• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.6
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• pp.40-53
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• 2018

In smart card data, movement of railway passengers appears in order of smart card terminal ID. The initial terminal ID holds information on the entering station's tag-in railway line, the final terminal ID the exit station tag-out railway line, and the middle terminal ID the transfer station tag subway line. During the past, when the metropolitan city rail consisted of three public corporations (Seoul Metro, Incheon Transit Corporation, and Korail), OD data was expressed in two metrics of initial and final smart card terminal ID. Recently, with the entrance of private corporations like Shinbundang Railroad Corporation, and UI Corporation, inclusion of entering transfer line terminal ID and exiting transfer line terminal ID as part of Chain OD has become standard. Exact route construction using Chain OD has thus become integral as basic data for revenue allocation amongst metropolitan railway transport corporations. Accordingly, path detection in railway networks has evolved to an optimal path detection problem using Chain OD, hence calling for a renewed solution method. This research proposes an optimal path detection method between the initial terminal ID and final terminal ID of Chain OD terminal IDs within the railway network. Here, private line transfer TagIn/Out must be reflected in optimal path detection using Chain OD. To achieve this, three types of link-based optimum path detection methods are applied in order of 1. node-link, 2. link-link, 3. link-node. The method proposed based on additional path costs is shown to satisfy the optimal conditions.

• Korean Journal of Environment and Ecology
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• v.35 no.4
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• pp.387-397
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• 2021

This study aims to present reference data necessary for developing evaluation indicators to analyze the actual resilience of purchased land by investigating the factors that affect the restoration of the purchased land in the riparian zone and quantitatively calculating its importance. The main results are as follows. Firstly, this study identified 34 potential resilience factors through a literature review encompassing domestic and overseas studies and derived seven ecological responsiveness factors, six physical responsiveness factors, and four managerial responsiveness factors through the Delphi survey. Secondly, reliability analysis and Analytic Hierarchy Process (AHP) analysis derived the following important factors: structural stability of the vegetation restored in the purchased land, species diversity of wildlife, structural stability of wildlife, the size of restored wetland after purchase, number of plant species, and the land cover status adjacent to the purchased land. The study results are expected to be helpful information for ecological restoration and management plans reflecting reinforcing factors for resilience at each stage of land purchase, restoration, and management.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.391-404
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• 2021

This study developed a long-term prediction model for the potential yield of garlic based on a genetic algorithm (GA) by utilizing global climate reanalysis data. The GA is used for digging the inherent signals from global climate reanalysis data which are both directly and indirectly connected with the garlic yield potential. Our results indicate that both deterministic and probabilistic forecasts reasonably capture the inter-annual variability of crop yields with temporal correlation coefficients significant at 99% confidence level and superior categorical forecast skill with a hit rate of 93.3% for 2 × 2 and 73.3% for 3 × 3 contingency tables. Furthermore, the GA method, which considers linear and non-linear relationships between predictors and predictands, shows superiority of forecast skill in terms of both stability and skill scores compared with linear method. Since our result can predict the potential yield before the start of farming, it is expected to help establish a long-term plan to stabilize the demand and price of agricultural products and prepare countermeasures for possible problems in advance.

• Land and Housing Review
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• v.13 no.1
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• pp.67-84
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• 2022

This study aims to investigate the value of greenbelts exploring how they can be linked with green infrastructure networks. This research interprets the results of geographical information system (GIS) analysis differently from a conventional approach. The findings of the research are four-fold based on the analysis of the Daejeon Metropolitan Area. First, the most controversial greenbelts are laid on Yuseong-gu because the relaxation of the greenbelts for new housing development has caused outstanding issues since the early 2000s. Decisions on further relaxation or restoration of the greenbelts, which will provide a new direction for the establishment of green infrastructure networks, should be made through accurate environmental assessments. Second, the connected north-south corridors of large cities will affect the greenbelts not only in Daejeon, but also in the entire Chungcheong Provinces, and surrounding local municipalities, which should be considered for the revision of the greenbelt policy. Third, it is expected to experience growing development pressures towards neighboring municipalities due to the ongoing strict greenbelt policy. Among them, the most likely areas are Sejong City to the north and Nonsan to the south, requiring policy measures. Fourth, the value of green infrastructure should be added to current evaluation criteria rather than a binary approach - relaxing or preserving the greenbelts - to be holistically integrated with a metropolitan plan.

