• 한국지형공간정보학회:학술대회논문집
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• 2004.10a
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• pp.141-146
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• 2004

최근 들어 국내에서도 홍수에 의한 재산과 인명피해를 최소화하기 위해 지역특성에 알맞은 홍수지도를 제작 중에 있으며, 주로 LiDAR를 이용하여 홍수지도 지형자료를 구축하고 있다. 그러나 이에 많은 시간과 비용이 소요되기 때문에 이미 전국적으로 구축된 수치지형도를 이용한 홍수지도 지형자료 구축의 가능성과 타당성을 검증의 필요성이 제기되고 있다. 이에 따라 본 연구에서는 수치지형도를 이용한 홍수지도제작시 가장 핵심이 되는 정확한 지형자료구축을 위해서 Breakline처리기법과 하천종횡단자료 연계방안을 중심으로 구리시 일부지역을 대상으로 DEM을 시범제작 하였다. 수치지형도와 LiDAR를 이용하여 구축한 DEM을 검수점을 통한 RMSE오차를 이용하여 수직위치정확도를 비교분석하였다. 분석을 위하여 선행연구(홍수지도제작, 2002)에서 검수점으로 사용한 9점과 제방부분의 실측한 9점을 본 연구의 검수점으로 사용하였다. 비교 결과 RMSE가 수치지형도 DEM의 경우 ${\pm}2.658m$이고, LiDAR DEM의 경우 ${\pm}3.430m$로 나타났다. 두 자료 모두 알려진 오차범위보다 훨씬 높은 오차가 발생함을 알 수 있었다. 향후 수치지형도를 이용한 효율적인 홍수지도 지형자료 구축을 위해서는 수치지형도의 신속하고 지속적인 갱신이 필요할 것이며, 현재 도시지역에만 구축되어 있는 1:1,000 수치지형도를 주변 하천지역까지 확대해서 구축해야 할 필요성이 있을 것으로 사료된다. 아울러 도입초기단계의 LiDAR 측량기술의 보급과 관련모델의 기술의 발달로 인하여 정확도 높은 DEM이 요구된다면 고밀도의 방대한 양의 LiDAR 자료로 DEM을 구축하는 것이 바람직하다고 사료된다.및 이용대책을 수립하는 데 활용될 수 있다., $1,000-2,000{\mu}g\;g^{-1}$), 나머지 177종 식물은 살초활성을 나타내지 않았다. 높은 살초활성을 나타낸 식물로부터 분리되는 천연활성물질들은 향후 새로운 제초제 개발을 위한 모화합물 제공, 상호대립억제 작용성을 갖는 작물 품종 개발 혹은 개량에의 활용, 그리고 친환경 유기농업용 잡초방제에의 활용이 기대된다.내(皮膚上皮組織內)의 Langerhans cell내(內)의 Birbeck granule에 비(比)해 수적(數的)으로 현저히 감소(減少)되어 있었다. 그러나 Thy-1 양성(陽性) dendritic cell에서 볼 수 있는 dense-core 과립(顆粒)은 별변화(別變化)없이 쉽게 관찰(觀察)될 수 있었다. 조직배양(組織培養)을 한 견(犬)의 keratinocyte에 대(對)해 사람 pemphigus vulgaris의 항체(抗體)로 반응(反應)시킨 후 protein-A gold(15 nm)로 표식(標識)시킨 바 제일 바깥 상층(上層)의 keratinocyte에 있어서 세포막표면(細胞膜表面)을 따라 표식(標識)되어 세포막항원(細胞膜抗元)을 나타내었으며, 이와 같은 소견(所見)으로 미루어 정상피부(正常皮膚) 중층편평상피세포(重層扁平上皮細胞)에서도 동일(同一)한 소견(所見)을 관찰(觀察)할 수 있다고 본다.al remnants, Resorption of fetus로 관찰된 것이다. Fetal death는 수정후 $14{\sim}18$일까지의 사망으로써 Maceration of fetus로 관찰되는 것이다. 통계학적 분석은 각 Group의 착상 을과 자궁 내 사망 율을 산출할 때에는 각 임신마우스에 따라 발생빈도가 크

