无现场采样的机载LiDAR最大测深估算

杨文泽; 杨安秀; 高兴国; 王春晓; 王振辉; 阳凡林; 宿殿鹏

doi:10.12284/hyxb2025099

无现场采样的机载LiDAR最大测深估算

doi: 10.12284/hyxb2025099

杨文泽^1,,
杨安秀^{1, 2, ,},
高兴国³,
王春晓⁴,
王振辉⁵,
阳凡林¹,
宿殿鹏¹

1.
山东科技大学测绘与空间信息学院，山东青岛 266590
2.
自然资源部第二海洋研究所自然资源部海底科学重点实验室，浙江杭州 310012
3.
山东电力工程咨询院有限公司，山东济南 250013
4.
自然资源部海南基础地理信息中心，海南海口 570203
5.
自然资源部第七地形测量队，海南海口 570203

基金项目: 国家自然科学基金（42406186）；中国博士后科学基金（2021M700155）；山东省自然科学基金（ZR2023QD050）；山东省高等教育青年创新科技计划项目（2023KJ088）；青岛市关键技术攻关及产业化示范类项目（23−1−3−hygg−1−hy）；青岛市自然科学基金（24−8−4−zrjj−2−jch, 23−2−1−66−zyyd−jch）；山东科技大学科研创新团队支持计划（2019TDJH103）；自然资源部海底科学重点实验室开放基金(KLSG2306)。

详细信息

作者简介:
杨文泽（2002—），男，山东省泰安市人，主要从事机载LiDAR测深波形数据处理方面的研究。E-mail：3378133630@qq.com

通讯作者:
杨安秀，博士，实验师，主要从事LiDAR测深点云处理与多源数据融合方面的研究。E-mail：skyanganxiu@163.com

中图分类号: P229
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出版历程
- 收稿日期: 2025-08-18
- 修回日期: 2025-10-27
- 网络出版日期: 2025-11-06
- 刊出日期: 2025-10-31

Maximum bathymetric depth estimation for airborne LiDAR without in-situ sampling

1.
College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao 266590, China
2.
Key Laboratory of Submarine Geosciences, Second Institute of Oceanography, Ministry of Natural Resources, Hangzhou 310012, China
3.
Shandong Electric Power Engineering Consulting Institute Corp., Ltd., Jinan 250000, China
4.
Hainan Geomatics Center of Ministry of Natural Resources, Haikou 570203, China
5.
The 7S1 Topographic Survey Brigade of Ministry of Natural Resources, Haikou 570203, China

摘要

摘要: 浅水区域的地形测量数据能够为海洋资源开发、水资源调查管理等提供基础的数据支撑，一直是海洋测绘等领域的研究热点。机载LiDAR测深（Airborne LiDAR Bathymetry，ALB）是一种高精度、高效率、机动性强的一种测量技术，特别适用于浅水区域的地形测量。针对机载激光最大测深估算依赖传统现场采样法（如赛齐盘透明度测量）效率低、成本高的问题，论文提出一种联合卫星遥感水色数据产品与波形建模的无现场采样最大测深估算方法。通过获取NASA Ocean Color的K_d(490)产品反演得到532 nm波段漫衰减系数，结合激光测深回波信号的物理模型，得到水面、水体、水底以及噪声的回波叠加波形，并利用峰值探测算法实现最大测深自动化判定。以山东省青岛市胶州湾与青海省德令哈市托素湖为实验区域，实验结果表明利用所提方法估算的最大测深估算偏差均不超过0.4 m，相对误差保持在5%以内，验证了方法的有效性。本文所提方法无需现场采样，相较于传统方法以卫星遥感水色数据产品代替现场透明度测量，不仅显著降低了机载LiDAR测深外业测量成本，还能够为浅水区测绘与水资源调查提供高效的技术支撑。
- 机载LiDAR测深 /
- 波形建模 /
- 漫衰减系数 /
- 最大测深
Abstract: Terrain measurement data in shallow water areas provide essential support for marine resource development and water resource investigation and management, making them a focal point in marine surveying and related fields. Airborne LiDAR Bathymetry (ALB) is a high-precision, high-efficiency, and highly mobile measurement technology particularly suited for topographic surveys in shallow water regions. To address the inefficiencies and high costs associated with traditional on-site sampling methods ( Secchi disk transparency measurements) for estimating maximum bathymetric depth using airborne LiDAR, this study proposes a novel method for maximum depth estimation without on-site sampling, integrating satellite remote sensing water color data products with waveform modeling. By retrieving the diffuse attenuation coefficient at 532 nm through inversion of NASA Ocean Color’s K_d(490) product and combining it with a physical model of LiDAR bathymetric echo signals, the method constructs a superimposed waveform model incorporating contributions from the water surface, water column, seabed, and noise. A peak detection algorithm is then employed to automate maximum depth determination. Experimental results from Jiaozhou Bay in Qingdao City, Shandong Province, and Tuosu Lake in Delingha City, Qinghai Province, demonstrate that the proposed method achieves maximum depth estimation with deviations not exceeding 0.4 m and relative errors within 5%, validating its effectiveness. By replacing on-site transparency measurements with satellite remote sensing water color data products, the proposed method eliminates the need for field sampling, significantly reducing the operational costs of airborne LiDAR bathymetry while providing efficient technical support for shallow water mapping and water resource investigations.
- Airborne LiDAR Bathymetry /
- waveform modeling /
- diffuse attenuation coefficient /
- maximum depth estimation

