• Journal of the Korean Society for Precision Engineering
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• v.34 no.3
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• pp.191-197
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• 2017

Light detection and ranging (LiDAR) is one of the most efficient technologies to obtain the topographic and bathymetric map of coastal zones, superior to other technologies, such as sound navigation and ranging (SONAR) and synthetic aperture radar (SAR). However, the measurement results using LiDAR are vulnerable to environmental factors. To achieve a correspondence between the acquired LiDAR data and reality, error sources must be considered, such as the water surface slope, water turbidity, and seafloor slope. Based on the knowledge of those factors' effects, error corrections can be applied. We concentrated on the effect of the seafloor slope on LiDAR waveforms while restricting other error sources. A simulation regarding in-water beam scattering was conducted, followed by an investigation of the correlation between the seafloor slope and peak timing of return waveforms. As a result, an equation was derived to correct the depth error caused by the seafloor slope.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.1
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• pp.49-58
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• 2012

Buildings become complex and diverse with time. It is difficult to extract individual buildings using only an optical image, because they have similar spectral characteristics to objects such as vegetation and roads. In this study, we propose a method to extract building area and boundary through integrating airborne Light Detection and Ranging(LiDAR) data and aerial images. Firstly, a binary edge map was generated using Edison edge detector after applying Adaptive dynamic range linear stretching radiometric enhancement algorithm to the aerial image. Secondly, building objects on airborne LiDAR data were extracted from normalized Digital Surface Model and aerial image. Then, a temporary building areas were extracted by overlaying the binary edge map and building objects extracted from LiDAR data. Finally, some building boundaries were additionally refined considering positional accuracy between LiDAR data and aerial image. The proposed method was applied to two experimental sites for validation. Through error matrix, F-measure, Jaccard coefficient, Yule coefficient, and Overall accuracy were calculated, and the values had a higher accuracy than 0.85.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.5
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• pp.355-369
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• 2018

LiDAR (Light Detection And Ranging) strip adjustment is process to improve geo-referencing of the ALS (Airborne Laser Scanner) strips that leads to seamless LiDAR data. Multiple strips are required to collect data over the large areas, thus the strips are overlapped in order to ensure data continuity. The LSA (LiDAR Strip Adjustment) consists of identifying corresponding features and minimizing discrepancies in the overlapping strips. The corresponding features are utilized as control features to estimate transformation parameters. This paper applied SURF (Speeded Up Robust Feature) to identify corresponding features. To improve determination of the corresponding feature, false matching points were removed by applying three schemes: (1) minimizing distance of the SURF feature vectors, (2) selecting reliable matching feature with high cross-correlation, and (3) reflecting geometric characteristics of the matching pattern. In the strip adjustment procedure, corresponding points having large residuals were removed iteratively that could achieve improvement of accuracy of the LSA eventually. Only a few iterations were required to reach reasonably high accuracy. The experiments with simulated and real data show that the proposed method is practical and effective to airborne LSA. At least 80 % accuracy improvement was achieved in terms of RMSE (Root Mean Square Error) after applying the proposed schemes.

• Journal of Advanced Navigation Technology
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• v.12 no.6
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• pp.548-553
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• 2008

While in the past map-making process by field survey devices such as MicroStation needs more time relatively, we can make more precise map effectively with airbone LiDAR and GPS devices. Also the data, captured by LiDAR, are very large in size and so it needs to use Relational DBMS to manage and process LiDAR data. In this study we propose how to store and manage LiDAR data using RDBMS.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.24 no.2
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• pp.209-215
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• 2006

Shoreline changes its shapes and attribution dynamically by natural, unnatural acts and is the most information for country. These shorelines can apply to framework data of MGIS (Marine Geographic Information System), and they are getting important to implement a phase of monitoring around coastal areas. This study proposed an algorithm automatically extracting shorelines to use a new developed LiDAR (Light Detection And Ranging) data which is applying in ocean and coastal areas. Then, in result, it was compared to shorelines which is derived from ground survey. In result, it shows stable shorelines in various coast areas such as nature, artificial coast. Additionally, and a possibility of shoreline extraction through LiDAR data.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.642-645
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• 2007

Mounted in aircraft, LiDAR (Light Detection And Ranging) technology uses pulses of light to collect data about the terrain below. The main objective of this study was to extract reliable the individual tree and analysis techniques to facilitate the used LiDAR data for estimating tree crown diameter by measuring individual trees identifiable on the three dimensional LiDAR surface. In addition, this study can be quantitative analysis of individual tree through the canopy parameter.

• 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.

• Korean Journal of Remote Sensing
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• v.28 no.3
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• pp.307-318
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• 2012

To understand forest structures, the Geoscience Laser Altimeter System (GLAS) instrument have been employed to measure and monitor forest canopy with feasibility of acquiring three dimensional canopy structure information. This study tried to examine the potential of GLAS dataset in measuring forest canopy structures, particularly maximum canopy height estimation. To estimate maximum canopy height using feasible GLAS dataset, we simply used difference between signal start and ground peak derived from Gaussian decomposition method. After estimation procedure, maximum canopy height was derived from airborne Light Detection and Ranging (LiDAR) data and it was applied to evaluate the accuracy of that of GLAS estimation. In addition, several influences, such as topographical and biophysical factors, were analyzed and discussed to explain error sources of direct maximum canopy height estimation using GLAS data. In the result of estimation using direct method, a root mean square error (RMSE) was estimated at 8.15 m. The estimation tended to be overestimated when comparing to derivations of airborne LiDAR. According to the result of error occurrences analysis, we need to consider these error sources, particularly terrain slope within GLAS footprint, and to apply statistical regression approach based on various parameters from a Gaussian decomposition for accurate and reliable maximum canopy height estimation.

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1709-1718
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• 2021

The waveform data of the Airborne Bathymetric LiDAR (ABL; LiDAR: Light Detection And Ranging) system provides data with improved accuracy, resolution, and reliability compared to the discrete-return data, and increases the user's control over data processing. Furthermore, we are able to extract additional information about the return signal. Waveform decomposition is a technique that separates each echo from the received waveform with a mixture of water surface and seabed reflections, waterbody backscattering, and various noises. In this study, a new waveform decomposition technique based on a Gaussian model was developed to improve the point extraction performance from the ABL waveform data. In the existing waveform decomposition techniques, the number of decomposed echoes and decomposition performance depend on the peak detection results because they use waveform peaks as initial values. However, in the study, we improved the approximation accuracy of the decomposition model by adding the estimated potential peak candidates to the initial peaks. As a result of an experiment using waveform data obtained from the East Coast from the Seahawk system, the precision of the decomposition model was improved by about 37% based on evaluating RMSE compared to the Gaussian decomposition method.

• 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.