1.中国科学院 空天信息创新研究院 数字地球重点实验室，北京 100094;2.可持续发展大数据国际研究中心，北京 100094;3.中国科学院大学 资源与环境学院，北京 100049
习晓环（1972—），女，副研究员，硕士生导师，主要研究方向为激光雷达遥感。E-mail：xixh@radi.ac.cn
王子家（1997—），女，硕士研究生，主要研究方向为激光雷达遥感。E-mail： wangzijia20@mails.ucas.ac.cn
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国家重点研发计划（2021YFF0704600）；中国科学院青年创新促进会 （2019130）
- XI Xiaohuan 1,2
- WANG Zijia 1,2,3
WANG Zijia
Key Laboratory of Digital Earth Science， Aerospace Information Research Institute， Chinese Academy of Sciences， Beijing 100094， China;International Research Center of Big Data for Sustainable Development Goals， Beijing 100094， China;College of Resources and Environment， University of Chinese Academy of Sciences， Beijing 100049， China
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WANG Cheng
Key Laboratory of Digital Earth Science， Aerospace Information Research Institute， Chinese Academy of Sciences， Beijing 100094， China;International Research Center of Big Data for Sustainable Development Goals， Beijing 100094， China;College of Resources and Environment， University of Chinese Academy of Sciences， Beijing 100049， China
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1.Key Laboratory of Digital Earth Science， Aerospace Information Research Institute， Chinese Academy of Sciences， Beijing 100094， China;2.International Research Center of Big Data for Sustainable Development Goals， Beijing 100094， China;3.College of Resources and Environment， University of Chinese Academy of Sciences， Beijing 100049， China
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水深是表征海洋浅水和海岸环境的重要地形要素，光子计数激光雷达可穿透一定深度的水体，为水深信息提取提供可靠的数据支持。以我国南海岛礁为例，利用目前唯一在轨的星载光子计数激光雷达-ICESat-2/ATLAS数据开展岛礁浅水水深提取及精度评价研究。首先根据置信度参数对原始光子数据进行粗去噪，基于点密度分布差异分离水面和水底光子；然后对水面光子采用区间估计方法精去噪，利用RANSAC算法拟合水面高程；通过改进滤波参数，基于改进OPTICS算法对水底光子进行两次聚类，实现水底光子的精去噪，进而通过折射校正和潮汐校正提取近岸水深；最后利用机载LiDAR测深数据进行验证。实验结果表明，与ATL03高置信度光子数据和AVEBM去噪结果相比，该精去噪算法具有更高的F值，分别提高了约5.87％和3.38％；水深提取结果与机载测深数据的R2为0.91，均方根误差RMSE为0.53m。
Water depth is an important topographical parameter that characterizes shallow ocean and coastal environment. Photon-counting light detection and ranging （LiDAR） can penetrate a certain depth of water and provide reliable date support for water depth information extraction. Taking the islands and reefs in the South China Sea as an example， this paper uses the only in-orbit spaceborne photon-counting LiDAR - Ice， Cloud and land Elevation Satellite-2/Advanced Topographic Laser Altimeter System （ICESat-2/ATLAS） to carry out research on depth extraction and accuracy evaluation in shallow water areas of islands and reefs. Firstly， confidence parameter is adopted to remove the coarse noise photons， and the photons in the water surface and bottom are separated according to their density. Secondly， interval estimate and the modified ordering points to identify the clustering structure （OPTICS） are utilized to filter out noise photons in the water surface and bottom respectively， and the modified OPTICS is changed twice by the filter parameters. Then the water surface elevation is obtained by using the random sample consensus （RANSAC） algorithm. Thirdly， the bathymetric information is achieved by the refraction and tide correction. Finally， the airborne bathymetric LiDAR data of South China Sea is used to validate and evaluate the bathymetric accuracy. Compared with the depth results extracted from the high confidence photons and adaptive variable ellipse filtering bathymetric method （AVEBM）， the proposed noise removal algorithm has a higher F value， which is increased by 5.87% and 3.38% respectively. The experimental results indicated that the R2 of bathymetric results obtained by ATLAS and airborne LiDAR is 0.91 and root mean square error （RMSE） is 0.53m.
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习晓环,王子家,王成.基于ICESat-2/ATLAS数据的近海岸水深提取[J].同济大学学报(自然科学版),2022,50(7):940~946
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- 收稿日期:2022-04-17
- 在线发布日期: 2022-07-22
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