Characterization of portuguese sown rainfed grasslands using remote sensing and machine learning

Sown biodiverse pastures (SBP) enhance grassland productivity and reduce fertilizer use in Portugal. Researchers used Sentinel-2 remote sensing to assess aboveground biomass; legume fraction; and nitrogen and phosphorus content across six farms in 2018 and 2019; employing various machine learning models for analysis.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-05-07
DOI
https://doi.org/10.5281/zenodo.15358122
Primary Topic
Genetic Associations and Epidemiology
Type
article
Field-Weighted Citation Impact
0.00
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article

Characterization of portuguese sown rainfed grasslands using remote sensing and machine learning

Zenodo (CERN European Organization for Nuclear Research)
Genetic Associations and Epidemiology
article

Characterization of portuguese sown rainfed grasslands using remote sensing and machine learning

article en

Abstract

Sown biodiverse pastures (SBP) enhance grassland productivity and reduce fertilizer use in Portugal. Researchers used Sentinel-2 remote sensing to assess aboveground biomass; legume fraction; and nitrogen and phosphorus content across six farms in 2018 and 2019; employing various machine learning models for analysis.

Zenodo (CERN European Organization for Nuclear Research)
Vale (Brazil) (BR)
Zero hunger
Openalex Percentile: Top 50%
Genetic Associations and Epidemiology
DOIOpen Access PDFOpenAlex
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Characterization of portuguese sown rainfed grasslands using remote sensing and machine learning · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS