Source: Remote Sensing. Unidade: ESALQ
Subjects: APRENDIZADO COMPUTACIONAL, ECOLOGIA DA RESTAURAÇÃO, ESPECTROSCOPIA, FLORESTAS TROPICAIS, LUZ, TECNOLOGIA LIDAR, SENSORIAMENTO REMOTO
ABNT
ALMEIDA, Catherine Torres de et al. Advancing forest degradation and regeneration assessment Through light detection and ranging and hyperspectral imaging integration. Remote Sensing, v. 16, p. 1-26, 2024Tradução . . Disponível em: https://doi.org/10.3390/rs16213935. Acesso em: 06 jan. 2025.APA
Almeida, C. T. de, Galvão, L. S., Ometto, J. P. H. B., Jacon, A. D., Pereira, F. R. de S., Sato, L. Y., et al. (2024). Advancing forest degradation and regeneration assessment Through light detection and ranging and hyperspectral imaging integration. Remote Sensing, 16, 1-26. doi:10.3390/rs16213935NLM
Almeida CT de, Galvão LS, Ometto JPHB, Jacon AD, Pereira FR de S, Sato LY, Silva-Junior CHL, Brancalion PHS, Aragão LEO e C de. Advancing forest degradation and regeneration assessment Through light detection and ranging and hyperspectral imaging integration [Internet]. Remote Sensing. 2024 ; 16 1-26.[citado 2025 jan. 06 ] Available from: https://doi.org/10.3390/rs16213935Vancouver
Almeida CT de, Galvão LS, Ometto JPHB, Jacon AD, Pereira FR de S, Sato LY, Silva-Junior CHL, Brancalion PHS, Aragão LEO e C de. Advancing forest degradation and regeneration assessment Through light detection and ranging and hyperspectral imaging integration [Internet]. Remote Sensing. 2024 ; 16 1-26.[citado 2025 jan. 06 ] Available from: https://doi.org/10.3390/rs16213935