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Lightweight Neural Network for Spatiotemporal Filling of Data Gaps in Sea Surface Temperature Images

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Created 20/01/2025

Updated 20/01/2025

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Cloud coverage remains a key issue for researchers working with satellite data. Accurate reconstruction of measurements obstructed by cloud can enhance the usefulness of satellite databases for identifying trends and changes in various environments. In this work, we develop, train and test a bidirectional long short-term memory (BiLSTM) model with a custom temporal penalty layer for filling gaps in sea surface temperature (SST) images acquired by the Himawari- 8 satellite. The proposed model showed strong performance, achieving a per-image MAE of 0.1193◦C and per-image RMSE of 0.0985◦C. Our model is also shown to outperform previous state-of-the-art literature. Overall, this work shows that our BiLSTM algorithm is an effective tool for gapfilling cloud-affected SST data. Citation: S. Baker, Z. Huang and B. Philippa, "Lightweight Neural Network for Spatiotemporal Filling of Data Gaps in Sea Surface Temperature Images," in IEEE Transactions on Geoscience and Remote Sensing, vol. 61, pp. 1-10, 2023, Art no. 4204310, doi: 10.1109/TGRS.2023.3273575

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Title Lightweight Neural Network for Spatiotemporal Filling of Data Gaps in Sea Surface Temperature Images
Language eng
Licence notspecified
Landing Page https://devweb.dga.links.com.au/data/dataset/7287c291-3e8c-4d70-a5fb-196550c90ea9
Contact Point
Geoscience Australia
clientservices@ga.gov.au
Reference Period 08/04/2019
Geospatial Coverage {"type": "Polygon", "coordinates": [[[112.0, -44.0], [154.0, -44.0], [154.0, -9.0], [112.0, -9.0], [112.0, -44.0]]]}
Data Portal data.gov.au

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This dataset was originally found on data.gov.au "Lightweight Neural Network for Spatiotemporal Filling of Data Gaps in Sea Surface Temperature Images". Please visit the source to access the original metadata of the dataset:
https://devweb.dga.links.com.au/data/dataset/lightweight-neural-network-for-spatiotemporal-filling-of-data-gaps-in-sea-surface-temperature-i

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