Reconstructing Gap-Free Daily Remote Sensing Reflectance in the Marginal Seas Using the DINEOF Method
Ocean color remote sensing has provided extensive datasets of various bio-optical parameters, which are essential for studying marine biogeochemical processes and ecosystems. However, factors such as the clouding cover, sun glint, and wide sensor viewing angles often result in missing satellite data...
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IEEE
2025-01-01
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| Series: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
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| Online Access: | https://ieeexplore.ieee.org/document/10973136/ |
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| author | Shuyan Lang Yuxuan Jiang Shengqiang Wang Yongjun Jia Yi Zhang |
| author_facet | Shuyan Lang Yuxuan Jiang Shengqiang Wang Yongjun Jia Yi Zhang |
| author_sort | Shuyan Lang |
| collection | DOAJ |
| description | Ocean color remote sensing has provided extensive datasets of various bio-optical parameters, which are essential for studying marine biogeochemical processes and ecosystems. However, factors such as the clouding cover, sun glint, and wide sensor viewing angles often result in missing satellite data, which complicates near-real-time ocean monitoring and may introduce errors in time-series analyses due to limited data availability. Remote sensing reflectance <inline-formula><tex-math notation="LaTeX">$(R_{\text{rs}}(\lambda ))$</tex-math></inline-formula> constitutes the primary product in ocean color remote sensing, which serves as a source deriving for most bio-optical products. This study aims to reconstruct a daily gap-free <inline-formula><tex-math notation="LaTeX">$R_{\text{rs}}(\lambda )$</tex-math></inline-formula> dataset using the data interpolating empirical orthogonal functions method, applied on moderate resolution imaging spectroradiometer (MODIS)-Aqua daily time-series <inline-formula><tex-math notation="LaTeX">$R_{\text{rs}}(\lambda )$</tex-math></inline-formula> product, focusing on the Eastern China Seas as a case study. The evaluation demonstrates the reconstructed <inline-formula><tex-math notation="LaTeX">$R_{\text{rs}}(\lambda )$</tex-math></inline-formula> data is both feasible and accurate in terms of magnitude and spectral shape. The reconstructed <inline-formula><tex-math notation="LaTeX">$R_{\text{rs}}(\lambda )$</tex-math></inline-formula> data were then utilized to derive secondary ocean color products, including the diffuse attenuation coefficient at 490 nm for downwelling irradiance and chlorophyll-<italic>a</italic> concentration, which revealed high similarity and accuracy versus those calculated from the original MODIS <inline-formula><tex-math notation="LaTeX">$R_{\text{rs}}(\lambda )$</tex-math></inline-formula> data. These findings suggest that the reconstructed daily <inline-formula><tex-math notation="LaTeX">$R_{\text{rs}}(\lambda )$</tex-math></inline-formula> data can effectively serve as foundational data for calculating other ocean color satellite products. These gap-free ocean color satellite products produced in this study can be further utilized in oceanographic studies and as inputs for marine ecosystem models to predict marine ecological environments. Future research will focus on <inline-formula><tex-math notation="LaTeX">$R_{\text{rs}}(\lambda )$</tex-math></inline-formula> reconstruction using multiple ocean color sensor data and extending the approach to other water regions. |
| format | Article |
| id | doaj-art-86ec4c1e1fba419e8a9d747e3fe7c68d |
| institution | DOAJ |
| issn | 1939-1404 2151-1535 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
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| series | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
