• Journal of Cadastre & Land InformatiX
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• v.53 no.1
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• pp.47-63
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• 2023

The Seoul Metropolitan Government is building and operating digital twin-based urban spatial information to solve various problems in the city and provide public services. Two essential factors to ensure the stable utilization of spatial information for the implementation of such a digital twin city are the latest and quality of the data. However, it is time-consuming and costly to maintain continuous updating of high-quality urban spatial information. To overcome this problem, we studied efficient urban spatial information construction technology and the operation, management, and update procedures of construction data. First, we demonstrated and applied automatic 3D building construction technology centered on point clouds using the latest hybrid sensors, confirmed that it is possible to automatically construct high-quality building models using high-density airborne lidar results, and established an efficient data management plan. By applying differentiated production methods by region, supporting detection of urban change areas through Seoul spatial feature identifiers, and producing international standard data by level, we strengthened the utilization of urban spatial information. We believe that this study can serve as a good precedent for local governments and related organizations that are considering activating urban spatial information based on digital twins, and we expect that discussions on the construction and management of spatial information as infrastructure information for city-level digital twin implementation will continue.

• Journal of Korean Society for Geospatial Information Science
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• v.16 no.1
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• pp.23-32
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• 2008

According to recent frequent local flash flood due to climate change, the very short-term rainfall forecast using remotely sensed rainfall like radar is necessary to establish. This research is to evaluate the feasibility of GIS-based distributed model coupled with radar rainfall, which can express temporal and spatial distribution, for multipurpose dam operation during flood season. $Vflo^{TM}$ model was used as physically based distributed hydrologic model. The study area was Yongdam dam basin ($930\;km^2$) and the 3 storm events of local convective rainfall in August 2005, and the typhoon.Ewiniar.and.Bilis.collected from Jindo radar was adopted for runoff simulation. Distributed rainfall consistent with hydrologic model grid resolution was generated by using K-RainVieux, pre-processor program for radar rainfall. The local bias correction for original radar rainfall shows reasonable results of which the percent error from the gauge observation is less than 2% and the bias value is $0.886{\sim}0.908$. The parameters for the $Vflo^{TM}$ were estimated from basic GIS data such as DEM, land cover and soil map. As a result of the 3 events of multiple peak hydrographs, the bias of total accumulated runoff and peak flow is less than 20%, which can provide a reasonable base for building operational real-time short-term rainfall-runoff forecast system.

• Journal of Korea Spatial Information System Society
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• v.3 no.1 s.5
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• pp.89-94
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• 2001

The purpose of this study is development of the management system for convenient use of new address guide system for systematic management and use of spatial information gained by mapping of numerical map of building and road to large basic new address, survey and input of main gate, decision of the road session, naming and input of road name, grant of numbering of all houses and buildings, new address guide, real life geographical information and added information service on Web-site in Jecheon-city area. In this study, the development and establishment of new address management in local cities are designed by making full use of GIS function of client server based system. In the result, the effectiveness of new address management system of Jecheon- city could be highly increased owing to not only citizens' easy access but also easy availability of various informations necessary in life by developed its system.

• Korean Journal of Artificial Intelligence
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• v.12 no.4
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• pp.27-33
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• 2024

Various techniques are being researched to effectively detect forest fires. Among them, techniques using object detection models can monitor forest fires over wide areas 24 hours a day. However, detecting forest fires early with traditional object detection models is a very challenging task. While they show decent accuracy for thick smoke and large fires, they show low accuracy for faint smoke and small fires, and frequently generate false positives for lights that are like fires. In this paper, to solve these problems, we focus on leveraging local characteristics such as contours and textures of fire and smoke, which are crucial for accurate detection. Based on this approach, we propose EDAM (Edge driven Attention Module) that performs enhancement by richly utilizing contour and texture information of fire and smoke. EDAM extracts important edge information to generate feature maps with emphasized contour and texture information, and based on this map, performs Attention Mechanism to emphasize key characteristics of smoke and fire. Through this mechanism, the overall model performance was improved, with AP_sincreasing from 0.154 to 0.204 and AP_0.5 from 0.779 to 0.784, resulting in a significant improvement in AP_svalue to 32.47%. In practice, the model applying this technique showed excellent inference speed while greatly improving detection performance for small objects compared to existing models and reduced false positive rates for building and street light illumination in nighttime environments that are easily mistaken for fire.

• Journal of the Korean Association of Geographic Information Studies
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• v.4 no.3
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• pp.13-20
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• 2001

The purpose of this study is development of the management and guide system for convenient use of new address guide system for systematic management and use of spatial information gained by mapping of numerical map of building and road to large basic new address, survey and input of main gate, decision of the road session, naming and input of road name, grant of numbering of all houses and buildings, new address guide, real life geographical information and added information service on web site in Jecheon-si city area. In this study, the development and establishment of new address management and guide system in local cities are designed by making full use of GIS function of client server based system. A guide system is designed the same database as management system, and it is transformed into Web GIS environment and developed in order to add the various functions of life GIS as well as new address guide. In the result, the effectiveness of new address system and guide of Jecheon-si city could be highly increased owing to not only citizens' easy access but also easy availability of various informations necessary in life by developed its system.