• The Journal of the Korea Contents Association
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• v.22 no.9
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• pp.260-270
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• 2022

With the revision of the 「State Property Act」, the conditions for using state-owned land have improved. The new government is also suggesting the necessity of using state-owned land to revitalize private investment and secure financial investment capacity. In line with these policy changes, this study examines Japan's policy on the utilization of state-owned land and effective use cases, and seeks to find policy implications from the perspective of managing and promoting the use of state-owned land. The direction of Japan's public land utilization policy is to induce optimal use of state-owned land through efficient management, and to increase the value of state property by promoting active use of state-owned land through linkage of state-owned and public land and private participation, etc. It appears that the policy is being pursued in the direction of suppressing the sale of state-owned land in the country. To promote the effective use of state-owned land, it is necessary to establish a clear policy direction first. In addition, the establishment of a transparent information disclosure system and the establishment of a strong control tower capable of coordinating interests between ministries are required. The starting point of policy establishment for efficient use of state-owned land is to change the perception that the actual owner of state-owned land is the people.

• Korean Journal of Remote Sensing
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• v.38 no.5_1
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• pp.597-608
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• 2022

Remotely sensed data have been used in various fields, such as disasters, agriculture, urban planning, and the military. Recently, the demand for the multitemporal dataset with the high-spatial-resolution has increased. This manuscript proposed an automatic image matching algorithm using a deep learning technique to utilize a multitemporal remotely sensed dataset. The proposed deep learning model was based on High Resolution Net (HRNet), widely used in image segmentation. In this manuscript, denseblock was added to calculate the correlation map between images effectively and to increase learning efficiency. The training of the proposed model was performed using the multitemporal orthophotos of the National Geographic Information Institute (NGII). In order to evaluate the performance of image matching using a deep learning model, a comparative evaluation was performed. As a result of the experiment, the average horizontal error of the proposed algorithm based on 80% of the image matching rate was 3 pixels. At the same time, that of the Zero Normalized Cross-Correlation (ZNCC) was 25 pixels. In particular, it was confirmed that the proposed method is effective even in mountainous and farmland areas where the image changes according to vegetation growth. Therefore, it is expected that the proposed deep learning algorithm can perform relative image registration and image matching of a multitemporal remote sensed dataset.

• Journal of the Korean Institute of Landscape Architecture
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• v.46 no.1
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• pp.9-16
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• 2018

Landscape architecture is an indispensable professional service in building sustainable land and urban environments. The landscape architecture industry is closely related to the promotion of the health and welfare of the people, urban revitalization and residential environment improvement as well as job creation. Despite various public interest values of landscape architecture, the growth engine of the landscape architecture industry, which is supposed to improve the quality of landscape services, has stagnated. In 2015, the Landscape Architecture Promotion Act was enacted to provide a landscape architectural promotion facility and complex system to support revitalization through the integration of the landscape architecture industry. The purpose of this study is to suggest an improvement plan to enhance the effectiveness of the landscape architectural promotion facility and complex system. The results of the analysis are as follows: First, workers and experts in landscape architecture recognized the need for policies and projects to promote the landscape architecture industry. Second, the industrial types suitable for the landscape architectural promotion facility were landscape design, landscape maintenance and management, and landscape construction industry. Meanwhile the industrial types suitable for a landscape architectural promotion complex were landscape trees and landscape facilities production and distribution. Third, the expected effect of the designation of the landscape architectural facility was 'the increase of the business opportunity through the expansion of the network'. On the other hand, that of the landscape architectural promotion complex was 'the activation of various information sharing'. Fourth, 'the size of the local government landscape architecture industry and the capacity to cultivate' was the most important among the designation criteria of the landscape architectural promotion facility. As for that of the landscape architectural promotion complex, the 'feasibility of promotion plan' was the most crucial. Fifth, 'tax benefit and deductible exemption' was considered as a necessary support method for the activation of the landscape architectural promotion facility, and 'maintenance and management fee support' was recognized in the case of the landscape architectural promotion complex.

