Estimating leaf mass per area and equivalent water thickness based on leaf optical properties: potential and limitations of physical modeling and machine learning (2019)
- Authors:
- Autor USP: NOUVELLON, YANN PIERRE - ESALQ
- Unidade: ESALQ
- DOI: 10.1016/j.rse.2018.11.002
- Subjects: ESPECTROSCOPIA INFRAVERMELHA; FOLHAS (PLANTAS); SENSORIAMENTO REMOTO; VEGETAÇÃO
- Agências de fomento:
- Luc Bidel, Christophe François and Gabriel Pavan
- TOSCA program grant of the French Space Agency (CNES)
- International Network for Terrestrial Research and Monitoring in the Arctic (INTERACT)
- Financiado pela CAPES
- ITATINGA genotype test is funded in part by the EUCFLUX
- Agence Nationale de la Recherche
- Nouragues Field Station
- Language: Inglês
- Imprenta:
- Source:
- Título: Remote Sensing of Environment
- ISSN: 0034-4257
- Volume/Número/Paginação/Ano: v. 231, p. 1-14, 2019
- Status:
- Artigo possui versão em acesso aberto em repositório (Green Open Access)
- Versão do Documento:
- Versão submetida (Pré-print)
- Acessar versão aberta:
-
ABNT
FERET, J-B et al. Estimating leaf mass per area and equivalent water thickness based on leaf optical properties: potential and limitations of physical modeling and machine learning. Remote Sensing of Environment, v. 231, p. 1-14, 2019Tradução . . Disponível em: https://doi.org/10.1016/j.rse.2018.11.002. Acesso em: 01 abr. 2026. -
APA
Feret, J. -B., Maire, G. le, Jay, S., Berveiller, D., Bendoula, R., Hmimina, G., et al. (2019). Estimating leaf mass per area and equivalent water thickness based on leaf optical properties: potential and limitations of physical modeling and machine learning. Remote Sensing of Environment, 231, 1-14. doi:10.1016/j.rse.2018.11.002 -
NLM
Feret J-B, Maire G le, Jay S, Berveiller D, Bendoula R, Hmimina G, Cheraiet A, Oliveira JC, Ponzoni FJ, Solanki T, Boissieu F de, Chave J, Nouvellon YP, Porcar-Castell A, Proisy C, Soudani K, Gastellu-Etchegorry J-P, Lefevre-Fonollosa M-J. Estimating leaf mass per area and equivalent water thickness based on leaf optical properties: potential and limitations of physical modeling and machine learning [Internet]. Remote Sensing of Environment. 2019 ; 231 1-14.[citado 2026 abr. 01 ] Available from: https://doi.org/10.1016/j.rse.2018.11.002 -
Vancouver
Feret J-B, Maire G le, Jay S, Berveiller D, Bendoula R, Hmimina G, Cheraiet A, Oliveira JC, Ponzoni FJ, Solanki T, Boissieu F de, Chave J, Nouvellon YP, Porcar-Castell A, Proisy C, Soudani K, Gastellu-Etchegorry J-P, Lefevre-Fonollosa M-J. Estimating leaf mass per area and equivalent water thickness based on leaf optical properties: potential and limitations of physical modeling and machine learning [Internet]. Remote Sensing of Environment. 2019 ; 231 1-14.[citado 2026 abr. 01 ] Available from: https://doi.org/10.1016/j.rse.2018.11.002 - Growth and maintenance respiration of roots of clonal Eucalyptus cuttings: scaling to stand-level
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| Tipo | Nome | Link | |
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| 2966383-Estimating leaf m... | Direct link |
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