• The Journal of Korea Robotics Society
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• v.10 no.1
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• pp.33-41
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• 2015

Recent developments in robotics and intelligent vehicle area, bring interests of people in an autonomous driving ability and advanced driving assistance system. Especially fully automatic parking ability is one of the key issues of intelligent vehicles, and accurate parked vehicles detection is essential for this issue. In previous researches, many types of sensors are used for detecting vehicles, 2D LiDAR is popular since it offers accurate range information without preprocessing. The L shape feature is most popular 2D feature for vehicle detection, however it has an ambiguity on different objects such as building, bushes and this occurs misdetection problem. Therefore we propose the accurate vehicle detection method by using a 3D complete vehicle model in 3D point clouds acquired from front inclined 2D LiDAR. The proposed method is decomposed into two steps: vehicle candidate extraction, vehicle detection. By combination of L shape feature and point clouds segmentation, we extract the objects which are highly related to vehicles and apply 3D model to detect vehicles accurately. The method guarantees high detection performance and gives plentiful information for autonomous parking. To evaluate the method, we use various parking situation in complex urban scene data. Experimental results shows the qualitative and quantitative performance efficiently.

• Journal of KIBIM
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• v.7 no.4
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• pp.8-20
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• 2017

When it comes to set up the BIM through the reverse engineering, the level of detail(LoD) required for finalized outcomes is different from each purpose. Therefore, it is necessary to establish some concrete criteria which describe the definition of LoDs on 3D modeling for the purpose of each reverse engineering. This research shows the criteria of the 1) positional accuracy, 2) generalization level, 3) scale level, 4) scope of description, and 5) the area available for application by classifying LoD from 1 to 6 on 3D modeling for each purpose of reverse engineering. Moreover, through applying those criteria for the 3D point cloud dataset of building made by terrestrial LiDAR, this research finds out the working hour of 3D modeling of reverse engineering by each LoDs according to defined LoD criteria for each level. It is expected that those findings, how those criteria of LoD on reverse engineering are utilized for modeling-workers to decide whether the outcomes can be suitable for their budget, applicable fields or not, would contribute to help them as a basic information.

• Korean Journal of Remote Sensing
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• v.34 no.1
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• pp.45-74
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• 2018

Landslide is a natural hazard that threats lives and properties in many areas around the world. Landslides are difficult to recognize, particularly in rainforest regions. Thus, an accurate, detailed, and updated inventory map is required for landslide susceptibility, hazard, and risk analyses. The inconsistency in the results obtained using different features selection techniques in the literature has highlighted the importance of evaluating these techniques. Thus, in this study, six techniques of features selection were evaluated. Very-high-resolution LiDAR point clouds and orthophotos were acquired simultaneously in a rainforest area of Cameron Highlands, Malaysia by airborne laser scanning (LiDAR). A fuzzy-based segmentation parameter (FbSP optimizer) was used to optimize the segmentation parameters. Training samples were evaluated using a stratified random sampling method and set to 70% training samples. Two machine-learning algorithms, namely, Support Vector Machine (SVM) and Random Forest (RF), were used to evaluate the performance of each features selection algorithm. The overall accuracies of the SVM and RF models revealed that three of the six algorithms exhibited higher ranks in landslide detection. Results indicated that the classification accuracies of the RF classifier were higher than the SVM classifier using either all features or only the optimal features. The proposed techniques performed well in detecting the landslides in a rainforest area of Malaysia, and these techniques can be easily extended to similar regions.

