Fonte: Geoderma. Unidade: ESALQ
Assuntos: ANÁLISE MULTIVARIADA, CARBONO, ESPECTROS, SENSORIAMENTO REMOTO, SOLOS
ABNT
MOURA-BUENO, Jean Michel et al. Stratification of a local VIS-NIR-SWIR spectral library by homogeneity criteria yields more accurate soil organic carbon predictions. Geoderma, v. 337, p. 565-581, 2019Tradução . . Disponível em: https://doi.org/10.1016/j.geoderma.2018.10.015. Acesso em: 11 nov. 2025.APA
Moura-Bueno, J. M., Dalmolin, R. S. D., ten Caten, A., Dotto, A. C., & Demattê, J. A. M. (2019). Stratification of a local VIS-NIR-SWIR spectral library by homogeneity criteria yields more accurate soil organic carbon predictions. Geoderma, 337, 565-581. doi:10.1016/j.geoderma.2018.10.015NLM
Moura-Bueno JM, Dalmolin RSD, ten Caten A, Dotto AC, Demattê JAM. Stratification of a local VIS-NIR-SWIR spectral library by homogeneity criteria yields more accurate soil organic carbon predictions [Internet]. Geoderma. 2019 ; 337 565-581.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1016/j.geoderma.2018.10.015Vancouver
Moura-Bueno JM, Dalmolin RSD, ten Caten A, Dotto AC, Demattê JAM. Stratification of a local VIS-NIR-SWIR spectral library by homogeneity criteria yields more accurate soil organic carbon predictions [Internet]. Geoderma. 2019 ; 337 565-581.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1016/j.geoderma.2018.10.015
