Estimated chlorophyall-a concentration at 60 m spatial resolution (20220307)
Abstract
The dataset consists of estimated chlorophyll-a (CHL-a) concentration maps obtained as the output of a machine learning model. Multispectral data from twelve bands of the Sentinel-2 mission of the Copernicus Programme of the European Union, together with in situ CHL-a measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework. Full metadata: https://erddap.s4raise.it/erddap/info/unige-diten_chlorophyll_final_output_laspezia_20220307/index.htmlThis 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).
Fields of Study & Subjects
Marine Plankton and Biogeochemistry
Remote-Sensing Image Classification
Water Quality Monitoring Technologies
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 9 March 2026
- Language
- EN
- Document type
- Dataset