Combined Impact of Sample Size and Modeling Approaches for Predicting Stem Volume in Eucalyptus spp. Forest Plantations Using Field and LiDAR Data (2020)
- Authors:
- Autor USP: ALMEIDA, DANILO ROBERTI ALVES DE - ESALQ
- Unidade: ESALQ
- DOI: 10.3390/rs12091438
- Subjects: ALGORITMOS; AMOSTRAGEM; APRENDIZADO COMPUTACIONAL; DENDROMETRIA; EUCALIPTO; MODELAGEM DE DADOS; TECNOLOGIA LIDAR
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Título: Remote Sensing
- ISSN: 2072-4292
- Volume/Número/Paginação/Ano: v. 12, p. 1-19, May 2020
- Este periódico é de acesso aberto
- Este artigo é de acesso aberto
- URL de acesso aberto
- Cor do Acesso Aberto: gold
- Licença: cc-by
-
ABNT
SILVA, Vanessa Sousa da et al. Combined Impact of Sample Size and Modeling Approaches for Predicting Stem Volume in Eucalyptus spp. Forest Plantations Using Field and LiDAR Data. Remote Sensing, v. 12, p. 1-19, 2020Tradução . . Disponível em: https://doi.org/10.3390/rs12091438. Acesso em: 27 dez. 2025. -
APA
Silva, V. S. da, Silva, C. A., Mohan, M., Cardil, A., Rex, F. E., Loureiro, G. H., et al. (2020). Combined Impact of Sample Size and Modeling Approaches for Predicting Stem Volume in Eucalyptus spp. Forest Plantations Using Field and LiDAR Data. Remote Sensing, 12, 1-19. doi:10.3390/rs12091438 -
NLM
Silva VS da, Silva CA, Mohan M, Cardil A, Rex FE, Loureiro GH, Almeida DRA de, Broadbent EN, Gorgens EB, Dalla Corte AP, Silva EA, Valbuena R, Klauberg C. Combined Impact of Sample Size and Modeling Approaches for Predicting Stem Volume in Eucalyptus spp. Forest Plantations Using Field and LiDAR Data [Internet]. Remote Sensing. 2020 ; 12 1-19.[citado 2025 dez. 27 ] Available from: https://doi.org/10.3390/rs12091438 -
Vancouver
Silva VS da, Silva CA, Mohan M, Cardil A, Rex FE, Loureiro GH, Almeida DRA de, Broadbent EN, Gorgens EB, Dalla Corte AP, Silva EA, Valbuena R, Klauberg C. Combined Impact of Sample Size and Modeling Approaches for Predicting Stem Volume in Eucalyptus spp. Forest Plantations Using Field and LiDAR Data [Internet]. Remote Sensing. 2020 ; 12 1-19.[citado 2025 dez. 27 ] Available from: https://doi.org/10.3390/rs12091438 - Assessing tropical forest degradation and restoration through lidar remote sensing
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Informações sobre o DOI: 10.3390/rs12091438 (Fonte: oaDOI API)
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