• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.887-890
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• 2007

For a integrated system to control several parking lots within a commercial district, it is required to guide a route to a nearest neighbor parking lot considering diverse realtime constraints such as realtime status of parking lots and changes of an access route. This paper proposes an optimized route-searching technique of integrated parking control system considering realtime contraints. In concrete, it proposes a method of researching a route in the surrounding area considering various status of parking lots that a customer designates (no parking, closed, under construction, no passing of a road) and deals with a route-searching technique optimized for each situation in detail.

• Journal of the Korean Association of Geographic Information Studies
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• v.10 no.2
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• pp.103-111
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• 2007

Since the 1980's the school of Busan metropolitan city has been converted into the other land-use such as high-rise apartment houses, commercial and office buildings. School facilities are available to locate in green area due to not restricted by land use zone. And the location of school facilities were closely related with the school district, distribution of neighborhood unit, safety of students, and so on. The purpose of this study is to understand the location characteristic of school - moved sites in Busan metropolitan city.

• Journal of the Economic Geographical Society of Korea
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• v.23 no.4
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• pp.408-424
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• 2020

This study attempts to analyze the spatial clustering of survived and closed coffee shops based on the land price and land use for each coffee shop location. The locational characteristics of survived and closed coffee shops for each cluster type are identified through various locational properties such as transport factors (physical accessibility), shop properties (franchise information, newly open/closed business experience), and spatial density (kernel density estimation). To this end, we categorize the clusters of survived and closed coffee shops into three types (general locational distribution type, commercialization type of residential area and location type of commercial center), and then analyze their locational characteristics. As the result, we found that the locations of newly open and closed coffee shops show different distribution characteristics, even though they are classified into the same type due to the double sidedness of new open and closed locations. The results of this study can be provided as basic data for planning the location of coffee shop as well as regional commercial district.

• The Journal of Industrial Distribution & Business
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• v.7 no.3
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• pp.5-12
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• 2016

Purpose - In this paper, we consider more segmented types of markets than conventional version of ones in South Korea and explore the degree of relations between these markets and the related factors with them. In this case, ten attributes of types of markets mentioned above will be considered. To be more specific, the numerical strength is evaluated and graphical approach is expressed on two-dimensional plane, if the association exists between the considered variables. Research design, data, and methodology - This work is done by the 2013 report on the commercial building lease offered by Small Businessmen Promotion Institute (May/2013~August/2013) and exploited by statistical analyses such as correspondence analysis and a chi-squared test in IBM SPSS 23.0. Results - Findings of this paper indicate that a variable Korean market, including traditional markets, are closely connected with variables administrative district, sales and occupation instead of company, age group and business duration and the detailed associations between variables can be obtained by inspecting results of correspondence analysis. Conclusions - We can understand where the status of the Korean markets stands now through this work and also government authority and local autonomy can take advantage of these findings to enhance the revitalization of Korean markets and other markets.

• Journal of the Korean Institute of Landscape Architecture
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• v.46 no.1
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• pp.115-126
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• 2018

A new urban paradigm that moves from a vehicle-centric to pedestrian-centric culture should be considered to improve the quality of the pedestrian environments for women, children, senior citizens, and disabled persons as well as to promote community unification by providing general movement rights to everyone. This study was implemented to provide decent alternatives to improve street spaces. The street spaces around the Commercial and Residential Area No.1 located in the Administrative-Centered City, Sejong Special Autonomic City, were selected to analyze and define the status of the walkways and the street spaces. Satellite imagery and numerical maps were used to collect geographic data. Practical and actual surveys for the selected sites were performed to analyze the street status and the pedestrian status. Based on the all collected data, analysis results, and literature reviews, the questionnaire was made, and 315 inquiries qualified for analysis. The physical status of all four study sites was the highest level, Grade A, and green open spaces were relatively sufficient. As a result, the factors obtained from the factor analysis have an impact on the satisfaction of the pedestrian streets in the commercial area. The factors are as followed Design > Convenience > Roadside trees and rest areas > Safety > Safety protective facilities > Transportation and information facilities > Continuity > Basic state of road surfaces > Comfortability, and in the residential area: Transportation and information facilities > Basic state of road surfaces > Comfort > Convenience > Continuity > Design > Illumination and crime prevention facilities > Safety > Roadside trees and rest areas.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.4
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• pp.78-89
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• 2012

