• Journal of the Korean Association of Geographic Information Studies
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• v.11 no.3
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• pp.136-150
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• 2008

Many studies have been carried out for automatic extraction of building by LiDAR data or airphoto. Combining the benefits of 3D location information data and shape information data of image can improve the accuracy. So, in this research building recognition algorithm based on contour was used to improve accuracy of building recognition by LiDAR data and elaborate building boundary recognition by airphoto. Building recognition algorithm based on contour can generate building boundary and roof structure information. Also it shows better accuracy of building detection than the existing recognition methods based on TIN or NDSM. Out of creating buffers in regular size on the building boundary which is presumed by contour, this research limits the boundary area of airphoto and elaborate building boundary to fit into edge of airphoto by double active contour. From the result of this research, 3D building boundary will be able to be detected by optimal matching on the constant range of extracted boundary in the future.

• Journal of Korean Society for Geospatial Information Science
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• v.13 no.3 s.33
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• pp.25-32
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• 2005

This paper presents a method for point-based 3D building reconstruction using Lidar data and digital map. The proposed method consists of three processes: extraction of building roof points, identification of roof types, and 3D building reconstruction. After extracting points inside the polygon of building, the ground surface, wall and tree points among the extracted points are removed through the filtering process. The filtered points are then fitted into the flat plane using ODR(Orthogonal Distance Regression) in the first place. If the fitting error is within the predefined threshold, the surface is classified as a flat roof. Otherwise, the surface is fitted and classified into a gable or arch roof through RMSE analysis. Experimental results showed that the proposed method classified successfully three different types of roof and that the fusion of LIDAR data and digital map could be a feasible method of modeling 3D building reconstruction.

• 한국방재학회:학술대회논문집
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• 2010.02a
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• pp.33.2-33.2
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• 2010

고층건물의 최상층 수평변위는 해당 건물의 안전성 및 사용성 평가에 중요한 지표가 된다 이러한 건물의 수평변위는 주로 풍하중에 기인한다 본 논문에서는 이러한 구조반응을 풍하중에 기인한 풍속데이터로부터 직접 추정하기 위해서 인공신경망(Artificial Neural Network, ANN)을 도입하였다 이에 대한 적용성을 판단하기 위해서 고층건물을 형상화한 모형테스트를 실시하고 풍향, 풍속, 변위 값을 얻었다. 이후 인공신경망에 적용시켜 실제 실험 데이터와의 비교를 통해 타당성을 검토하였다.

• Journal of Energy Engineering
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• v.25 no.1
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• pp.131-144
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• 2016

Damage occur frequently around the world on climate change and the main cause of greenhouse gas emissions regulation is growing. To this end, the government has built integrated management system for national building energy. The building energy information is total 6.8 million complex. Integrated management system for national building energy database are matched building registers information and energy information of the supply agencies. However, the matching process has its limitations so advanced work is in progress continuously. This study analyzed integrated management system for national building energy database quality and limitations and deduce improvement plan to increase system reliability and availability. The existing database matching average rate is 85.6%. 58.2% of the total non-matching data type has no building information. To ensure the ease of new database matching and the accuracy of the existing database matching, address standarization and building properties system are needed between building information and energy information. Also, The system construction is required to include information on other energy sources like petroleum energy which has high proportion of non-urban areas and small residential areas and renewable energy which has high potential in development and utilization.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.3
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• pp.227-239
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• 2008

Processing LiDAR (Light Detection And Ranging) data obtained from ALS (Airborne Laser Scanning) systems mainly involves organization and segmentation of the data for 3D object modeling and mapping purposes. The ALS systems are viable and becoming more mature technology in various applications. ALS technology requires complex integration of optics, opto-mechanics and electronics in the multi-sensor components, Le. data captured from GPS, INS and laser scanner. In this study, digital image processing techniques mainly were implemented to gray level coded image of the LiDAR data for building extraction and superstructures segmentation. One of the advantages to use gray level image is easy to apply various existing digital image processing algorithms. Gridding and quantization of the raw LiDAR data into limited gray level might introduce smoothing effect and loss of the detail information. However, smoothed surface data that are more suitable for surface patch segmentation and modeling could be obtained by the quantization of the height values. The building boundaries were precisely extracted by the robust edge detection operator and regularized with shape constraints. As for segmentation of the roof structures, basically region growing based and gap filling segmentation methods were implemented. The results present that various image processing methods are applicable to extract buildings and to segment surface patches of the superstructures on the roofs. Finally, conceptual methodology for extracting characteristic information to reconstruct roof shapes was proposed. Statistical and geometric properties were utilized to segment and model superstructures. The simulation results show that segmentation of the roof surface patches and modeling were possible with the proposed method.

