• Journal of Korea Spatial Information System Society
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• v.11 no.1
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• pp.1-8
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• 2009

The u-GIS national land information providing technology is the technology which maximizes the application of u- GIS data through the national land information platform technique of the next generation web and provides a user with the on-demand national land information in the ubiquitous environment. Recently, as the environment emphasizing the web as a platform 'Web 2.0' emerges, the where 2.0 which is paradigm is diffused in the spatial information area. And the Geo-spatial Web technology develops in a center. Moreover, it is changed to the open platform of the user participation trend. And the consumer of the geo-spatial information is changed to the end-user center from the public institution. The geo-spatial technique is technologically faced with the new challenge. In this paper, we analyze the technical tendency about a paradigm, And we present the u-GIS national land information platform technique, the u-GIS national land information visualization technology, the u-GIS national land information GeoDRM integrative technique, and the u-GIS national land information mobile application technology as the essential elemental technology for overcoming this.

• Journal of Korea Spatial Information System Society
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• v.11 no.4
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• pp.33-38
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• 2009

Since the beginning of 2000, the ubiquitous technology rapidly has been at center of public concerns, and application of the ubiquitous technology is expanding in Korea with U-City as the center. U-City is currently planned and built by local governments, but the applicable range of the ubiquitous technology should be expanded in the future to build U-Territory and U-Land projects. As a part of this, U-forest should also be implemented, and that now is the time to gain support in policy and systematic initiative. Therefore, this study defines U-Forest concept to implement valuable national resources, healthy land environment, and pleasant green space by using ubiquitous technology as an effective way to produce, manage, use, and distribute the forest. In order to establish strategy for U-Forest, it has considered basic forest plan, k-Forest, and FGIS projects, and has drawn a service model pertaining to them. Also, it has proposed the need to establish the basic plan for U-Forest, and suggested details to include in the plan.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.11a
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• pp.1369-1372
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• 2010

유비쿼터스 및 건설기술 등이 융합된 유시티는 최근 신도시를 중심으로 활발하게 구축 중에 있다. 그러나 구축 및 운영에 있어 고비용의 예산요구로 실효성을 얻기에 많은 어려움을 겪고 있다. 특히, 유시티 통합네트워크센터에서 요구되는 표준화된 유시티 통합플랫폼의 부재로 각각의 유시티에서 개발된 U-서비스의 재활용이 어려울 뿐만 아니라 U-서비스 간 연계에 많은 어려움이 발생하고 있다. 이에 따라 본 연구에서는 SOA기반 통합플랫폼을 제시함으로써 U-서비스의 쉽고 빠른 개발, 개발된 서비스의 재활용 및 서비스 간 연계 효율성을 높일 수 있도록 설계하였다.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.29 no.4
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• pp.159-169
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• 2011

This research aims to discover how the pure land(Sukkavati), which had the greatest impact on ordinary people since the Shilla period, are represented in the Buddhist temples. This study first looked into the seven landscapes of the pure land, which are written on the $Amit{\bar{a}}yurdhy{\bar{a}}na$ $S{\bar{u}}tra$ a reliance on $s{\bar{u}}tras$ of the Pure Land School. Then, their meaning in the modern world were interpreted. Next the research moved on to the next step to see how the spirit and ideas of the pure land are shown in temples of the Pure Land School. Korean temples of the Pure Land School were found to faithfully embody the landscapes of the pure land in the $Amit{\bar{a}}yurdhy{\bar{a}}na$ $S{\bar{u}}tra$. One might say that those landscape traits of the temples surveyed are common among all Korean buddhist temples, but in the temples of the Pure Land School. those traits consistently reflect special concepts, forming their landscape identity. But ponds, on which the $Amit{\bar{a}}yurdhy{\bar{a}}na$ $S{\bar{u}}tra$ and the picture of $Amit{\bar{a}}yurdhy{\bar{a}}na$ $S{\bar{u}}tra$ put huge emphasis and drawn without an exception, were hard to find among the temples surveyed. This means that previous idea that a pond was an indispensible part in the temples of the Pure Land School needs to be corrected.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.04a
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• pp.1047-1050
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• 2011

U-City 건설은 도시의 과밀화 및 자원부족, 경제 사회적 급격한 변화 등으로 발생하게 되는 각종 도시문제들을 첨단정보통신기술을 활용하여 저비용, 고효율적인 해결방안으로 대두되고 있다. 그러나 신도시를 중심으로 유시티 건설을 추진 중인 많은 지방자치단체에서 무분별한 서비스 개발로 인해 유지보수 및 운영에 따른 어려움을 겪고 있고 사업시행자에게도 개발 비용부담을 가중시키고 있다. 이에 따라 본 연구에서는 유시티 건설 사업에서 제기되고 있는 유시티 서비스 구축 범위에 대하여 여러 분류 및 적용 방법들을 제안하여 합리적인 유시티 서비스 건설기준 수립 방안을 제시하였다.

