ICESat‑2 LiDAR Bathymetry Based on Adaptive Spatial Density Filtering

CHEN Yifu; LI Shuai; ZHANG Dongfang; LE Yuan; WANG Lizhe

doi:10.13203/j.whugis20220453

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ICESat‑2 LiDAR Bathymetry Based on Adaptive Spatial Density Filtering

Photogrammetry and Remote Sensing | 更新时间：2026-11-05

- ICESat‑2 LiDAR Bathymetry Based on Adaptive Spatial Density Filtering
- Geomatics and Information Science of Wuhan University Vol. 50, Issue 1, Pages: 83-96(2025)
- 作者机构：
  
  1.湖北珞珈实验室，湖北武汉，430079
  2.中国地质大学（武汉）计算机学院，湖北武汉，430074
  3.中国地质大学（武汉）地理与信息工程学院，湖北武汉，430074
- 作者简介：
- 基金信息：
- DOI：10.13203/j.whugis20220453
  CLC： P237
- Received：09 March 2023，
  
  Published：05 January 2025
- 稿件说明：
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谌一夫,李帅,张东方，等.自适应空间密度滤波的ICESat‑2激光雷达测深[J].武汉大学学报（信息科学版）,2025,50(1):83-96.

CHEN Yifu,LI Shuai,ZHANG Dongfang,et al.ICESat‑2 LiDAR Bathymetry Based on Adaptive Spatial Density Filtering[J].Geomatics and Information Science of Wuhan University,2025,50(1):83-96.
谌一夫,李帅,张东方，等.自适应空间密度滤波的ICESat‑2激光雷达测深[J].武汉大学学报（信息科学版）,2025,50(1):83-96. DOI：,10.13203/j.whugis20220453

CHEN Yifu,LI Shuai,ZHANG Dongfang,et al.ICESat‑2 LiDAR Bathymetry Based on Adaptive Spatial Density Filtering[J].Geomatics and Information Science of Wuhan University,2025,50(1):83-96. DOI：,10.13203/j.whugis20220453

摘要

冰、云和陆地高程卫星2号（ice

cloud and land elevation satellite-2

ICESat-2）搭载了先进地形激光测高系统（advanced topographic laser altimeter system，ATLAS），该系统采用光子计数探测模式，可获取高精度的地表高程信息。ATLAS使用532 nm波段激光器，具备一定的水深探测能力，为星载数据近岸水深探测提供了新手段。利用ICESat-2 ATLAS数据进行测深，关键问题是如何实现不同区域、不同环境、不同密度分布条件下信号光子的自动探测与提取。为解决此问题，提出了一种基于自适应空间滤波的ICESat-2数据测深方法，该方法首先将水面以上、水面和水下区域的原始光子进行分离，随后基于可变椭圆密度滤波核精确提取水面与水底光子，椭圆密度滤波核参数根据不同水深下光子密度的分布特点自适应确定，最终实现浅海水深测量。实验结果表明，所提方法获取的ICESat-2测深结果与机载激光雷达测深结果的相关系数达到0.93，均方根误差为0.51 m，具有较高的测深精度。

Abstract

Objectives

The ice

cloud

and land elevation satellite-2 (ICESat-2)

equipped with the advanced topographic laser altimeter system (ATLAS)

is a new measurement strategy with a photon-counting technique to obtain the high-accuracy elevation information in the surface of the Earth. ATLAS uses a 532 nm band laser to emit three pairs of scanning laser beams

each pair containing one strong and one weak sub-beam. The receiver collects millions of return photons from the echo

and each received photon is recorded. In the field of bathymetry

photon counting LiDAR has great advantages. For traditional LiDAR with linear detection regime

the only way to achieve high signal-to-noise ratio requirement is to increase the emitted laser energy

which results in a very bulky and huge system and high design power consumption. Photon counting LiDAR is no longer confined to the detection of clear high signal-to-noise ratio echo waveform. It uses statistical optics theory to achieve effective ranging

and maximizes the use of each photon energy in the laser echo

which can greatly improve the detection efficiency of bathymetry detection while reducing the system complexity

providing new opportunities for near-shore bathymetry detection. Based on ICESat-2 ATLAS data for bathymetry

the main problem is how to achieve automatic detection and extraction of signal photons for raw photons in different regions

different environments and different density distributions.

Methods

To overcome these existing problems

an adaptive spatial filtering bathymetric method based on photon density distribution is proposed. The method first separate the photons into above the water

water-surface

and underwater photons. The filter parameters can be automatically determined by the photon density distribution generated based on the optical characteristics of different water bodies and water depth distribution

so that the signal photons of the water surface and bottom can be precisely extracted to achieve bathymetry. In order to verify the bathymetric accuracy of the method

experiments were conducted using ATLAS datasets obtained in different areas of the South China Sea

and finally the experimental results were verified by using high-precision bathymetric data acquired by airborne LiDAR.

Results

The validation results show that the coefficient of determination between the ICESat-2 bathymetric results and the airborne LiDAR bathymetric results reaches 0.93

and the correspond root mean square error is 0.51 m

which illustrate the bathymetric potential of the method proposed in this research. In addition

when using photonic data for bathymetry

it is influenced by the refraction of the water body

which mainly exists in the vertical direction and increases with the increase of depth.

Conclusions

Due to the complex diversity of water body environment

the photon bathymetry accuracy will show a certain decreasing trend with the increase of water depth. In future research

bathymetric experiments will be conducted using the method of this paper and the ATLAS dataset to investigate a more accurate refraction correction model in order to explore the bathymetric potential of the satellite-based photon counting LiDAR in different water environments.

关键词

Keywords

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