• Spatial Information Research
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• v.17 no.3
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• pp.381-387
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• 2009

This study investigates the use of geomorphic analysis results obtained from high-resolution LiDAR-derived DEM. The results of analysis, slope angle and eigenvalue ratio (ER) were derived from the DEM for 3 landslide and 1 non-landslide occurrence area. Results of this study highlighted the importance of geomorphic analysis in characterizing landslide feature as well as the various contents in their future occurrence and activity. The relationship between the results of geomorphic analysis and landslides are well expressed in this paper.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.739-743
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• 2010

본 연구에서는 확산파 기반의 2차원 침수해석 모형을 이용하여 울산광역시 태화강 유역에 대하여 침수시 건물 안으로의 흐름은 없다는 가정 하에서 건물로 인한 흐름의 양상, 침수심, 침수위등을 분석하였다. 지형자료는 최근 대도시를 중심으로 구축되고 있는 1m 간격으로 수집된 LiDAR 자료를 바탕으로 10m간격의 정형격자를 통하여 지형자료를 생성하였으며, 수치지도로부터 추출된 건물을 ArcView 등의 GIS Tool을 활용하여 LiDAR 자료와 합성하여 2차원 침수해석에 적용되는 지형자료를 구성하였다. 200년 빈도의 확률강우에 대한 유출해석 결과를 이용하여 FLDWAV 모형을 적용한 태화강에 대한 1차원 하천해석을 실시하였고, 제방파제에 대한 가상의 시나리오를 생성하여 파제에 따른 외수범람에 대한 2차원 침수해석을 실시하였으며, 침수해석 결과를 각 시간별로 가시화함으로써 효율적이며 정확한 침수해석 방법을 제안하고자 하였다. 침수해석 결과에 대한 분석을 통하여 침수면적에 따른 적합도가 건물의 영향을 고려한 경우와 그렇지 않은 경우를 비교한 결과 90%이하로 떨어지는 것을 확인하였고, 침수심과 침수위에 대한 분석을 통하여 침수심은 건물 영향 고려시 낮게 산정되나 침수위로 고려시 높은 수위 값을 나타내는 것을 확인하였다.

• Tunnel and Underground Space
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• v.30 no.1
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• pp.76-86
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• 2020

In this study, a small autonomous driving robot was developed for underground mines using the Light Detection and Ranging (LiDAR) sensor. The developed robot measures the distances to the left and right wall surfaces using the LiDAR sensor, and automatically controls its steering to drive along the centerline of mine tunnel. A field experiment was conducted in an underground amethyst mine to test the driving performance of developed robot. During five repeated driving tests, the robot showed stable driving performance overall. There were no collision accidents with the wall of mine tunnel.

• Korean Journal of Remote Sensing
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• v.24 no.4
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• pp.333-340
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• 2008

For the indoor spatial modeling by terrestrial LiDAR and the analyzing its positional accuracy result, two terrestrial LiDARs which have different specification each other were used at test site. This paper shows disparity of accuracy between (1) the structural coordinate transformation by point cloud unit using control points and (2) the relative registration among all point cloud units then structural coordinate transformation in bulk, under condition of limited number of control points. As results, the latter had smaller size and distribution of errors than the former although different specifications and acquistion methods are used.

• Korean Journal of Remote Sensing
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• v.34 no.6_1
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• pp.1009-1024
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• 2018

With the increased use of LiDAR (Light Detection and Ranging) that can obtain over millions of point dataset, methodologies for efficient search and dimensionality reduction for the point cloud became a crucial technique. The existing octree-based "parametric algorithm" has proved its efficiency and contributed as a part of PCL (Point Cloud Library). However, the implementation of the algorithm on GPU (Graphics Processing Unit) is considered very difficult because of structural constraints of the octree implemented in PCL. In this paper, we present a method for the parametric algorithm on GPU environment and implement a projection of the queried points on four directions with an improved noise reduction.

• Journal of Cadastre & Land InformatiX
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• v.46 no.1
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• pp.87-100
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• 2016

The acquisition of the forest resource information has depended on a partial sampling method or aerial photographs which demand a lot of effort and time because of the vast areas and the difficult approach. For the acquisition of the forest resource information, there have been the optical remote-sensing and the multi-spectrum image to offer only horizontal distributions of trees, but a new technological approach, such as Airborne LiDAR, is more necessary to acquire directly three dimensional information related to the forest terrains and trees' features. This paper proposes an algorithm for the forest information extraction such as trees' individual numbers and the heights of trees by using LiDAR data. Especially, this proposed algorithm adopts a region growing method for the extraction of the vegetation-point and extracts the forest information using morphological features of trees.