• Title/Summary/Keyword: discrete return LiDAR

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Comparative study for height accuracy of Full waveform LiDAR data (Full waveform LiDAR의 높이 정확도 비교 분석)

  • Ryu, Joong-Hi;Lee, Jae-Hwan;Koh, Seung-Bum;Kim, Back-Seok;Seo, Hae-Soo
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.29 no.3
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    • pp.257-263
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    • 2011
  • There are many previous researches such as verification of accuracy, application, and change detection of discrete return LiDAR data, but no researches for full waveform LiDAR data. In this study, we selected the forest area and urban area as case study areas and compared the height accuracy of full waveform LiDAR data with field surveying data. As a result, we got an RMSE of 3.lcm in urban area, 4.7cm in forest area, and it is verified that height accuracy of full waveform LiDAR is high. We think that it is very usefull in aerial photogrammetry.

EXTRACTING COMPLEX BUILDING FROM AIRBORNE LIDAR AND AIRBORNE ORTHIMAGERY

  • Nguyen, Dinh-Tai;Lee, Seung-Ho;Cho, Hyun-Kook
    • Proceedings of the KSRS Conference
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    • 2008.10a
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    • pp.177-180
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    • 2008
  • Many researches have been tried to extract building models and created a 3D cyber city from LiDAR data. In this paper, the approach of extracting complex building by using airborne LiDAR data combined with airborne orthoimagery has been performed. The pseudo-building elevations were derived from modified discrete return LiDAR data. Based on information property of the pseudo-height, building features could be extracted. The results of this study indicated the improvement of building extraction.

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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.