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Retrieval of rice biophysical parameters from Sentinel‑2 using parsimonious multi‑output machine learning

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Published in:Agrosystems, Geosciences & Environment
Format: Online Article RSS Article
Published: 2026
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container_title Agrosystems, Geosciences & Environment
description
discipline_display Environmental Studies
discipline_facet Environmental Studies
format Online Article
RSS Article
genre Journal Article
id rss_article:72201
institution FRELIP
journal_source_facet Agrosystems, Geosciences & Environment
publishDate 2026
publishDateSort 2026
record_format rss_article
spellingShingle Retrieval of rice biophysical parameters from Sentinel‑2 using parsimonious multi‑output machine learning
Environmental Studies
General
Environmental Studies
sub_discipline_display General
sub_discipline_facet General
subject_display Environmental Studies
General
Environmental Studies
Environmental Studies
General
Environmental Studies
subject_facet Environmental Studies
General
Environmental Studies
title Retrieval of rice biophysical parameters from Sentinel‑2 using parsimonious multi‑output machine learning
title_auth Retrieval of rice biophysical parameters from Sentinel‑2 using parsimonious multi‑output machine learning
title_full Retrieval of rice biophysical parameters from Sentinel‑2 using parsimonious multi‑output machine learning
title_fullStr Retrieval of rice biophysical parameters from Sentinel‑2 using parsimonious multi‑output machine learning
title_full_unstemmed Retrieval of rice biophysical parameters from Sentinel‑2 using parsimonious multi‑output machine learning
title_short Retrieval of rice biophysical parameters from Sentinel‑2 using parsimonious multi‑output machine learning
title_sort retrieval of rice biophysical parameters from sentinel‑2 using parsimonious multi‑output machine learning
topic Environmental Studies
General
Environmental Studies
url https://acsess.onlinelibrary.wiley.com/doi/10.1002/agg2.70381?af=R