Paper
30 April 2024 Assessing the impact of cirrus cloud thickness on ICESat-2's maximum bathymetric capabilities in coastal waters
Boran Zhang, Chengkang Xu, Shuaibo Wang, Chonghui Cheng, Kai Zhang, Jingxin Zhang, Weize Li, Xiaotao Li, Xianzhe Hu, Wentao Xu, Jiesong Deng, Dong Liu
Author Affiliations +
Proceedings Volume 13157, Sixth Conference on Frontiers in Optical Imaging and Technology: Applications of Imaging Technologies; 131571C (2024) https://doi.org/10.1117/12.3019858
Event: Sixth Conference on Frontiers in Optical Imaging Technology and Applications (FOI2023), 2023, Nanjing, JS, China
Abstract
This study explores the maximum bathymetric capabilities of the ICESat-2 in coastal environments, with a particular focus on the impact of cirrus cloud thickness. Utilizing MODTRAN simulations for atmospheric transmittance under various cloud conditions, we integrate these with a maximum bathymetric depth model to quantitatively assess this impact. Our results indicate a significant decrease in detection depth with increasing cloud thickness, culminating in complete signal attenuation at cloud thicknesses of 3-4 km. Furthermore, simulations reveal that the FF phase function model outperforms OTHG and TTHG models, exhibiting the lowest Mean Absolute Error (MAE) and Mean Relative Error (MRE) in the Puerto Rico and Virgin Islands study sub-areas. This research provides critical insights into the capabilities and limitations of spaceborne lidar in coastal bathymetry, highlighting the importance of atmospheric conditions in remote sensing applications.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Boran Zhang, Chengkang Xu, Shuaibo Wang, Chonghui Cheng, Kai Zhang, Jingxin Zhang, Weize Li, Xiaotao Li, Xianzhe Hu, Wentao Xu, Jiesong Deng, and Dong Liu "Assessing the impact of cirrus cloud thickness on ICESat-2's maximum bathymetric capabilities in coastal waters", Proc. SPIE 13157, Sixth Conference on Frontiers in Optical Imaging and Technology: Applications of Imaging Technologies, 131571C (30 April 2024); https://doi.org/10.1117/12.3019858
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