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| Main Authors: | , , , , , |
|---|---|
| Format: | Recurso digital |
| Language: | English |
| Published: |
Zenodo
2026
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| Subjects: | |
| Online Access: | https://doi.org/10.5281/zenodo.19329039 |
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Table of Contents:
- The dataset consists of estimated sea surface temperature (SST) obtained as the output of a machine learning model. Thermal infrared data from the Sentinel-3 mission of the Copernicus programme of the European Union, together with in situ sea-truth temperature measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework <br><br>Full metadata: <a href="https://erddap.s4raise.it/erddap/info/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240607T095649/index.html" target="_blank">https://erddap.s4raise.it/erddap/info/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240607T095649/index.html</a><br><br>This dataset is part of the RAISE Spoke 3 project outcomes. RAISE is an innovation ecosystem funded by the Ministry of University and Research under the National Recovery and Resilience Plan (NRRP, Mission 4, Component 2, Investment 1.5).