• Land and Housing Review
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• v.2 no.2
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• pp.101-109
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• 2011

Recently, the construction of U-City or of U-City service (U-service) in many kinds of urban development projects becomes the general trend. However, as the construction of U-city comes into the spotlight like the trend of the times, various service constructions are being indiscreetly implemented since it's processed focusing on local specialized projects or local landmark project by a local autonomous entity or an institute in charge being off the original purpose of the improvement of living quality of residents and the efficiency of urban management, which causes a number of problems on the process, maintenance, operation and management of those projects. Therefore, this study is to derive the standard pattern of U-service construction through the analysis of patterns and numbers of U-service and problems during the process of construction in domestic U-City construction case district, and is aimed to suggest the reasonable direction of service construction based on this. 11 projects areas in which data related to U-service are available among U-City construction project areas were selected for the subjects of this study, and it's standardized with 228 detailed unit services that were suggested by U-Eco City R&D and with 11 service domains that are regulated in "the Act of ubiquitous city construction etc.", and it is limited to services that were suggested in U-City case area of which design was completed by July, 2010 based on this. The actual state of various U-service construction is analyzed through case studies as well as reviews on the legal and theoretical concept and the method of pattern classification of U-service, the plan for the standardization (pattern classification) of U-service and the plan for the construction body of service and to share the costs are suggested as the plan to construct reasonable U-service based on this for the method and the procedure of this study For the method to construct U-service, the plan to classify the pattern of U-service into the basic service and additional service is suggested, and whether it has the publicity, whether urban infrastructure is included, whether utilities are included, the body of realization, the recipients, the urgency, the importance and the spreading, etc. are suggested for the index to determine the pattern of service. The method to get the executor of a project to construct the basic service, the method to get the executor of a project to construct the most basic service among the group classification of service and to get a private entity and a local autonomous entity to perform additional service in the future, and the method to construct the whole service and to distribute the construction costs were suggested, and the first one that determines the body of construction after dividing U-service into the basic service and the additional service was evaluated to be the most reasonable one. And the plan to solve the problem that the excessive construction costs of U-service are shifted onto the executor of a project through benefit principle, balanced distribution principle and consultation and mediation between the interested parties was suggested for the criteria to share the costs.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.871-884
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• 2021

The purpose of this study was to determine ways to increase efficiency in constructing and verifying artificial intelligence learning data on land cover using aerial and satellite images, and in applying the data to AI learning algorithms. To this end, multi-resolution datasets of 0.51 m and 10 m each for 8 categories of land cover were constructed using high-resolution aerial images and satellite images obtained from Sentinel-2 satellites. Furthermore, fine data (a total of 17,000 pieces) and coarse data (a total of 33,000 pieces) were simultaneously constructed to achieve the following two goals: precise detection of land cover changes and the establishment of large-scale learning datasets. To secure the accuracy of the learning data, the verification was performed in three steps, which included data refining, annotation, and sampling. The learning data that wasfinally verified was applied to the semantic segmentation algorithms U-Net and DeeplabV3+, and the results were analyzed. Based on the analysis, the average accuracy for land cover based on aerial imagery was 77.8% for U-Net and 76.3% for Deeplab V3+, while for land cover based on satellite imagery it was 91.4% for U-Net and 85.8% for Deeplab V3+. The artificial intelligence learning datasets on land cover constructed using high-resolution aerial and satellite images in this study can be used as reference data to help classify land cover and identify relevant changes. Therefore, it is expected that this study's findings can be used in the future in various fields of artificial intelligence studying land cover in constructing an artificial intelligence learning dataset on land cover of the whole of Korea.

• Korean Journal of Remote Sensing
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• v.39 no.3
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• pp.269-282
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• 2023

The purpose of this study was to construct land cover maps using a deep learning model and to select the optimal deep learning model for land cover classification by adjusting the dataset such as input image size and Stride application. Two types of deep learning models, the U-net model and the DeeplabV3+ model with an Encoder-Decoder network, were utilized. Also, the combination of the two deep learning models, which is an Ensemble model, was used in this study. The dataset utilized RapidEye satellite images as input images and the label images used Raster images based on the six categories of the land use of Intergovernmental Panel on Climate Change as true value. This study focused on the problem of the quality improvement of the dataset to enhance the accuracy of deep learning model and constructed twelve land cover maps using the combination of three deep learning models (U-net, DeeplabV3+, and Ensemble), two input image sizes (64 × 64 pixel and 256 × 256 pixel), and two Stride application rates (50% and 100%). The evaluation of the accuracy of the label images and the deep learning-based land cover maps showed that the U-net and DeeplabV3+ models had high accuracy, with overall accuracy values of approximately 87.9% and 89.8%, and kappa coefficients of over 72%. In addition, applying the Ensemble and Stride to the deep learning models resulted in a maximum increase of approximately 3% in accuracy and an improvement in the issue of boundary inconsistency, which is a problem associated with Semantic Segmentation based deep learning models.

• Spatial Information Research
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• v.17 no.4
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• pp.417-430
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• 2009

This study examined correlations between U-Service for U-City and assessment indicators for urban competitiveness. The results of this study show that U-Service is used as a means of strengthening urban competitiveness in six types of cities, despite the differences in degree of contribution. The proper use of U-Service in Safety & Health City and Vitality (Economy) City has significantly contributed to strengthening the competitiveness of such cities. Of the assessment items for urban competitiveness, common items and Culture City type show that U-Service has not contributed much to strengthening urban competitiveness. The analysis shows that because common items are part of the assessment items for urban policies, these items are not suitable to the character of a U-City that implements U-Service through intelligent physical facilities. On the other hand, U-Service related to the Culture City type is relatively less developed. This study found out that U-Service could be used to reinforce urban competitiveness.

• Journal of IKEEE
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• v.27 no.4
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• pp.456-463
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• 2023

In this paper, we introduce the SSResUNet network model, which integrates the SPADE structure with the U-Net network model for accurate land cover classification using high-resolution satellite imagery without requiring user intervention. The proposed network possesses the advantage of preserving the spatial characteristics inherent in satellite imagery, rendering it a robust classification model even in intricate environments. Experimental results, obtained through training on KOMPSAT-3A satellite images, exhibit superior performance compared to conventional U-Net and U-Net++ models, showcasing an average Intersection over Union (IoU) of 76.10 and a Dice coefficient of 86.22.