Correcting Aquaculture Facility-Induced Spectral Distortions for Improved Satellite Water Quality Retrieval in Marine Ranching Areas
Marine ranching plays a vital role in sustainable fishery resource utilization and marine ecosystem protection. Accurate water quality monitoring through remote sensing is essential in these areas; however, aquaculture facilities such as floating buoys introduce additional reflected signals that can distort remote sensing reflectance (<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R</i><sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">rs</sub>(λ)), leading to significant errors in water quality parameter retrievals. Despite this challenge, previous studies have neither systematically quantified this interference nor developed effective correction methods. This study proposes a novel correction method to mitigate aquaculture-induced distortions in <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R</i><sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">rs</sub>(λ), enhancing the accuracy of remote sensing-based water quality assessments. Using the mussel aquaculture ranching area off Gouqi Island, China, as a case study, we systematically analyze the spectral influence of aquaculture facilities on <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R</i><sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">rs</sub>(λ) derived from Landsat observations. Comparative spectral analysis between affected and unaffected areas reveals that the high reflectance characteristics of aquaculture facilities cause abnormally elevated <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R</i><sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">rs</sub>(λ) values, particularly in the shortwave infrared bands. To address this issue, we introduce an aquaculture facility influence factor and develop a pixel-based dynamic correction approach that adjusts for varying degrees of aquaculture-induced distortions across different pixels. Validations using field-measured <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R</i><sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">rs</sub>(λ) demonstrates that the mean absolute percentage errors at wavelengths of 443, 483, 561, 655, 865, and 1609 nm decreased significantly from 17.6%, 19.8%, 14.8%, 26.8%, 50.9%, and 180.6% before correction to 9.5%, 11.0%,9.2%, 10.4%, 7.7%, and 20.4%, respectively. The effectiveness of the correction method is further supported by improvements in the retrieval of water transparency (<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Z</i><sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">sd</sub>). Sensitivity analysis further reveals that uncorrected <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Z</i><sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">sd</sub> retrieval errors increase exponentially with aquaculture facility coverage, exceeding 60% when coverage reaches 10%, underscoring the necessity of correcting <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R</i><sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">rs</sub>(λ) distortions caused by aquaculture facilities. Overall, the proposed correction method provides a robust and adaptable framework for improving satellite-based water quality monitoring in complex aquaculture regions, with potential applicability across diverse marine ranching environments and integration with various satellite sensors.
Authors
- Zishen Li (ORCID: https://orcid.org/0000-0002-3911-3059)
- Yongjun Jia (ORCID: https://orcid.org/0000-0002-9579-1217)
- Xin Zhang (ORCID: https://orcid.org/0000-0002-5935-5135)
- Xiumei Zhang (ORCID: https://orcid.org/0000-0002-3168-7971)
- Shengqiang Wang (ORCID: https://orcid.org/0000-0003-4725-1635)
- Deyong Sun (ORCID: https://orcid.org/0000-0001-9599-2732)
- Shuyan Lang
- Jingke Meng
Institutions
- Nanjing University of Information Science and Technology (CN)
- Zhejiang Ocean University (CN)
- National Satellite Ocean Application Service (CN)
- Aerospace Information Research Institute (CN)
Publication Details
- Journal
- IEEE Transactions on Geoscience and Remote Sensing
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1109/tgrs.2025.3583085
- Primary Topic
- Water Quality Monitoring Technologies
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China