• Tuberculosis and Respiratory Diseases
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• v.48 no.6
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• pp.837-852
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• 2000

Backgrounds : Today, tuberculosis cannot only be cured medically, but also controlled by public health. Despite the overall worldwide decline in tuberculosis, the disease continues to be a significant problem among developing countries and in the slums of large cities in some industrialized countries. Particularly, this communicable disease has come into the public health spotlight because of its resurgence in the 1990's. our country has been operating the Korean National Tuberculosis Control Program since 1962, focusing around public health centers. Therefore, this study aims to compare the effectiveness of tuberculosis control activities, one of the major public health activities in Korea, by producing indexes, such as the yearly registration rate per 100,000 population and treatment compliance of tuberculosis on in small areas (communities). Methods : This work was accomplished by constructing a time-series analytic model using data from "1980~2000: the Yearly Statistical Report" with patient registry data of 234 City. County. District public health centers and by identifying the factors influencing the tuberculosis indexes. Results : The trends of pulmonary tuberculosis positive point prevalence and pulmonary tuberculosis negative point prevalence on X-ray screening have declined steadily, beginning in 1981 and continuing to 1998 by region (city, county, district). Although the tuberculosis mortality rate steadily shows a declining trend by year and region, but Korea still ranks first among 29 OECD countries in 1998, with a tuberculosis mortality rate of 7.1 per 100,000 persons, according to the time-series analysis for fatal diseases. Conclusion : The results of the study will form the fundamental basis of future regional health care planning and the Korean Tuberculosis Surveillance System on 2000. Since the implementation of local autonomy through the Local Health Act of 1995, it has now become vita1 for each city, county, district public health centers to determine its own priorities for relevant health care management, including budget allocation and program goals.

• Korean Journal of Environment and Ecology
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• v.32 no.6
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• pp.686-697
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• 2018

Due to the advance in remote sensing technology, it has become easier to more frequently obtain high resolution imagery to detect delicate changes in an extensive area, particularly including forest which is not readily sub-classified. Time-series analysis on high resolution images requires to collect extensive amount of ground truth data. In this study, the potential of land coverage mapas ground truth data was tested in classifying high-resolution imagery. The study site was Wonju-si at Gangwon-do, South Korea, having a mix of urban and natural areas. KOMPSAT-3A imagery taken on March 2015 and land coverage map published in 2017 were used as source data. Two pixel-based classification algorithms, Support Vector Machine (SVM) and Random Forest (RF), were selected for the analysis. Forest only classification was compared with that of the whole study area except wetland. Confusion matrixes from the classification presented that overall accuracies for both the targets were higher in RF algorithm than in SVM. While the overall accuracy in the forest only analysis by RF algorithm was higher by 18.3% than SVM, in the case of the whole region analysis, the difference was relatively smaller by 5.5%. For the SVM algorithm, adding the Majority analysis process indicated a marginal improvement of about 1% than the normal SVM analysis. It was found that the RF algorithm was more effective to identify the broad-leaved forest within the forest, but for the other classes the SVM algorithm was more effective. As the two pixel-based classification algorithms were tested here, it is expected that future classification will improve the overall accuracy and the reliability by introducing a time-series analysis and an object-based algorithm. It is considered that this approach will contribute to improving a large-scale land planning by providing an effective land classification method on higher spatial and temporal scales.

• 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.