Automatic sea-land waveform classification method for single-wavelength airborne LiDAR bathymetry

doi:10.11947/j.AGCS.2022.20200314

Abstract

Abstract: Sea-land waveform classification is a preprocessing procedure for airborne LiDAR bathymetry (ALB), which is related to the accuracy of subsequent signal detection and point cloud generation. However, the existing methods are not applicable for single-wavelength ALB systems and have low degree of automation. Thus, an automatic sea-land waveform classification method for single-wavelength ALB is proposed. The point cloud elevation features are firstly obtained by the detection of the first and last signals and the calculation of the point coordinates. With the mean water level elevation approximated by elevation histogram fitting, most of the sea and land waveforms are classified based on the elevation features. The remaining undefined waveforms are processed as single-signal waveforms with only the strongest signal retained. The signal features and energy distribution features are extracted from the waveforms, and a train sample set is automatically generated using the similarity of point cloud elevation features. The sea-land labels of the undefined waveforms are finally determined by a support vector machine classifier. The field data collected by a domestic ALB system (Mapper5000) are used to test the proposed method. The experimental results show that the initial classification based on the point cloud elevation features can quickly and accurately classify the waveforms away from the sea-land boundary, and the undefined waveform classification based on waveform features can automatically classify the waveforms closed to the sea-land boundary with the support of the self-established train sample set. Compared to the traditional methods, the proposed method can achieve high accuracy sea-land classification without the assistance of near-infrared channel and manual samples, and the overall accuracy and the accuracy of the areas closed to sea-land boundary reach 99.82% and 91.59%, respectively.

Key words: airborne LiDAR bathymetry, waveform classification, sea-land classification, waveform feature, support vector machine

CLC Number:

P237

WANG Dandi, XING Shuai, XU Qing, LIN Yuzhun, LI Pengcheng. Automatic sea-land waveform classification method for single-wavelength airborne LiDAR bathymetry[J]. Acta Geodaetica et Cartographica Sinica, 2022, 51(5): 750-761.

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