The purpose of this study is to examine the possibility of crime prevention in consideration of urban physical environment by analyzing the spatial distribution characteristics and pattern using actual crime occurrence data of the case city. The crime data was rebuilt by transforming them into geographic information system to analyze the spatial aspect of crime occurrence. The findings are as follows: a change from 2008 to 2011 is indicated with similar trend. But the local movements of crime hot spots are found. Moreover crimes were happening along the roads in linear pattern rather than inside of blocks in commercial area. This indicates the importance of environmental improvement of roads and open spaces. In addition it was found that the crime occurrence in a dangerous district can be reduced and prevented through the physical environment design and urban planning. The findings will contribute to promoting fundamental crime prevention as the physical environmental improvement in a city and to building a safe community as its result.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.25-52
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• 2018

This study performs social network analysis based on consumer sentiment related to a location in Seoul using data reflecting consumers' web search activities and emotional evaluations associated with commerce. The study focuses on large commercial districts in Seoul. In addition, to consider their various aspects, social network indexes were combined with the trading area's public data to verify factors affecting the area's sales. According to R square's change, We can see that the model has a little high R square value even though it includes only the district's public data represented by static data. However, the present study confirmed that the R square of the model combined with the network index derived from the social network analysis was even improved much more. A regression analysis of the trading area's public data showed that the five factors of 'number of market district,' 'residential area per person,' 'satisfaction of residential environment,' 'rate of change of trade,' and 'survival rate over 3 years' among twenty two variables. The study confirmed a significant influence on the sales of the trading area. According to the results, 'residential area per person' has the highest standardized beta value. Therefore, 'residential area per person' has the strongest influence on commercial sales. In addition, 'residential area per person,' 'number of market district,' and 'survival rate over 3 years' were found to have positive effects on the sales of all trading area. Thus, as the number of market districts in the trading area increases, residential area per person increases, and as the survival rate over 3 years of each store in the trading area increases, sales increase. On the other hand, 'satisfaction of residential environment' and 'rate of change of trade' were found to have a negative effect on sales. In the case of 'satisfaction of residential environment,' sales increase when the satisfaction level is low. Therefore, as consumer dissatisfaction with the residential environment increases, sales increase. The 'rate of change of trade' shows that sales increase with the decreasing acceleration of transaction frequency. According to the social network analysis, of the 25 regional trading areas in Seoul, Yangcheon-gu has the highest degree of connection. In other words, it has common sentiments with many other trading areas. On the other hand, Nowon-gu and Jungrang-gu have the lowest degree of connection. In other words, they have relatively distinct sentiments from other trading areas. The social network indexes used in the combination model are 'density of ego network,' 'degree centrality,' 'closeness centrality,' 'betweenness centrality,' and 'eigenvector centrality.' The combined model analysis confirmed that the degree centrality and eigenvector centrality of the social network index have a significant influence on sales and the highest influence in the model. 'Degree centrality' has a negative effect on the sales of the districts. This implies that sales decrease when holding various sentiments of other trading area, which conflicts with general social myths. However, this result can be interpreted to mean that if a trading area has low 'degree centrality,' it delivers unique and special sentiments to consumers. The findings of this study can also be interpreted to mean that sales can be increased if the trading area increases consumer recognition by forming a unique sentiment and city atmosphere that distinguish it from other trading areas. On the other hand, 'eigenvector centrality' has the greatest effect on sales in the combined model. In addition, the results confirmed a positive effect on sales. This finding shows that sales increase when a trading area is connected to others with stronger centrality than when it has common sentiments with others. This study can be used as an empirical basis for establishing and implementing a city and trading area strategy plan considering consumers' desired sentiments. In addition, we expect to provide entrepreneurs and potential entrepreneurs entering the trading area with sentiments possessed by those in the trading area and directions into the trading area considering the district-sentiment structure.

