• Spatial Information Research
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• v.16 no.3
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• pp.373-383
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• 2008

LiDAR, unlike satellite imagery and aerial photographs, which provides irregularly distributed three-dimensional coordinates of ground surface, enables three-dimensional modeling. In this study, urban area was classified based on 3D information collected by LiDAR. Morphological and spatial properties are determined by the ratio of ground and non-ground point that are estimated with the number of ground reflected point data of LiDAR raw data. With this information, the residential and forest area could be classified in terms of height and density of trees. The intensity of the signal is distinguished by a statistical method, Jenk's Natural Break. Vegetative area (high or low density) and non-vegetative area (high or low density) are classified with reflective ratio of ground surface.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.515-518
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• 2005

LiDAR(Light Detection and Ranging) with digital aerial photograph can be used to measure tree growth factors like total height, height of clear-length, dbh(diameter at breast height) and crown projection area. Delineating crown is an important process for identifying and numbering individual trees. Crown delineation can be done by watershed method to segment basin according to elevation values of DSMmax produced by LiDAR. Digital aerial photograph can be used to validate the crown projection area using LiDAR. And tree height can be acquired by image processing using window filter$(3cell\times3cell\;or\;5cell\times5cell)$ that compares grid elevation values of individual crown segmented by watershed.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.646-649
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• 2004

LiDAR(Light Detection and Ranging) system can record intensity data as well as range data. Recently, LiDAR intensity data is widely used for landcover classification, ancillary data of feature extraction, vegetation species identification, and so on. Since the intensity return value is associated with several factors, same features is not consistent for same flight or multiple flights. This paper investigated correlation between intensity and range data. Once the effects of range was determined, the single flight line normalization and the multiple flight line normalization was performed by an empirical function that was derived from relationship between range and return intensity

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.3
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• pp.148-157
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• 2012

Recently, people are getting more interested in green energy resource and environment friendly energy resource due to the lack of energy and global warming. This study produced a solar energy resource map using LiDAR(Light Detection And Ranging) data to check if it is utilized for spatial information technology and solar energy sectors that people pay more attentions to as new recycling energy. This study assigned Ulleungdo(Island) located in Gyeongsangbuk-do as a target area. This study created the contour line with 1 meter by newly photographing LiDAR and data processing. And using this contour line, this study built DEM(Digital Elevation Model) data with 1 meter. The incidence range depending on the altitude and azimuth of sun using DEM data is used to evaluate solar energy resource. This is expected to suggest an accurate method to evaluate more reliable and more precise information of new recycling energy resource by producing solar energy resource map based on accurate and precise spatial resolution data with 1 meter level.

• 한국공간정보시스템학회:학술대회논문집
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• 2005.05a
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• pp.427-433
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• 2005

인공적으로 조성한 저수지의 대부분은 유역면적이 넓고 집중강우로 인하여 매년 입자성 물질이 상당량 유입하는 편이며 이들의 장기간 축적으로 인하여 저수지 용량을 줄이고 수질관리에 어려움을 야기 시킨다. 따라서 이들에 대한 정화한 예측이 필요한 실정이지만 지표에서의 침식현상은 토양조건, 피복조건, 그리고 지형조건 등의 복합적 요소에 의하여 지배되기 때문에 정확한 유입량을 산정하기에 많은 어려움이 존재한다. 본 연구에서는 높은 정확도를 갖는 LiDAR(Light Detection and Ranging)기술을 이용하여 DEM, DSM을 제작하고 반사강도 데이터로부터 물질적 특성을 분류하여 연구지역내 범용토양유실공식(USLE; Universal Soil Loss Equation)에 의한 유입퇴적량을 산정하였다. 또한 이들 분포를 기준으로 퇴적물의 유입 가능성이 큰 위치를 파악하였으며 지형특성에 따른 퇴적물의 유입경로를 분석하였다.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.519-521
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• 2005

In recent years, LiDAR(Light Detection and Ranging) data has been widely used to prepare digital elevation models(DEMs) with the high spatial resolution of centi-meters. This paper investigated possible applications of LiDAR-derived DEMs in surface hydrology modeling, such as characterizing flow direction, identifying sub-basins in a watershed, and calculating variables like upstream contribution area. The results were compared to the results of the DEMs from conventional topographic maps.

