• Korean Journal of Remote Sensing
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• v.37 no.5_3
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• pp.1389-1403
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• 2021

Disaster management using VHR (very high resolution) satellite images supports rapid damage assessment and also offers detailed information of the damages. However, the acquisition of pre-event VHR satellite images is usually limited due to the long revisit time of VHR satellites. The absence of the pre-event data can reduce the accuracy of damage assessment since it is difficult to distinguish the changed region from the unchanged region with only post-event data. To address this limitation, in this study, we conducted the wildfire-induced change detection on national wildfire cases using post-fire VHR satellite images and GIS (Geographic Information System) data. For GIS data, a national land cover map was selected to simulate the pre-fire NIR (near-infrared) images using the spatial information of the pre-fire land cover. Then, the simulated pre-fire NIR images were used to analyze bi-temporal NDVI (Normalized Difference Vegetation Index) correlation for unsupervised change detection. The whole process of change detection was performed on a superpixel basis considering the advantages of superpixels being able to reduce the complexity of the image processing while preserving the details of the VHR images. The proposed method was validated on the 2019 Gangwon wildfire cases and showed a high overall accuracy over 98% and a high F1-score over 0.97 for both study sites.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.4
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• pp.223-233
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• 2021

Systematic and continuous monitoring and management of the energy consumption of buildings are important for estimating building energy efficiency, and ultimately aim to cope with climate change and establish effective policies for environment, and energy supply and demand policies. Globally, buildings consume 36% of total energy and account for 39% of carbon dioxide emissions. The purpose of this study is to generate three-dimensional thermo-spatial building models with photogrammetric technique using drone TIR (Thermal Infrared) images to measure the temperature emitted from a building, that is essential for the building energy rating system. The aerial triangulation was performed with both optical and TIR images taken from the sensor mounted on the drone, and the accuracy of the models was analyzed. In addition, the thermo-spatial models of temperature distribution of the buildings in three-dimension were visualized. Although shape of the objects 3D building modeling is relatively inaccurate as the spatial and radiometric resolution of the TIR images are lower than that of optical images, TIR imagery could be used effectively to measure the thermal energy of the buildings based on spatial information. This paper could be meaningful to present extension of photogrammetry to various application. The energy consumption could be quantitatively estimated using the temperature emitted from the individual buildings that eventually would be uses as essential information for building energy efficiency rating system.

• Journal of the Korean Wood Science and Technology
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• v.47 no.2
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• pp.229-238
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• 2019

Various wood defects occur during tree growing or wood processing. Thus, to use wood practically, it is necessary to objectively assess their quality based on the usage requirement by accurately classifying their defects. However, manual visual grading and species classification may result in differences due to subjective decisions; therefore, computer-vision-based image analysis is required for the objective evaluation of wood quality and the speeding up of wood production. In this study, the SIFT+k-NN and CNN models were used to implement a model that automatically classifies knots and analyze its accuracy. Toward this end, a total of 1,172 knot images in various shapes from five domestic conifers were used for learning and validation. For the SIFT+k-NN model, SIFT technology was used to extract properties from the knot images and k-NN was used for the classification, resulting in the classification with an accuracy of up to 60.53% when k-index was 17. The CNN model comprised 8 convolution layers and 3 hidden layers, and its maximum accuracy was 88.09% after 1205 epoch, which was higher than that of the SIFT+k-NN model. Moreover, if there is a large difference in the number of images by knot types, the SIFT+k-NN tended to show a learning biased toward the knot type with a higher number of images, whereas the CNN model did not show a drastic bias regardless of the difference in the number of images. Therefore, the CNN model showed better performance in knot classification. It is determined that the wood knot classification by the CNN model will show a sufficient accuracy in its practical applicability.

• Journal of Digital Convergence
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• v.17 no.2
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• pp.373-379
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• 2019

This study examines the process and scope of visual directing through the case of SM Entertainment, and explores the role of visual directors. As a result of the case study, SM created the visual directing team composed of art director and visual designers within the creative headquarters and was actively introducing visual directing for the development of idol. The visual directing process of SM, which is being developed as a part of the star marketing, consists of analyzing the environment in marketing strategy, establishing marketing strategy related to idol, setting up target image per artist, and finally planning and managing the visual directing project. The visual director in SM is required to have creative talent, logical persuasion, information analytical ability, visual expression ability, and field application ability. SM also applies visual directing accumulated from idol singers to SM business areas such as MD product design and production, product composition and designer collaboration, and SM town COEX artium. This paper have significance in attracting visual directing to the academic field.

• International Area Studies Review
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• v.13 no.3
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• pp.413-438
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• 2009

Tourism is an attractive field of industry to many countries due to its strong potentials in increasing employment rates as well as improving the national image. The positive effect of the tourism on the national economy and globalization has been recognized in Korea. A multilateral effort has been made in order to develop its tourist industry. Therefore, it is necessary to analyze the patterns of tourism demand in Korea. The present study analyzes and demonstrates the effects of a nation's characteristics on tourism demand. The study model was based on factors that affected tourism demand, especially emphasizing on the economic size, distance, national income, and language differences from the mother country. In particular, this study highlights the effects of economic relations between the countries and their exchange rate on tourism demand. In summary, this thesis demonstrates that actual national and international panel data enhance the credibility of the research and precisely determine factors that have a direct influence on tourism demand. A corresponding strategy of development and products are required as most tourists show the preference in advanced nations.

