Optimal sample size and composition for crop classification with Sen2-Agri’s random forest classifier
Type:
Title:
Optimal sample size and composition for crop classification with Sen2-Agri’s random forest classifier
Creator:
Schulthess, U.;
Rodrigues, F.;
https://orcid.org/0000-0001-7273-2217
Scopus ID
Researcher ID
Mendeley
Items in this Repository
View
Taymans, M.;
Bellemans, N.;
Bontemps, S.;
Ortiz-Monasterio, I.;
Gerard, B.;
Defourny, P.
Rodrigues, F.;
Rodrigues, F.
https://orcid.org/0000-0001-7273-2217
Scopus ID
Researcher ID
Mendeley
Items in this Repository
View
Taymans, M.;
Bellemans, N.;
Bontemps, S.;
Ortiz-Monasterio, I.;
Gerard, B.;
Defourny, P.
Year:
2023
Copyright:
CIMMYT manages Intellectual Assets as International Public Goods. The user is free to download, print, store and share this work. In case you want to translate or create any other derivative work and share or distribute such translation/derivative work, please contact CIMMYT-Knowledge-Center@cgiar.org indicating the work you want to use and the kind of use you intend; CIMMYT will contact you with the suitable license for that purpose
Journal:
Remote Sensing
Journal volume:
15
Journal issue:
3
Article number:
608
DOI:
Place of Publication:
Basel (Switzerland)
Publisher:
MDPI
Related Datasets
CGIAR Initiatives
Initiative:
Digital Innovation
Impact Area:
Nutrition, health & food security
Poverty reduction, livelihoods & jobs
Poverty reduction, livelihoods & jobs
Action Area:
Systems Transformation
Resilient Agrifood Systems
Resilient Agrifood Systems
Donor or Funder:
CGIAR Research Program on Maize
CGIAR Research Program on Wheat
Henan Agricultural University
CGIAR Trust Fund
CGIAR Research Program on Wheat
Henan Agricultural University
CGIAR Trust Fund
CGSpace URL:
