Fonte: Journal of Applied Remote Sensing. Unidades: FZEA, ESALQ
Assuntos: CULTIVO DE PLANTAS, MILHO, REGRESSÃO LINEAR
ABNT
MAGALHÃES, Leonardo Pinto de e ROSSI, Fabricio. Estimation of canopy water content in maize using machine learning and multispectral vegetation indices: comparison of Adaboost regression and other methods. Journal of Applied Remote Sensing, v. 18, n. 4, p. 1-17, 2024Tradução . . Disponível em: https://doi.org/10.1117/1.JRS.18.042609. Acesso em: 05 dez. 2025.APA
Magalhães, L. P. de, & Rossi, F. (2024). Estimation of canopy water content in maize using machine learning and multispectral vegetation indices: comparison of Adaboost regression and other methods. Journal of Applied Remote Sensing, 18( 4), 1-17. doi:10.1117/1.JRS.18.042609NLM
Magalhães LP de, Rossi F. Estimation of canopy water content in maize using machine learning and multispectral vegetation indices: comparison of Adaboost regression and other methods [Internet]. Journal of Applied Remote Sensing. 2024 ; 18( 4): 1-17.[citado 2025 dez. 05 ] Available from: https://doi.org/10.1117/1.JRS.18.042609Vancouver
Magalhães LP de, Rossi F. Estimation of canopy water content in maize using machine learning and multispectral vegetation indices: comparison of Adaboost regression and other methods [Internet]. Journal of Applied Remote Sensing. 2024 ; 18( 4): 1-17.[citado 2025 dez. 05 ] Available from: https://doi.org/10.1117/1.JRS.18.042609
