Estimated chlorophyall-a concentration at 60 m spatial resolution (20220307)

Fuente: Zenodo

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Bibliographische Detailangaben
Hauptverfasser:	Serpico, Bruno Sebastiano, Moser, Gabriele, Basit, Abdul, Castellano, Michela, Massa, Francesco, Ciuffardi, Tiziana
Format:	Recurso digital
Sprache:	Englisch
Veröffentlicht:	Zenodo 2026
Schlagworte:	Chlorophyll-a Copernicus Programme Earth Science > Oceans > Ocean Optics > Chlorophyll (15Cc550B-068C-49F4-B082-Bc2A43675606) Earth Science Services > Models > Machine Learning Models (fe4392b0-13a9-43ff-bacc-f44a65aed4fa) Earth Science Services > Models > Machine Learning Models > Ensemble Models > Random Forest (A68048F4-181C-4C6C-9Bfa-9E4171E9F237) Instruments > Earth Remote Sensing Instruments (6015ef7b-f3bd-49e1-9193-cc23db566b69) Ligurian Sea Machine Learning Marine Environment Mondrian Forest Random Forest Remote Sensing Satellite Oceanography Sentinel-2 Space-based Platforms > Earth Observation Satellites (3466eed1-2fbb-49bf-ab0b-dc08731d502b) Thermal Infrared
Online-Zugang:	Acceder al recurso
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