Source: Remote Sensing. Unidade: ESALQ
Subjects: SALINIDADE DO SOLO, MAPEAMENTO DO SOLO, SENSORIAMENTO REMOTO, APRENDIZADO COMPUTACIONAL, ALGORITMOS
ABNT
NAIMI, Salman et al. Ground observations and environmental covariates integration for mapping of soil salinity: a machine learning-based approach. Remote Sensing, v. 13, p. 1-21, 2021Tradução . . Disponível em: https://doi.org/10.3390/rs13234825. Acesso em: 10 jun. 2024.APA
Naimi, S., Ayoubi, S., Zeraatpisheh, M., & Dematte, J. A. M. (2021). Ground observations and environmental covariates integration for mapping of soil salinity: a machine learning-based approach. Remote Sensing, 13, 1-21. doi:10.3390/rs13234825NLM
Naimi S, Ayoubi S, Zeraatpisheh M, Dematte JAM. Ground observations and environmental covariates integration for mapping of soil salinity: a machine learning-based approach [Internet]. Remote Sensing. 2021 ; 13 1-21.[citado 2024 jun. 10 ] Available from: https://doi.org/10.3390/rs13234825Vancouver
Naimi S, Ayoubi S, Zeraatpisheh M, Dematte JAM. Ground observations and environmental covariates integration for mapping of soil salinity: a machine learning-based approach [Internet]. Remote Sensing. 2021 ; 13 1-21.[citado 2024 jun. 10 ] Available from: https://doi.org/10.3390/rs13234825