• Korean Journal of Construction Engineering and Management
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• v.22 no.3
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• pp.40-51
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• 2021

MLS (Mobile Laser Scanning) which is a scanning method done by moving the LiDAR (Light Detection and Ranging) is widely employed to capture indoor PCD (Point Cloud Data) for floor plan generation in the AEC (Architecture, Engineering, and Construction) industry. The movement and rotation of LiDAR in the scanning phase cause deformation (i.e. skew) of PCD and impose a significant impact on quality of output. Thus, a de-skewing method is required to increase the accuracy of geometric representation. De-skewing methods which use position and pose information of LiDAR collected by IMU (Inertial Measurement Unit) have been mainly developed to refine the PCD. However, the existing methods have limitations on de-skewing PCD without IMU. In this study, a novel algorithm for de-skewing 2D PCD captured from MLS without IMU is presented. The algorithm de-skews PCD using scan matching between points captured from adjacent scan positions. Based on the comparison of the deskewed floor plan with the benchmark derived from TLS (Terrestrial Laser Scanning), the performance of proposed algorithm is verified by reducing the average mismatched area 49.82%. The result of this study shows that the accurate floor plan is generated by the de-skewing algorithm without IMU.

• 한국지형공간정보학회:학술대회논문집
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• 2004.10a
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• pp.123-128
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• 2004

최근 디지털 카메라(Digital camera), 다중/고분광 영상(Mumltispectral/Hyperspectral image), LiDAR(Light Detection and Ranging), InSAR(Interferometric SAR)와 같이 지상을 보다 상세하고 높은 정확도로 지상을 매핑할 수 있는 센서들이 출현하고 있다. 이러한 다양한 정보 취득 자료를 충분히 활용하여 통합하기 위해서는 영상에 대하여 정확한 기하보정 또는 정사영상의 제작과 LiDAR 자료와 같은 경우 평면위치의 오차를 조정하여 다중자료들 간의 정확한 지형보정(Coregistration)이 필요하다. 본 연구에서는 AIR-MS 자료를 이용하여 즉, 항공기로부터 취득한 LiDAR(Height와 강도(Intensity) 자료), digital camera을 통합하고, 기존의 컬러항공사진 및 1:1000 수치지도를 이용하여 3D GIS 자료의 생성을 시도하였다.

• Journal of agriculture & life science
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• v.50 no.3
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• pp.1-11
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• 2016

With increasing interest, there have been studies on LiDAR(Light Detection And Ranging)-based DEM(Digital Elevation Model) to acquire three dimensional topographic information. For producing LiDAR DEM with better accuracy, Filtering process is crucial, where only surface reflected LiDAR points are left to construct DEM while non-surface reflected LiDAR points need to be removed from the raw LiDAR data. In particular, the changes of input values for filtering algorithm-constructing parameters are supposed to produce different products. Therefore, this study is aimed to contribute to better understanding the effects of the changes of the levels of GroundFilter Algrothm's Mean parameter(GFmn) embedded in FUSION software on the accuracy of the LiDAR DEM products, using LiDAR data collected for Hwacheon, Yangju, Gyeongsan and Jangheung watershed experimental area. The effect of GFmn level changes on the products' accuracy is estimated by measuring and comparing the residuals between the elevations at the same locations of a field and different GFmn level-produced LiDAR DEM sample points. In order to test whether there are any differences among the five GFmn levels; 1, 3, 5, 7 and 9, One-way ANOVA is conducted. In result of One-way ANOVA test, it is found that the change in GFmn level significantly affects the accuracy (F-value: 4.915, p<0.01). After finding significance of the GFmn level effect, Tukey HSD test is also conducted as a Post hoc test for grouping levels by the significant differences. In result, GFmn levels are divided into two subsets ('7, 5, 9, 3' vs. '1'). From the observation of the residuals of each individual level, it is possible to say that LiDAR DEM is generated most accurately when GFmn is given as 7. Through this study, the most desirable parameter value can be suggested to produce filtered LiDAR DEM data which can provide the most accurate elevation information.

• KIISE Transactions on Computing Practices
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• v.23 no.10
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• pp.588-593
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• 2017

In this paper, we propose a LiDAR driver that virtualizes multiple inexpensive LiDARs (Light Detection and Ranging) with a smaller number of scan channels on an autonomous vehicle to replace a single expensive LiDAR with a larger number of scan channels. As a result, existing SLAM (Simultaneous Localization And Mapping) algorithms can be used with no modifications developed assuming a single LiDAR. In the paper, the proposed driver was implemented on the Robot Operating System and was evaluated with an existing SLAM algorithm. The results show that the proposed driver, combined with a filter to control the density of points in a 3D map, is compatible with the existing algorithm.