• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2009.04a
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• pp.115-117
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• 2009

Terrestrial Laser Scanner and Airborne Laser Scanning is one of the state of art surveying equipments. So This study deals with the combined use of mobile TLS(Terrestrial Laser Scanner) with ALS(Airborne Laser Scanning) to extract shoreline's topography information. These two systems have their own pros and cons. Mobile TLS can capture the facades of a low story building along the shoreline fast and quickly. Meanwhile, Due to viewpoint restrictions of ALS data collection, the amount of detail, which is available for the building facades is very limited. Therefore, it is recommended that the co-registration and geo-referencing methods of both two should be developed and the application of both system for shoreline mapping also should be investigated.

• Journal of Korean Society for Geospatial Information Science
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• v.14 no.4 s.38
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• pp.37-44
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• 2006

To use surveying data obtained from different sensors and different techniques, it is a pre-requite step that register them in a common coordinate system. For this purpose, we developed methodologies to register airborne photos, ALS (Airborne Laser Scanning) data and digital maps. To achieve this, conjugate features from these data should be extracted in advance. In this study, linear features are chosen as conjugate features. Based on such a selection strategy, a simple and robust algorithm is proposed for extracting such features from ALS data. Then, to register them, observation equations are established from similarity measurements of the extracted features and the results was evaluated statistically. The results clearly demonstrate that the proposed algorithms are appropriate to register these data.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.141-144
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• 2008

Many studies have been conducted on extracting buildings from ALS(Airborne Laser Scanning) data. After segmentation or classification of building points, additional steps such as generalization is required to get straight boundary lines that better approximate the real ones. In much research, orthogonal constraints are used to improve accuracies and qualities. All the lines of the building boundaries are assumed to be either parallel or perpendicular mutually. However, this assumption is not valid in many cases and more complex shapes of buildings have been increased. A new algorithm is presented that is applicable to various complex buildings. It consists of three steps of boundary tracing, grouping, and regularization. The performance of our approach was evaluated by applying the algorithm to some buildings and the results showed that our proposed method has good potential for extracting building boundaries of various shapes.

• ETRI Journal
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• v.25 no.2
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• pp.109-120
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• 2003

Though the airborne laser scanning (ALS) technique is becoming more popular in many applications, horizontal accuracy of points scanned by the ALS is not yet satisfactory when compared with the accuracy achieved for vertical positions. One of the major reasons is the drift that occurs in the inertial measurement unit (IMU) during the scanning. This paper presents an algorithm that adjusts for the error that is introduced mainly by the drift of the IMU that renders systematic differences between strips on the same area. For this, we set up an observation equation for strip-wise adjustments and completed it with tie point and control point coordinates derived from the scanned strips and information from aerial photos. To effectively capture the tie points, we developed a set of procedures that constructs a digital surface model (DSM) with breaklines and then performed feature-based matching on strips resulting in a set of reliable tie points. Solving the observation equations by the least squares method produced a set of affine transformation equations with 6 parameters that we used to transform the strips for adjusting the horizontal error. Experimental results after evaluation of the accuracy showed a root mean squared error (RMSE) of the adjusted strip points of 0.27 m, which is significant considering the RMSE before adjustment was 0.77 m.

• 한국공간정보시스템학회:학술대회논문집
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• 2005.05a
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• pp.267-272
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• 2005

최근 항공레이저스캐닝(ALS)은 높은 정확도와 경제성을 이유로 지형정보를 획득하는 탁월한 수단으로 주목받고 있다. ALS에 의해 수집되는 고도자료는 DSM, DEM 제작에 유용하게 이용된다. ALS는 고도자료 이외에 지표면의 물질적 특성을 나타내는 반사강도를 획득한다. 그러나 반사강도는 노이즈로 인해 널리 이용되지 못하고 있으며, 노이즈의 주원인은 반사각으로 알려져 있다. 따라서 본 연구는 센서 위치정보와 ALS 고도자료를 이용하여 반사각을 이용하여 반사강도를 보정하는 방법을 제안하였다 여기에는 ${\theta}$의 각도로 입사한 레이저의 강도는 수직으로 입사한 레이저의 강도보다 $sin{\theta}$만큼 감소한다는 물리학적 원리가 이용되었다 반사각은 지표면과 레이저가 이루는 각으로, 센서와 측정점 사이의 각과 지표면의 경사각의 두 단계로 나누었다. 방법의 적합 여부를 확인하기 위해 적외선 영역에서 분리도가 잘 이루어지는 아스팔트, 휴경지(토양), 콘크리트, 수목의 네 가지 검증영역을 선정하여 보정된 반사강도와 보정 전의 반사강도를 비교하였다. 모든 영역에서 반사강도가 증가하였으며 특히 콘크리트와 수목에서의 증가가 두드러졌다. 보정을 통해 네 영역에서 반사강도의 분리도가 향상됨을 물론 그 크기가 '아스팔트<토양<콘크리트<수목'으로 나타나는 이론적인 경향과 유사함을 확인할 수 있다.