| spelling | doaj-art-86ec4c1e1fba419e8a9d747e3fe7c68d2025-08-20T02:58:51ZengIEEEIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing1939-14042151-15352025-01-0118115881159810.1109/JSTARS.2025.356321610973136Reconstructing Gap-Free Daily Remote Sensing Reflectance in the Marginal Seas Using the DINEOF MethodShuyan Lang0Yuxuan Jiang1https://orcid.org/0009-0007-8999-5524Shengqiang Wang2https://orcid.org/0000-0003-4725-1635Yongjun Jia3https://orcid.org/0000-0002-9579-1217Yi Zhang4https://orcid.org/0000-0002-3622-8344National Satellite Ocean Application Service, Beijing, ChinaNational Marine Environmental Forecasting Center, Beijing, ChinaSchool of Marine Sciences, Nanjing University of Information Science and Technology, Nanjing, ChinaNational Satellite Ocean Application Service, Beijing, ChinaNational Satellite Ocean Application Service, Beijing, ChinaOcean color remote sensing has provided extensive datasets of various bio-optical parameters, which are essential for studying marine biogeochemical processes and ecosystems. However, factors such as the clouding cover, sun glint, and wide sensor viewing angles often result in missing satellite data, which complicates near-real-time ocean monitoring and may introduce errors in time-series analyses due to limited data availability. Remote sensing reflectance <inline-formula><tex-math notation="LaTeX">$(R_{\text{rs}}(\lambda ))$</tex-math></inline-formula> constitutes the primary product in ocean color remote sensing, which serves as a source deriving for most bio-optical products. This study aims to reconstruct a daily gap-free <inline-formula><tex-math notation="LaTeX">$R_{\text{rs}}(\lambda )$</tex-math></inline-formula> dataset using the data interpolating empirical orthogonal functions method, applied on moderate resolution imaging spectroradiometer (MODIS)-Aqua daily time-series <inline-formula><tex-math notation="LaTeX">$R_{\text{rs}}(\lambda )$</tex-math></inline-formula> product, focusing on the Eastern China Seas as a case study. The evaluation demonstrates the reconstructed <inline-formula><tex-math notation="LaTeX">$R_{\text{rs}}(\lambda )$</tex-math></inline-formula> data is both feasible and accurate in terms of magnitude and spectral shape. The reconstructed <inline-formula><tex-math notation="LaTeX">$R_{\text{rs}}(\lambda )$</tex-math></inline-formula> data were then utilized to derive secondary ocean color products, including the diffuse attenuation coefficient at 490 nm for downwelling irradiance and chlorophyll-<italic>a</italic> concentration, which revealed high similarity and accuracy versus those calculated from the original MODIS <inline-formula><tex-math notation="LaTeX">$R_{\text{rs}}(\lambda )$</tex-math></inline-formula> data. These findings suggest that the reconstructed daily <inline-formula><tex-math notation="LaTeX">$R_{\text{rs}}(\lambda )$</tex-math></inline-formula> data can effectively serve as foundational data for calculating other ocean color satellite products. These gap-free ocean color satellite products produced in this study can be further utilized in oceanographic studies and as inputs for marine ecosystem models to predict marine ecological environments. Future research will focus on <inline-formula><tex-math notation="LaTeX">$R_{\text{rs}}(\lambda )$</tex-math></inline-formula> reconstruction using multiple ocean color sensor data and extending the approach to other water regions.https://ieeexplore.ieee.org/document/10973136/Data interpolating empirical orthogonal function (DINEOF) methodgap-free data reconstructionmarginal seasmoderate resolution imaging spectroradiometer (MODIS) dataremote sensing reflectance |
| spellingShingle | Shuyan Lang Yuxuan Jiang Shengqiang Wang Yongjun Jia Yi Zhang Reconstructing Gap-Free Daily Remote Sensing Reflectance in the Marginal Seas Using the DINEOF Method IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Data interpolating empirical orthogonal function (DINEOF) method gap-free data reconstruction marginal seas moderate resolution imaging spectroradiometer (MODIS) data remote sensing reflectance |
| title | Reconstructing Gap-Free Daily Remote Sensing Reflectance in the Marginal Seas Using the DINEOF Method |
| title_full | Reconstructing Gap-Free Daily Remote Sensing Reflectance in the Marginal Seas Using the DINEOF Method |
| title_fullStr | Reconstructing Gap-Free Daily Remote Sensing Reflectance in the Marginal Seas Using the DINEOF Method |
| title_full_unstemmed | Reconstructing Gap-Free Daily Remote Sensing Reflectance in the Marginal Seas Using the DINEOF Method |
| title_short | Reconstructing Gap-Free Daily Remote Sensing Reflectance in the Marginal Seas Using the DINEOF Method |
| title_sort | reconstructing gap free daily remote sensing reflectance in the marginal seas using the dineof method |
| topic | Data interpolating empirical orthogonal function (DINEOF) method gap-free data reconstruction marginal seas moderate resolution imaging spectroradiometer (MODIS) data remote sensing reflectance |
| url | https://ieeexplore.ieee.org/document/10973136/ |
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