• Journal of Korean Society for Geospatial Information Science
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• v.13 no.3 s.33
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• pp.59-67
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• 2005

Building information is primary source in many applications such as mapping, telecommunication, car navigation and virtual city modeling. While aerial CCD images which are captured by passive sensor(digital camera) provide horizontal positioning in high accuracy, it is far difficult to process them in automatic fashion due to their inherent properties such as perspective projection and occlusion. On the other hand, LIDAR system offers 3D information about each surface rapidly and accurately in the form of irregularly distributed point clouds. Contrary to the optical images, it is much difficult to obtain semantic information such as building boundary and object segmentation. Photogrammetry and LIDAR have their own major advantages and drawbacks for reconstructing earth surfaces. The purpose of this investigation is to automatically obtain spatial information of 3D buildings by fusing LIDAR data with aerial CCD image. The experimental results show that most of the complex buildings are efficiently extracted by the proposed method and signalize that fusing LIDAR data and aerial CCD image improves feasibility of the automatic detection and extraction of buildings in automatic fashion.

• Journal of Cadastre & Land InformatiX
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• v.52 no.1
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• pp.37-55
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• 2022

This study presents the plans to derive quality items for develop the data quality standard for ensuring the quality of 3D building geospatial data in NDT(National Digital Twin). This paper is organized as follows. The first section briefly examines various factors that impact the quality of 3D geospatial data, and proposes the role and necessity of the data quality standard as a means of addressing the data errors properly and also meeting the minimum requirements of stakeholders. The second section analyzes the relationship between the standards - building data model for NDT and ISO 19157: Geospatial data quality - in order to consider directly relevant standards. Finally, we suggest three plans on developing NDT data quality standard: (1) the scope for evaluating data quality, (2) additional quality elements(geometric integrity, geometric fidelity, positional accuracy and semantic classification accuracy), and (3) NDT data quality items model based on ISO 19157. The plans reveled through the study would contribute to establish a way for the national standard on NDT data quality as well as the other standards associated with NDT over the coming years.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.11a
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• pp.421-424
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• 2013

최근 문제가 되고 있는 전력 문제를 효율적으로 관리하기 위해 건물 에너지 관리 시스템이 주목받고 있다. 건물 에너지 관리 시스템은 관리자가 건물의 전력 소비량을 효율적으로 관리할 수 있도록 전력 소비량에 대한 모니터링 기능을 제공하는 시스템이다. 기존의 건물 에너지 관리 시스템은 과거, 현재, 미래의 전력 소비량을 통계 자료로 제공하고, 이를 토대로 전력 과부하 발생을 방지하였다. 그렇지만 기존의 시스템에 반응형 웹 디자인을 적용한 사례를 찾아보기 힘들며 온도 변화에 따른 전력 소비량을 고려하지 않기 때문에 정확한 부하 예측을 하기 어렵다는 단점이 있다. 본 논문에서 제안한 건물 에너지 관리 시스템은 반응형 웹 디자인을 적용하여 여러 모바일 기기로도 편리하고 효율적으로 건물을 관리할 수 있게 하였다. 또한, 건물에서 유지되어야 할 목표 온도, 건물 전력 소비량에 대한 과거 데이터와 기상청에서 제공하는 데이터를 통하여 부하 예측을 하고, 다양한 전력 소비량 통계 자료를 제공한다. 이를 통해 관리자는 효율적인 건물 에너지 관리를 할 수 있다.

• Journal of Korean Society for Geospatial Information Science
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• v.20 no.4
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• pp.117-125
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• 2012

Although many studies have been conducted to extract buildings from airborne lidar data, most of them assume that all the boundaries of a building are straight line segments. This makes it difficult to model building boundaries containing curved segments correctly. This paper aims to model buildings containing curved segments as combination of straight lines and arcs. First, two sets of boundary points are extracted by adaptive convex hull algorithm and local convex hull algorithm with a larger radius. Then, arc segments are determined by average spacing of boundary points and intersection ratio of perpendicular lines. Finally, building boundary is modeled through regularization of least squares line or circle fitting. The experimental results showed that the proposed method can model the curved building boundaries as arc segments correctly by completeness of 69% and correctness of 100%. The approach will be utilized effectively to create automatically digital map that meets the conditions of the Korean digital mapping.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.547-548
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• 2023

내진 설계가 되어있지 않은 건물의 경우, 지진으로 인해 건물 붕괴 가능성이 높아지며 이로 인해 많은 인명 피해가 발생할 수 있다. 지진으로 인한 건물의 피해를 예측하고 이를 기반으로 취약점을 보완한다면 인명 피해를 줄일 수 있으므로 건물 피해 예측 모델에 대한 연구가 필요하다. 본 논문에서는 2015 년 네팔 대지진으로 인해 손상된 건물 데이터를 활용하여 Random Forest 와 Extreme Gradient Boosting 기계학습 분류 알고리즘을 사용하여 지진 피해 예측 모델의 정확도를 비교하였다.