• Journal of the Korean Association of Geographic Information Studies
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• v.6 no.3
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• pp.95-106
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• 2003

This study evaluated the architectural density of urban district using airborne laser scanning(ALS) that is a method used in urban planning, water resources and disaster prevention with high interest recently. First, digital elevation model(DEM) and digital surface model(DSM) was constructed from Light detection and ranging(LiDAR). For getting the height of building, ZONALMEAN filter was used in DEM and ZONALMAJORITY filter was used in DSM. This study compared the floor from filtering with the floor from survey and got standard error, which is ${\pm}0.199$ floor. Also, through the overlay and statistical analysis of total-area layer and zone layer, we could present floor area ratio by zone. As a result of comparison with floor area ratio between airborne laser scanning data and survey data, the standard error of floor area ratio shows ${\pm}2.68%$. Therefore, we expect that airborne laser scanning data can be a very efficient source to decision makers who set up landuse plan in near future.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.24 no.5
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• pp.389-397
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• 2006

The purpose of the present paper is to offer an analysis of LiDAR data processing and three dimensional terrain for Geographic Information System (CIS) applications. Generally, LiDAR survey is the method which obtains quantitative and qualitative information of the terrain using airborne laser scanning (ALS). We will get a most topographic data at a Triangular Irregular Network (TIN), Digital Surface Model (DSM) and Digital Elevation Model (DEM) using LiDAR data. We examined many factors such as visibility, hillshade, aspect and slope using DEM and DSM. The analyzing results obtained from each item are thought to be regarded as leading factors in the terrain analysis. It is to be hoped that LiDAR survey will contribute a new approach to the terrain analysis.

• Korean Journal of Geomatics
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• v.2 no.2
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• pp.123-130
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• 2002

LiDAR (Light Detection And Ranging) system has a profound impact on geoinformatics. The laser mapping system is now recognized as being a viable system to produce the digital surface model rapidly and efficiently. Indeed the number of its applications and users has grown at a surprising rate in recent years. Interest is now focused on the reconstruction of buildings in urban areas from LiDAR data. Although with present technology objects can be extracted and reconstructed automatically using LiDAR data, the quality issue of the results is still major concern in terms of geometric accuracy. It would be enormously beneficial to the geoinformatics industry if geometrically accurate modeling of topographic surface including man-made objects could be produced automatically. The objectives of this study are to reconstruct buildings using airborne LiDAR data and to evaluate accuracy of the result. In these regards, firstly systematic errors involved with ALS (Airborne Laser Scanning) system are introduced. Secondly, the overall LiDAR data quality was estimated based on the ground check points, then classifying the laser points was performed. In this study, buildings were reconstructed from the classified as building laser point clouds. The most likely planar surfaces were estimated by the least-square method using the laser points classified as being planes. Intersecting lines of the planes were then computed and these were defined as the building boundaries. Finally, quality of the reconstructed building was evaluated.

• 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 the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.4
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• pp.359-365
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• 2011

This study aims at filtering ALS points into ground and non-ground effectively through labeling and window based algorithm by utilizing 2D adjacency based on scan line. Firstly, points adjacency is constructed through minimal search based on scan line. Connected component labeling algorithm is applied to classify raw ALS points into ground and non-ground by utilizing the adjacency structure. Then, some small objects are removed by morphology filtering, and isolated ground points are restored by IDW estimation. The experimental results shows that the method provides good filtering performance( about 97% accuracy) for diverse sites, and the overall processing takes less time than converting raw data into TIN or raster grid.