• Title/Summary/Keyword: 항공수심라이다

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Segmentation of Seabed Points from Airborne Bathymetric LiDAR Point Clouds Using Cloth Simulation Filtering Algorithm (항공수심라이다 데이터 해저면 포인트 클라우드 분리를 위한 CSF 알고리즘 적용에 관한 연구)

  • Lee, Jae Bin;Jung, Jae Hoon;Kim, Hye Jin
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.38 no.1
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    • pp.1-9
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    • 2020
  • ABL (Airborne Bathymetric LiDAR) is an advanced survey technology that uses green lasers to simultaneously measure the water depths and oceanic topography in coastal and river areas. Seabed point cloud extraction is an essential prerequisite to further utilizing the ABL data for various geographic data processing and applications. Conventional seabed detection approaches often use return waveforms. However, their limited accessibility often limits the broad use of the bathymetric LiDAR (Light Detection And Ranging) data. Further, it is often questioned if the waveform-based seabed extraction is reliable enough to extract seabed. Therefore, there is a high demand to extract seabed from the point cloud using other sources of information, such as geometric information. This study aimed to assess the feasibility of a ground filtering method to seabed extraction from geo-referenced point cloud data by using CSF (Cloth Simulation Filtering) method. We conducted a preliminary experiment with the RIGEL VQ 880 bathymetric data, and the results show that the CSF algorithm can be effectively applied to the seabed point segmentation.

Water Depth and Riverbed Surveying Using Airborne Bathymetric LiDAR System - A Case Study at the Gokgyo River (항공수심라이다를 활용한 하천 수심 및 하상 측량에 관한 연구 - 곡교천 사례를 중심으로)

  • Lee, Jae Bin;Kim, Hye Jin;Kim, Jae Hak;Wie, Gwang Jae
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.39 no.4
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    • pp.235-243
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    • 2021
  • River surveying is conducted to acquire basic geographic data for river master plans and various river maintenance, and it is also used to predict changes after river maintenance construction. ABL (Airborne Bathymetric LiDAR) system is a cutting-edge surveying technology that can simultaneously observe the water surface and river bed using a green laser, and has many advantages in river surveying. In order to use the ABL data for river surveying, it is prerequisite step to segment and extract the water surface and river bed points from the original point cloud data. In this study, point cloud segmentation was performed by applying the ground filtering technique, ATIN (Adaptive Triangular Irregular Network) to the ABL data and then, the water surface and riverbed point clouds were extracted sequentially. In the Gokgyocheon river area, Chungcheongnam-do, the experiment was conducted with the dataset obtained using the Leica Chiroptera 4X sensor. As a result of the study, the overall classification accuracy for the water surface and riverbed was 88.8%, and the Kappa coefficient was 0.825, confirming that the ABL data can be effectively used for river surveying.

Waveform Decomposition of Airborne Bathymetric LiDAR by Estimating Potential Peaks (잠재적 피크 추정을 통한 항공수심라이다 웨이브폼 분해)

  • Kim, Hyejin;Lee, Jaebin;Kim, Yongil;Wie, Gwangjae
    • 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.

Coastal Erosion Time-series Analysis of the Littoral Cell GW36 in Gangwon Using Seahawk Airborne Bathymetric LiDAR Data (씨호크 항공수심라이다 데이터를 활용한 연안침식 시계열 분석 - 강원도 표사계 GW36을 중심으로 -)

  • Lee, Jaebin;Kim, Jiyoung;Kim, Gahyun;Hur, Hyunsoo;Wie, Gwangjae
    • Korean Journal of Remote Sensing
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    • v.38 no.6_1
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    • pp.1527-1539
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    • 2022
  • As coastal erosion of the east coast is accelerating, the need for scientific and quantitative coastal erosion monitoring technology for a wide area increases. The traditional method for observing changes in the coast was precision monitoring based on field surveys, but it can only be applied to a small area. The airborne bathymetric Light Detection And Ranging (LiDAR) system is a technology that enables economical surveying of coastal and seabed topography in a wide area. In particular, it has the advantage of constructing topographical data for the intertidal zone, which is a major area of interest for coastal erosion monitoring. In this study, time series analysis of coastal seabed topography acquired in Aug, 2021 and Mar. 2022 on the littoral cell GW36 in Gangwon was performed using the Seahawk Airborne Bathymetric LiDAR (ABL) system. We quantitatively monitored the topographical changes by measuring the baseline length, shoreline and Digital Terrain Model (DTM) changes. Through this, the effectiveness of the ABL surveying technique was confirmed in coastal erosion monitoring.