HTML全文

图 1 无现场采样的机载LiDAR测深能力估算流程

Fig. 1 Flowchart for estimating the bathymetric capability of airborne LiDAR without on-site sampling

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图 2 激光测深回波信号各部分和总体建模

Fig. 2 Modeling of individual components and the overall laser bathymetry echo signal

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图 3 青岛胶州湾机载LiDAR测深实验概况

a. 测区地理位置（审图号：GS(2019)3333号）；b. 机载测深LiDAR；c. 现场水质情况；d. 无人机平台；e. 青岛胶州湾沿岸地理概况

Fig. 3 Overview of the airborne LiDAR bathymetry experiment in Jiaozhou Bay, Qingdao

a. Geographical location of the study area (Map Approval Number: GS(2019)3333); b. airborne bathymetric LiDAR; c. on-site water quality conditions; d. UAV platform; e. geographical overview of the Jiaozhou Bay coastline

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图 4 青海托素湖机载LiDAR测深实验概况

a. 测区地理位置（审图号：GS(2019)3333号）；b. 现场飞行照片；c. 青海托素湖卫星影像；d. 现场水质情况

Fig. 4 Overview of the airborne LiDAR bathymetry experiment in Tosu Lake, Qinghai

a. Geographical location of the study area (Map Approval Number: GS(2019)3333); b. on-site flight photos; c. satellite imagery of Tosu Lake, Qinghai; d. on-site water quality conditions

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图 5 实际测深回波波形（a），建模激光测深回波波形（b）

Fig. 5 Actual measured echo waveform (a), modeled laser altimetry echo waveform (b)

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图 6 青岛胶州湾测量数据成果及最大测深

Fig. 6 Measurement results and maximum depth map of Jiaozhou Bay, Qingdao

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图 7 青海托素湖测量数据成果及最大测深

Fig. 7 Measurement results and maximum depth of Tuosu Lake, Qinghai

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图 8 最大测深与航高以及K_d(532)三者间的相互关系

Fig. 8 The interrelationship among maximum detectable depth, flight altitude, and K_d(532)

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表 1 建模中部分系统参数和环境参数

Tab. 1 System parameters and environmental parameters in modeling

系统参数	数值	环境参数	数值
激光波长λ	532 nm	大气双程损失${T^2_{{\mathrm{atm}}}} $	0.9
脉冲宽度T₀	5 ns	水面粗糙度r	0.1
航高H	130 m	水体折射率n_w	1.33
入射角θ	20°	水底反照率R_b	0.12
发射光学效率ƞ_e	0.9	镜面反射系数k_s	0.98
接收光学效率ƞ_R	0.58	漫反射系数k_d	0.02
噪声标准差	1.1	漫衰减系数K_d(532)	0.197

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表 2 实验真实系统参数和环境参数

Tab. 2 Actual system and environmental parameters used in the experiment

测区	航高/m	K_d(532)
青岛胶州湾	130	0.19
青海托素湖	160	0.15

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表 3 建模中部分系统参数和环境参数

Tab. 3 System Parameters and Environmental Parameters in Modeling

测区	实测最大测深/m	估算最大测深/m	深度差值/m
青岛胶州湾	7.90	8.3	0.40
青海托素湖	8.45	8.7	0.25

下载: 导出CSV

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