• Korean Journal of Remote Sensing
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• v.34 no.6_3
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• pp.1399-1414
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• 2018

Natural forests are un-manned forests where the artificial forces of people are not applied to the formation of forests. On the other hand, artificial forests are managed by people for their own purposes such as producing wood, preventing natural disasters, and protecting wind. The artificial forests enable us to enhance economical benefits of producing more wood per unit area because it is well-maintained with the purpose of the production of wood. The distinction surveys have been performed due to different management methods according to forests. The distinction survey between natural forests and artificial forests is traditionally performed via airborne remote sensing or in-situ surveys. In this study, we suggest a classification method of forest types using satellite imagery to reduce the time and cost of in-situ surveying. A classification map of natural forest and artificial forest were generated using KOMPSAT-3, 3A, 5 data by employing artificial neural network (ANN). And in order to validate the accuracy of classification, we utilized reference data from 1/5,000 stock map. As a result of the study on the classification of natural forest and plantation forest using artificial neural network, the overall accuracy of classification of learning result is 77.03% when compared with 1/5,000 stock map. It was confirmed that the acquisition time of the image and other factors such as needleleaf trees and broadleaf trees affect the distinction between artificial and natural forests using artificial neural networks.

• Korean Journal of Heritage: History & Science
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• v.46 no.3
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• pp.78-93
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• 2013

The purpose of this study is to analyze college students' perception of national natural heritages, including natural monumentsand scenic sites, in comparison with the similar concepts of national parks and eco-landscape preservation areas, to suggest managerial implications to enhance competitiveness. The first objective of this study is to measure their attitude toward traveling each type of natural heritage and to rate the relative importance of the four types of heritages in terms of preservation. Natural monuments were perceived as the most strongly preserved type, while scenic sites were perceived as the least strongly preserved type. The second objective is to conduct a correspondence analysis to match the concepts of four types of natural heritages with 10 tourist attractions representing the types. It was found that college students have difficulty appropriately identifying the types of 10 tourist attractions. In addition, multi-dimensional scaling (MDS) was implemented to identify the similarities and differences of the four types of natural heritages and to produce a positioning map matching the four types of natural heritages with the six attributes representing each type as a tourist attraction. Natural monuments were perceived very differently from scenic sites and not very differently from eco-landscape preservation areas. There were a few associations between the four types of natural heritages and the six tourism attributes, implying that little effort is made to promote and position each type of natural heritage in terms of tourism. In conclusion, a public awareness program is required to enhance the brand image of natural monuments and scenic sites in comparison to national parks and eco-landscape preservation areas. In addition, local residents who live near the natural heritages should be bolstered to play a managerial role as supporters and contents providers for sustainability.

• Journal of Digital Convergence
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• v.17 no.1
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• pp.159-168
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• 2019

The purpose of this study is to propose a strategy for creating an advertisement for Corporate Social Responsibility(CSR) based on the strategy of selecting an advertisement model in order to efficiently execute the advertisement of CSR. Data were analyzed by regression analysis. The results of this study are as follows: First, it is found that the value-relevance factors of the model are important regardless of the theme of CSR. In the economic field, the reliability of the model is important. But, the attractiveness of the model was more important in the environmental field. Second, it is effective to select a model with high value-relevance when selecting CSR advertising model. But, in the case of an expert, it is effective to select not only value addition, but also attractive and reliable models. Third, when producing CSR ads using emotional messages, it is important to consider the value and reliability of the advertising model. But, it is important to select the model considering the importance of the value and attractiveness of the advertisement model when producing the CSR advertisement using the informational message. It was found that it is very important to select a model that has a high relevance to the image of the social responsibility subject and the advertisement model when producing the social responsibility advertisement.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.29 no.2
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• pp.71-76
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• 2019

Recently, the demand of labels for product management is increasing, as the automation system becomes more common. the development of functional labels which can be used in various environments has been rapidly proceeded. In the case of a printed circuit board, barcode labels with thermal and chemical stability are generally used due to a high temperature process around $300^{\circ}C$ and chemical cleaning in the manufacturing process. However, the yellowing phenomenon of labels that can lower the resolution of printed barcode image still needs to be prevented. In this study, we prepared a composite coating layer using a silica inorganic binder and a titanium dioxide white pigment, and developed a functional labels with thermal and chemical stability. The silica inorganic binder prepared by sol-gel process was confirmed to show excellent adhesion and abrasion resistance with the polyimide film. The white coating layer could be formed on the polyimide film with mixing the silica inorganic binder and titanium dioxide white pigment. The prepared coating layer showed excellent whiteness and glossiness above $400^{\circ}C$. The excellent chemical stability of the coating layer was also confirmed by the chemical treatment with acidic (pH 1.6) and basic (pH 13.6) cleaners.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.400-402
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• 2019

The electric point machine, which is used for the control of the turnout used to change the track of the train, is very important in the railway system. Various wired and wireless real-time monitoring systems are used to check the status of the point machine, but there is a possibility of malfunction due to sensor or network error. In this paper, a redundant monitoring system was designed that incorporates the point machine monitoring system and the CCTV camera control system to double check the operation of the point machine. In the point machine monitoring system, the operating state of the railway converter is monitored, alarmed and transmitted over the network. The CCTV camera control system, which received this information, was required to record the status of the turnout and the point machine in question and send it to the administrator. The manager of the railway line can check the conversion status of the railway through the monitoring screen for the railway line switcher first, and then confirm the switching status directly through the CCTV camera image, thereby improving the reliability of the point machine operation. It will also enable the safe and efficient operation of personnel for management. It is expected to contribute to preventing a derailment caused by a malfunction of the point machine.