PDF
Full
Outline
The airborne LiDAR bathymetry (ALB) technology has the advantages of high precision, high efficiency, strong mobility and dual use of water and land. It is especially suitable for the rapid detection of complex terraforming in shallow waters such as coastal zones, islands and reefs. When the laser penetrates the water, the energy will attenuate rapidly, which makes it difficult to extract part of the seabed echo effectively and distinguish the true position of the sea bottom. Therefore, an airborne LiDAR bathymetric travel time in the water column extraction algorithm based on echo enhancement is proposed in this paper. The Gold deconvolution algorithm was used to restore the cross section shape of the target and determine the initial range of the seabed. Then, the effective range of backscattering was fitted by double exponential function, and the diffuse attenuation coefficient Kd was obtained. Finally, combined with the seabed LiDAR equation, the waveform in the initial range of the seabed is enhanced by Kd value, and the enhanced echo is decomposed by Gaussian function to determine the seabed position parameters, so as to realize the travel time in the water column extraction of ALB waveform. The feasibility of the proposed algorithm was verified by using the experimental data of RIEGL VQ-840-G ALB in Qingdao Jiaozhou Bay, and the proposed algorithm was compared with the Richardson-Lucy deconvolution model and the peak detection model. The results show that the root mean square error (RMSE) between the proposed algorithm and the single-beam point with the same name is 18.5 cm, which is 29.9% and 41.4% lower than the above two algorithms, respectively. Therefore, the proposed algorithm is feasible and can satisfy the high precision extraction of ALB waveform during water column traveling, which can provide certain technical support for the fine processing of airborne LiDAR bathymetry data.
PDF
134
54
| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
关闭全屏
No. 86 Xueyuan South Road, Haidian District, Beijing
010-62199257
qkjq@cast.org.cn
Copyright © 2025 China Association for Science and Technology. All rights reserved. For all open access content, the relevant licensing terms apply.
Sponsored by the Office of the Leading Group for Cybersecurity and Informatization of CAST, and supported by Science and Technology Review Publishing House
