area to some extent. This study presented the possible incorporation of social media data, e. g. Tweet data, into the field of spatial information. It is expected that there will be more advantage to use a variety of social media data in areas such as land planning and urban planning.

• Journal of the Economic Geographical Society of Korea
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• v.16 no.3
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• pp.512-527
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• 2013

This study examines the spatial distribution characteristics of financial industry which has been a necessary service for contemporary urban life. In particular, we analyze the spatial distribution patterns of money lending business which is considered with informal financial services as well as the spatial distribution patterns of banks which are representative of the institutional financial services. For the purpose, their density distribution patterns are explored by Kernel density analysis for both financial services in first. Moran's I coefficients are estimated for these two financial services to clarify the distintion in their geographical concentration patterns. The results of spatial autocorrelation analysis show stark differences between the center city and outskirts of the Seoul metropolitan area. Multivariate regression models are developed to explain the relationships between the spatial distributions of financial services and geographical variables. Finally, we discuss financial exclusion problem in the Metropolitan Seoul based on these spatial distribution characteristics.