An active-passive fusion strategy and accuracy evaluation for shallow water bathymetry based on ICESat-2 ATLAS laser point cloud and satellite remote sensing imagery. Issue 8 (18th April 2021)

• Record Type: Journal Article
• Authors: Cao, Bincai; Fang, Yong; Gao, Li; Hu, Haiyan; Jiang, Zhengzhi; Sun, Bijiao; Lou, Lele
• Is Part Of: International journal of remote sensing. Volume 42:Issue 8(2021)
• Page Start: 2783
• Page End: 2806
• Publication Date: 2021-04-18
• Subjects: ICESat-2, ATLAS -- photon-counting LiDAR -- active-passive fusion -- shallow bathymetry -- accuracy evaluation; Remote sensing -- Periodicals; Télédétection -- Périodiques; 621.3678
• DOI: 10.1080/01431161.2020.1862441
• Languages: English
• ISSNs: 0143-1161

Abstract

ABSTRACT: The Advanced Topographic Laser Altimeter System (ATLAS) on ICESat-2 (Ice, Cloud, and Land Elevation Satellite-2) uses a 532 nm band photon-counting LiDAR (Light Detection and Ranging), which has certain penetrability to water bodies, and the measured data show that the bathymetric ability reaches nearly one Secchi depth. ATLAS has a limited number of beams and a fixed ground track, and only collects section elevation along the track direction. The fusion of active laser point cloud and passive optical remote sensing satellite image can fill the gap of shallow water depth data in a large range. This paper takes ATLAS as the research object, with the aim of exploring the effective algorithm flow of spaceborne active laser and passive optical fusion processing, and systematically evaluating the bathymetric accuracy of the fusion algorithm. An adaptive Gauss filtering technology based on the density of point cloud was firstly improved to achieve accurate denoising under the condition of uneven surface/underwater density. Subsequently, the depth of underwater points was calculated automatically through steps of water surface modelling, refraction correction, etc. Finally, the control points and check points were randomly extracted to solve the parameters of multispectral inversion model and verify the internal accuracy of the model. In this paper, the accuracy of ATLAS bathymetry was verified by Airborne LiDAR Bathymetry (ALB) data in Oahu Island, Hawaii, and the results indicate that the vertical root mean square error (RMSE) ranges from 0.56 m to 1.11 m. In Yongle islands and Qilianyu area of the South China Sea, WorldView-2 (WV2) 4 bands multispectral images and ATLAS data were used to carry out the active-passive fusion bathymetry, and the ALB and sonar data were used to evaluate the accuracy. Experimental results show that the internal compliance accuracy of the fusion model is better than 1.25 m (RMSE), and the real bathymetry accuracy is better than 1.42 m (RMSE). The above results reveal the great potential of active-passive fusion bathymetry based on ICESat-2 and other high-resolution remote sensing satellites, which can provide strong technical support for filling the blank of shallow water depth information.