• 해양환경안전학회지
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• 제19권3호
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• pp.233-240
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• 2013

Jakarta is the capital city of Indonesia which has problems of land subsidence with the rates of about 1 to 15 cm/year, up to 20-25 cm/year. The study has examined the land subsidence in Pantai Mutiara, Jakarta Bay which is a reclaimed area by using the Terrestrial LIDAR survey technique. The Terrestrial LIDAR survey results show that the survey site has mean elevation of 0.24 m with the highest elevation of 0.93 m and lowest - 0.35 m. Considering that AHHW (approximate highest high water) is 0.51 m, many areas of the survey site are lying below the AHHW. Pantai Mutiara area is showing various subsidence rates depending on sites although the site is relatively narrow and small (about 1 $km^2$). There is elevation differences of almost 1m within the site. In this study, key information including topography, dike height distribution, and future coastal flooding risk of the survey area was able to be provided by Terrestrial LIDAR survey conducted only once. Especially, as the 3D precision topography effectively conveys important messages relating to vulnerability of the site, policy makers and stakeholders can easily understand the situation of the site.

• 신재생에너지
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• 제7권2호
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• pp.43-50
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• 2011

The only practical way to measure wind resource at high-altitude over 100 m above ground for a feasibility study on a high-rise building integrated wind turbine might be ground-based remote sensing. The remote-sensing campaign was performed at a 145 m-building roof in Jamsil where is a center of metropolitan city Seoul. The campaign aimed uncertainty assessment of Leosphere WindCube LIDAR and Scintec MPAS SODAR through a mutual comparison. Compared with LIDAR, the data availability of SODAR was about 2/3 at 550 m altitude while both showed over 90% under 400 m, and it is shown that the data availability decrease may bring a distortion of statistical analysis. The wind speed measurement of SODAR was fitted to a slope of 0.92 and $R^2$ of 0.90 to the LIDAR measurement. The relative standard deviation of wind speed difference and standard deviation of wind direction difference were evaluated to be 30% and 20 degrees, respectively over the whole measurement heights.

• 한국GIS학회:학술대회논문집
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• 한국GIS학회 2010년도 춘계학술대회
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• pp.298-302
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• 2010

본 논문은 라이다영상으로부터 지표면의 형상을 분석하기 위하여 표변의 차분적 기하 특성을 이용하는 기법을 제시한다. 항공라이다영상은 지형지물의 고도값을 신속하게 제공하지만 영상으로부터 지형, 도로, 수목, 건물 등 의미 있는 객체를 추출하는 과정이 필요하다. 이를 위해서는 라이다영상의 고유정확도를 토대로 각 지형지물이 라이다영상 내 표현된 지표면의 특성을 분석할 필요가 있다. 지표면의 기하학적 특성을 분석하기 위하여 본 논문은 Hessian 행렬로부터 유도된 고유값을 이용한다. 실험을 위하여 대학 캠퍼스 건물을 포함하는 약 1미터 간격의 라이다영상을 처리한 결과, 제안 기법으로 지표면특성을 효과적으로 분석해낼 수 있었다.

• 대한공간정보학회지
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• 제15권1호통권39호
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• pp.17-22
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• 2007

본 연구에서는 선행 연구에서 제시한 스캔라인을 이용한 LIDAR 포인트 cloud의 분리과정 중 분리된 포인트 군집간인접 관계를 인식할 수 있는 기능을 추가하여 분리된 건물요소를 인식하고 재결합하였다. 아울러 군집간 인접 특성을 활용하여 지면 포인트 군집을 인식하기 위한 방법론을 제시하였다. 실험 결과 포인트 cloud 분리 과정에 군집간 인접 관계 인식 기능을 추가하더라도 처리 성능이 저하되지 않았으며 후처리를 통하여 건물 요소를 결합하여 온전한 형태의 건물 포인트 군집을 형성함과 더불어 지면 포인트 군집도 인식할 수 있음을 확인하였다.

• 대한공간정보학회지
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• 제14권3호
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• pp.13-22
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• 2006

3차원 지형공간정보의 활용범위가 확대되면서 다양한 형태와 크기의 건물들이 존재하는 광범위한 도시지역에 대하여 신속하고 정확하게 실세계에 가까운 3차원 건물 모형을 구축하는 기술 개발이 요구되고 있다. 기존의 항공사진이나 고해상 위성영상을 이용한 3차원 도시 지형공간의 구축 연구와는 달리 최근에는 높은 정밀도를 가진 항공 LIDAR 관측 자료를 활용한 3차원 건물 복원에 관한 연구가 활발히 진행되고 있다. 본 연구에서는 Zero-crossing의 특성을 갖는 LoG 연산자를 이용하여 높이별로 건물의 경계선 정보를 추출하고 Douglas-Peucker 알고리즘을 이용하여 경계선을 직선화하여 건물의 경계선을 정제하고 3차원으로 건물을 복원하는 기법을 제안하였다.