• Journal of Navigation and Port Research
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• v.35 no.1
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• pp.57-62
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• 2011

On the view point of renewable energies as energy sources of district heating and cooling plant, the purpose of this study is to develop, classify and map the 500m${\times}$500m mesh, of which is treated as normal size in DHC regulations for evaluation process. Followings are the results. Various building and geographical informations including 13 districts and 108 counties are re-defined to create 500m${\times}$500m meshes, and it is find out that 3,289 meshes among 8,463 meshes have meaningful floor areas. Only 59 meshes(1.8%) are evaluated as mesh which has more than 50% of building volume ratio per mesh. 5 clusters classified by principal analysis and cluster analysis with building needs' characteristics are defined. Gwang-an Dong is representative of cluster 1 characterized as commercial area, and the cluster 4, 5 which has mainly residential needs are distributed in Yong-ho dong. Because there are a lot of cluster 3 meshes, which has complex needs area based on residential, cluster 3 could be defined as representative of Busan metropolitan city.

• Proceedings of the KSRS Conference
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• v.2
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• pp.551-554
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• 2006

House management is very important in water resource protection in order to provide sustainable drinking water for about four millions population in northern Taiwan. House management can be a simple job that can be done without any ingredient of remote sensing or geographic information systems. Remote sensing and GIS integration for house management can provide more efficient management prescription when land use enforcement, soil and water conservation, sewage management, garbage collection, and reforestation have to be managed simultaneously. The objective of this paper was to integrate remote sensing and GIS to manage houses in a water resource protection district. More than four thousand houses have been surveyed and created as a house data base. Site map of every single house and very detail information consisting of address, ownership, date of creation, building materials, acreages floor by floor, parcel information, and types of house condition. Some houses have their photos in different directions. One house has its own card consists these information and these attributes were created into a house data base. Site maps of all houses were created with the same coordinates system as parcel maps, topographic maps, sewage maps, and city planning maps. Visual Basic.NET, Visual C#.NET have been implemented to develop computer programs for house information inquiry and maps overlay among house maps and other GIS map layers. Remote sensing techniques have been implemented to generate the background information of a single house in the past 15 years. Digital orthophoto maps at a scale of 1:5000 overlay with house site maps are very useful in determination of a house was there or not for a given year. Satellite images if their resolutions good enough are also very useful in this type of daily government operations. The developed house management systems can work with commercial GIS software such as ArcView and ArcPad. Remote sensing provided image information of a single house whether it was there or not in a given year. GIS provided overlay and inquiry functions to automatically extract attributes of a given house by ownership, address, and so on when certain house management prescriptions have to be made by government agency. File format is the key component that makes remote sensing and GIS integration smoothly. The developed house management systems are user friendly and can be modified to meet needs encountered in a single task of a government technician.

• International Journal of Advanced Culture Technology
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• v.10 no.1
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• pp.274-283
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• 2022

Korea is facing a number difficulties arising from rising housing prices. As 'housing' takes the lion's share in personal assets, many difficulties are expected to arise from fluctuating housing prices. The purpose of this study is creating housing price prediction model to prevent such risks and induce reasonable real estate purchases. This study made many attempts for understanding real estate instability and creating appropriate housing price prediction model. This study predicted and validated housing prices by using the LSTM technique - a type of Artificial Intelligence deep learning technology. LSTM is a network in which cell state and hidden state are recursively calculated in a structure which added cell state, which is conveyor belt role, to the existing RNN's hidden state. The real sale prices of apartments in autonomous districts ranging from January 2006 to December 2019 were collected through the Ministry of Land, Infrastructure, and Transport's real sale price open system and basic apartment and commercial district information were collected through the Public Data Portal and the Seoul Metropolitan City Data. The collected real sale price data were scaled based on monthly average sale price and a total of 168 data were organized by preprocessing respective data based on address. In order to predict prices, the LSTM implementation process was conducted by setting training period as 29 months (April 2015 to August 2017), validation period as 13 months (September 2017 to September 2018), and test period as 13 months (December 2018 to December 2019) according to time series data set. As a result of this study for predicting 'prices', there have been the following results. Firstly, this study obtained 76 percent of prediction similarity. We tried to design a prediction model of real estate transaction price with the LSTM Model based on AI and Bigdata. The final prediction model was created by collecting time series data, which identified the fact that 76 percent model can be made. This validated that predicting rate of return through the LSTM method can gain reliability.