Crop Nitrogen Retrieval Methods for Simulated Sentinel-2 Data Using In-Field Spectrometer Data.

ARTMO toolbox agro-ecosystem monitoring chlorophyll gaussian processes regression leaf area index nitrogen random forest spectral indices

Journal

Remote sensing
ISSN: 2072-4292
Titre abrégé: Remote Sens (Basel)
Pays: Switzerland
ID NLM: 101624426

Informations de publication

Date de publication:
19 Jun 2021
Historique:
entrez: 9 9 2022
pubmed: 19 6 2021
medline: 19 6 2021
Statut: epublish

Résumé

Nitrogen (N) is one of the key nutrients supplied in agricultural production worldwide. Over-fertilization can have negative influences on the field and the regional level (e.g., agro-ecosystems). Remote sensing of the plant N of field crops presents a valuable tool for the monitoring of N flows in agro-ecosystems. Available data for validation of satellite-based remote sensing of N is scarce. Therefore, in this study, field spectrometer measurements were used to simulate data of the Sentinel-2 (S2) satellites developed for vegetation monitoring by the ESA. The prediction performance of normalized ratio indices (NRIs), random forest regression (RFR) and Gaussian processes regression (GPR) for plant-N-related traits was assessed on a diverse real-world dataset including multiple crops, field sites and years. The plant N traits included the mass-based N measure, N concentration in the biomass (N

Identifiants

pubmed: 36082363
doi: 10.3390/rs13122404
pmc: PMC7613346
mid: EMS152668
doi:

Types de publication

Journal Article

Langues

eng

Pagination

2404

Subventions

Organisme : European Research Council
ID : 755617
Pays : International

Déclaration de conflit d'intérêts

Conflicts of Interest: The authors declare no conflict of interest.

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Auteurs

Gregor Perich (G)

Group of Crop Science, Institute of Agricultural Sciences, Department of Environmental Systems Science, ETH Zurich, 8092 Zurich, Switzerland.

Helge Aasen (H)

Group of Crop Science, Institute of Agricultural Sciences, Department of Environmental Systems Science, ETH Zurich, 8092 Zurich, Switzerland.

Jochem Verrelst (J)

Image Processing Laboratory (IPL), University of Valencia Science Park, 46980 Valencia, Spain.

Francesco Argento (F)

Group of Crop Science, Institute of Agricultural Sciences, Department of Environmental Systems Science, ETH Zurich, 8092 Zurich, Switzerland.

Achim Walter (A)

Group of Crop Science, Institute of Agricultural Sciences, Department of Environmental Systems Science, ETH Zurich, 8092 Zurich, Switzerland.

Frank Liebisch (F)

Group of Crop Science, Institute of Agricultural Sciences, Department of Environmental Systems Science, ETH Zurich, 8092 Zurich, Switzerland.
Water Protection and Substance Flows, Department Agroecology and Environment, Agroscope, 8046 Zürich, Switzerland.

Classifications MeSH