• ETRI Journal
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• 제33권4호
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• pp.506-516
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• 2011

In this paper, we develop a registration method to eliminate the geometric inconsistency between the stereo-images and light detection and ranging (LIDAR) data obtained by an airborne multisensor system. This method consists of three steps: registration primitive extraction, correspondence establishment, and exterior orientation parameter (EOP) adjustment. As the primitives, we employ object points and linked edges from the stereo-images and planar patches and intersection edges from the LIDAR data. After extracting these primitives, we establish the correspondence between them, being classified into vertical and horizontal groups. These corresponding pairs are simultaneously incorporated as stochastic constraints into aerial triangulation based on the bundle block adjustment. Finally, the EOPs of the images are adjusted to minimize the inconsistency. The results from the application of our method to real data demonstrate that the inconsistency between both data sets is significantly reduced from the range of 0.5 m to 2 m to less than 0.05 m. Hence, the results show that the proposed method is useful for the data fusion of aerial images and LIDAR data.

• 대한임베디드공학회논문지
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• 제12권1호
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• pp.43-62
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• 2017

Mobile pulse scanning Light Detection And Ranging (LIDAR) are essential components of intelligent vehicles capable of autonomous travel. Obstacle detection functions of autonomous vehicles require very low failure rates. With the increasing number of autonomous vehicles equipped with scanning LIDARs to detect and avoid obstacles and navigate safely through the environment, the probability of mutual interference becomes an important issue. The reception of foreign laser pulses can lead to problems such as ghost targets or a reduced signal-to-noise ratio. This paper will show the probability that any two scanning LIDARs will interfere mutually by considering spatial and temporal overlaps. We have conducted four experiments to investigate the occurrence of the mutual interference between scanning LIDARs. These four experimental results introduced the effects of mutual interference and indicated that the interference has spatial and temporal locality. It is hard to ignore consecutive mutual interference on the same line or the same angle because it is possible the real object not noise or error. It may make serious faults because the obstacle detection functions of autonomous vehicle rely on heavily the scanning LIDAR.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.241-243
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• 2003

This paper presents an algorithm that automatically extracts buildings among many different features on the earth surface by fusing LIDAR data with panchromatic aerial images. The proposed algorithm consists of three stages such as point level process, polygon level process, parameter space level process. At the first stage, we eliminate gross errors and apply a local maxima filter to detect building candidate points from the raw laser scanning data. After then, a grouping procedure is performed for segmenting raw LIDAR data and the segmented LIDAR data is polygonized by the encasing polygon algorithm developed in the research. At the second stage, we eliminate non-building polygons using several constraints such as area and circularity. At the last stage, all the polygons generated at the second stage are projected onto the aerial stereo images through collinearity condition equations. Finally, we fuse the projected encasing polygons with edges detected by image processing for refining the building segments. The experimental results showed that the RMSEs of building corners in X, Y and Z were ${\pm}$8.1㎝, ${\pm}$24.7㎝, ${\pm}$35.9㎝, respectively.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.113-119
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• 2003

Building information is extremely important for many applications within the urban environment. Sufficient techniques and user-friendly tools for information extraction from remotely sensed imagery are urgently needed. This paper presents an automatic and manual approach for extracting footprints of buildings in urban areas from airborne Light Detection and Ranging (LIDAR) data. First a digital surface model (DSM) was generated from the LIDAR point data. Then, objects higher than the ground surface are extracted using the generated DSM. Based on general knowledge on the study area and field visits, buildings were separated from other objects. The automatic technique for extracting the building footprints was based on different window sizes and different values of image add backs, while the manual technique was based on image segmentation. A comparison was then made to see how precise the two techniques are in detecting and extracting building footprints. Finally, the results were compared with manually digitized building reference data to conduct an accuracy assessment and the result shows that LIDAR data provide a better shape characterization of each buildings.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2015년도 추계학술발표대회
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• pp.10-11
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• 2015

최근 자율 주행 분야의 연구에서 LIDAR를 활용한 분류 기법들이 연구되고 있다. 그러나 2D 영상 처리와 비교하여, 대량의 3D 포인트를 사용하는 분류 알고리즘의 성능을 평가하기 위한 지상 검증자료를 쉽게 획득하기 어렵다. 본 연구는 LIDAR를 가상 공간에서 시뮬레이션 함으로써 감지한 물체의 정보를 기록함으로써 3D 포인트 클라우드를 사용하는 다양한 분류 알고리즘의 검증을 위한 지상검증자료를 생성하는 기법을 설명한다. 본 기법은 실제 LIDAR를 사용하는 것보다 적은 비용으로 다양한 환경에서의 분류 알고리즘 성능 검증을 가능하게 한다.