IAP-SWBF: an ICESat-2 shallow-water bathymetry framework for saturated nearshore environments considering afterpulse effects

The photon-counting laser altimeter onboard the Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) offers a new opportunity for bathymetric mapping in nearshore extremely shallow waters (0–5 m). However, its single-photon detection mode is prone to pronounced instrument-induced artifacts in saturated nearshore environments, particularly over highly reflective shallow seabeds or calm water surfaces. Afterpulse noise exhibits structured distributions and is frequently misclassified as seabed signals by density-based algorithms, thereby degrading shallow-water bathymetric accuracy. To address this issue, this study proposes a shallow-water bathymetry framework that integrates the physical mechanism of afterpulses with the spatial characteristics of photons (IAP-SWBF). First, an adaptive probabilistic model is constructed using detector dead-time properties and photon quality flags to accurately identify and suppress afterpulse noise. Next, a sliding-window kernel density estimation approach is employed to derive an initial seabed profile, followed by a dynamic elliptical domain constraint algorithm that adaptively adjusts the search window according to terrain slope, enabling robust separation of true seabed photons. Finally, refraction correction based on Snell’s law is applied to the extracted underwater photons. The framework was validated across nine representative shallow-water sites worldwide, including the Florida coast (USA), western Pacific islands, and lakes in Greenland. Airborne laser bathymetry (ALB) data released by National Oceanic and Atmospheric Administration (NOAA) were used as reference truth, and the IAP-SWBF results were compared with an improved Density-Based Spatial Clustering of Applications with Noise (DBSCAN) approach and the ICESat-2 official bathymetric product ATL24. The results demonstrate strong agreement between IAP-SWBF derived depths and ALB, with a minimum RMSE of 0.13 m, an average RMSE of 0.5 m, and a mean correlation coefficient (R) of 0.95. In complex environments characterized by extremely low photon density or steep terrain, IAP-SWBF outperforms DBSCAN and ATL24. In saturated nearshore regions, afterpulse removal reduces bathymetric average RMSE from 1.65 m to 0.33 m. Even within the extremely shallow 0–5 m depth range, the framework effectively suppresses afterpulse interference. This study provides a valuable technical reference for high-precision bathymetry retrieval in saturated shallow-water environments affected by afterpulse interference.

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Publication Details

Journal
GIScience & Remote Sensing
Published
2026-05-02
DOI
https://doi.org/10.1080/15481603.2026.2661501
Primary Topic
Remote Sensing and LiDAR Applications
Type
article
Field-Weighted Citation Impact
0.00

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article

IAP-SWBF: an ICESat-2 shallow-water bathymetry framework for saturated nearshore environments considering afterpulse effects

Shuangcheng Zhang, Zhijie Feng, Jun Li, Hui Gong et al.
GIScience & Remote Sensing
Remote Sensing and LiDAR Applications
article

IAP-SWBF: an ICESat-2 shallow-water bathymetry framework for saturated nearshore environments considering afterpulse effects

Shuangcheng Zhang, Zhijie Feng, Jun Li, Hui Gong, Minghui Wang, Tianyou Wei, Tao Wang
article en

Abstract

The photon-counting laser altimeter onboard the Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) offers a new opportunity for bathymetric mapping in nearshore extremely shallow waters (0–5 m). However, its single-photon detection mode is prone to pronounced instrument-induced artifacts in saturated nearshore environments, particularly over highly reflective shallow seabeds or calm water surfaces. Afterpulse noise exhibits structured distributions and is frequently misclassified as seabed signals by density-based algorithms, thereby degrading shallow-water bathymetric accuracy. To address this issue, this study proposes a shallow-water bathymetry framework that integrates the physical mechanism of afterpulses with the spatial characteristics of photons (IAP-SWBF). First, an adaptive probabilistic model is constructed using detector dead-time properties and photon quality flags to accurately identify and suppress afterpulse noise. Next, a sliding-window kernel density estimation approach is employed to derive an initial seabed profile, followed by a dynamic elliptical domain constraint algorithm that adaptively adjusts the search window according to terrain slope, enabling robust separation of true seabed photons. Finally, refraction correction based on Snell’s law is applied to the extracted underwater photons. The framework was validated across nine representative shallow-water sites worldwide, including the Florida coast (USA), western Pacific islands, and lakes in Greenland. Airborne laser bathymetry (ALB) data released by National Oceanic and Atmospheric Administration (NOAA) were used as reference truth, and the IAP-SWBF results were compared with an improved Density-Based Spatial Clustering of Applications with Noise (DBSCAN) approach and the ICESat-2 official bathymetric product ATL24. The results demonstrate strong agreement between IAP-SWBF derived depths and ALB, with a minimum RMSE of 0.13 m, an average RMSE of 0.5 m, and a mean correlation coefficient (R) of 0.95. In complex environments characterized by extremely low photon density or steep terrain, IAP-SWBF outperforms DBSCAN and ATL24. In saturated nearshore regions, afterpulse removal reduces bathymetric average RMSE from 1.65 m to 0.33 m. Even within the extremely shallow 0–5 m depth range, the framework effectively suppresses afterpulse interference. This study provides a valuable technical reference for high-precision bathymetry retrieval in saturated shallow-water environments affected by afterpulse interference.

GIScience & Remote SensingVol. 63(1)
Xi'an University of Science and Technology (CN), Chang'an University (CN), Quantum Spatial (United States) (US), Geomatics (Norway) (NO)
National Natural Science Foundation of China
Life below water
Openalex Percentile: Top 11%
Remote Sensing and LiDAR Applications
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