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Ocean Optical Profiling in South China Sea Using Airborne LiDAR

State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, Ministry of Natural Resources, 36 Bochubeilu, Hangzhou 310012, China
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Remote Sens. 2019, 11(15), 1826; https://doi.org/10.3390/rs11151826
Received: 25 June 2019 / Revised: 28 July 2019 / Accepted: 1 August 2019 / Published: 5 August 2019
(This article belongs to the Section Ocean Remote Sensing)
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Abstract

Increasingly, LiDAR has more and more applications. However, so far, there are no relevant publications on using airborne LiDAR for ocean optical profiling in the South China Sea (SCS). The applicability of airborne LiDAR for optical profiling in the SCS will be presented. A total of four airborne LiDAR flight experiments were conducted over autumn 2017 and spring 2018 in the SCS. A hybrid retrieval method will be presented here, which incorporates a Klett method to obtain LiDAR attenuation coefficient and a perturbation retrieval method for a volume scattering function at 180°. The correlation coefficient between the LiDAR-derived results and the traditional measurements was 0.7. The mean absolute relative error (MAE) and the normalized root mean square deviation (NRMSD) between the two are both between 10% and 12%. Subsequently, the vertical structure of the LiDAR-retrieved attenuation and backscattering along airborne LiDAR flight tracks was mapped. In addition to this, ocean subsurface phytoplankton layers were detected between 10 to 20 m depths along the flight track in Sanya Bay. Primary results demonstrated that our airborne LiDAR has an independent ability to survey and characterize ocean optical structure. View Full-Text
Keywords: LiDAR; optical property profiles; attenuation coefficient; backscattering; bio-optical model; hybrid method LiDAR; optical property profiles; attenuation coefficient; backscattering; bio-optical model; hybrid method
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Chen, P.; Pan, D. Ocean Optical Profiling in South China Sea Using Airborne LiDAR. Remote Sens. 2019, 11, 1826.

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