• Journal of the Korea Computer Graphics Society
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• v.16 no.1
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• pp.1-7
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• 2010

With the widespread use of vision-based surveillance systems, the capability for person identification is now an essential component. However, the CCTV cameras used in surveillance systems tend to produce relatively low-resolution images, making it difficult to use face recognition techniques for person identification. Therefore, an algorithm is proposed for person identification in CCTV camera images based on the clothing. Whenever a person is authenticated at the main entrance of a building, the clothing feature of that person is extracted and added to the database. Using a given image, the clothing area is detected using background subtraction and skin color detection techniques. The clothing feature vector is then composed of textural and color features of the clothing region, where the textural feature is extracted based on a local edge histogram, while the color feature is extracted using octree-based quantization of a color map. When given a query image, the person can then be identified by finding the most similar clothing feature from the database, where the Euclidean distance is used as the similarity measure. Experimental results show an 80% success rate for person identification with the proposed algorithm, and only a 43% success rate when using face recognition.

• Journal of the Korean Association of Geographic Information Studies
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• v.4 no.1
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• pp.1-17
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• 2001

This research is primarily intended to develop a decision-making support system about the natural environment in the country by integrating various formats of spatial data into a comprehensive GIS database. The first part of the research is to design GIS database as a means of combining thematic cartographic data with field survey records. Ecosystem records acquired by a field sampling have been reproduced as digital thematic maps. The database also included various natural environment related data (map for forestry, soil, national park etc.) collected from many other agencies. The second part of the research is devoted to the design of efficient man-machine interfaces. A key concern in the GUI (graphic user interface) design process was to address the need to handle and to manage large databases by non-GIS experts. The system has been checked experimentally, enabled the users to quarry the data required simply and execute spatial analysis accommodating versatile alternatives in decision-making process. Detailed visual maps can be generated over large areas quickly and easily. The system will serve to increase the scientific and objective decision-making by overcoming serious constraints suffered from the past non-GIS-based approach. It is anticipated that this research output could be used as a valuable reference in building a nationwide natural environment GIS-DB (database) in the central and local governments.

• Journal of the Korean Geotechnical Society
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• v.25 no.1
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• pp.5-19
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• 2009

Most of earthquake-induced geotechnical hazards have been caused by the site effects relating to the amplification of ground motion, which is strongly influenced by the local geologic conditions such as soil thickness or bedrock depth and soil stiffness. In this study, an integrated GIS-based information system for geotechnical data, called geotechnical information system (GTIS), was constructed to establish a regional counterplan against earthquake-induced hazards at an urban area of Daejeon, which is represented as a hub of research and development in Korea. To build the GTIS for the area concerned, pre-existing geotechnical data collections were performed across the extended area including the study area and site visits were additionally carried out to acquire surface geo-knowledge data. For practical application of the GTIS used to estimate the site effects at the area concerned, seismic zoning map of the site period was created and presented as regional synthetic strategy for earthquake-induced hazards prediction. In addition, seismic zonation for site classification according to the spatial distribution of the site period was also performed to determine the site amplification coefficients for seismic design and seismic performance evaluation at any site in the study area. Based on this case study on seismic zonations in Daejeon, it was verified that the GIS-based GTIS was very useful for the regional prediction of seismic hazards and also the decision support for seismic hazard mitigation.

• Tunnel and Underground Space
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• v.33 no.6
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• pp.508-518
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• 2023

This paper presents a new approach for the automatic mapping of discontinuities in a tunnel face based on its 3D digital model reconstructed by LiDAR scan or photogrammetry techniques. The main idea revolves around the identification of discontinuity areas in the 3D digital model of a tunnel face by segmenting its 2D projected images using a deep-learning semantic segmentation model called U-Net. The proposed deep learning model integrates various features including the projected RGB image, depth map image, and local surface properties-based images i.e., normal vector and curvature images to effectively segment areas of discontinuity in the images. Subsequently, the segmentation results are projected back onto the 3D model using depth maps and projection matrices to obtain an accurate representation of the location and extent of discontinuities within the 3D space. The performance of the segmentation model is evaluated by comparing the segmented results with their corresponding ground truths, which demonstrates the high accuracy of segmentation results with the intersection-over-union metric of approximately 0.8. Despite still being limited in training data, this method exhibits promising potential to address the limitations of conventional approaches, which only rely on normal vectors and unsupervised machine learning algorithms for grouping points in the 3D model into distinct sets of discontinuities.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.9
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• pp.595-602
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• 2013

WiFi fingerprinting is well known as an effective localization technique used for indoor environments. However, this technique requires a large amount of pre-built fingerprint maps over the entire space. Moreover, due to environmental changes, these maps have to be newly built or updated periodically by experts. As a way to avoid this problem, crowd-sourced fingerprint mapping attracts many interests from researchers. This approach supports many volunteer users to share their WiFi fingerprints collected at a specific environment. Therefore, crowd-sourced fingerprinting can automatically update fingerprint maps up-to-date. In most previous systems, however, individual users were asked to enter their positions manually to build their local fingerprint maps. Moreover, the systems do not have any principled mechanism to keep fingerprint maps clean by detecting and filtering out erroneous fingerprints collected from multiple users. In this paper, we present the design of a crowd-sourced fingerprint mapping and localization(CMAL) system. The proposed system can not only automatically build and/or update WiFi fingerprint maps from fingerprint collections provided by multiple smartphone users, but also simultaneously track their positions using the up-to-date maps. The CMAL system consists of multiple clients to work on individual smartphones to collect fingerprints and a central server to maintain a database of fingerprint maps. Each client contains a particle filter-based WiFi SLAM engine, tracking the smartphone user's position and building each local fingerprint map. The server of our system adopts a Gaussian interpolation-based error filtering algorithm to maintain the integrity of fingerprint maps. Through various experiments, we show the high performance of our system.