Silva, Carlos Alberto; Hudak, Andrew T; Vierling, Lee A; Valbuena, Ruben; Cardil, Adrian; Mohan, Midhun; Almeida, Danilo Roberti Alves de 
; Broadbent, Eben North ; Zambrano, Angelica M. Almeyda; Wilkinson, Ben; Sharma, Ajay; Drake, Jason B; Medley, Paul B; Vogel, Jason G; Prata, Gabriel Atticciati; Atkins, Jeff W; Hamamura, Caio; Johnson, Daniel J; Klauberg, Carine
Fonte: Methods in Ecology and Evolution. Unidade: ESALQ
Assuntos: ÁRVORES FLORESTAIS, DISTRIBUIÇÃO ESPACIAL, DOSSEL (BOTÂNICA), R (SOFTWARE ESTATÍSTICO), TECNOLOGIA LIDAR
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SILVA, Carlos Alberto et al. Treetop: A Shiny-based application and R package for extracting forest information from LiDAR data for ecologists and conservationists. Methods in Ecology and Evolution, p. 1–13, 2022Tradução . . Disponível em: https://doi.org/10.1111/2041-210X.13830. Acesso em: 11 nov. 2024.APA
Silva, C. A., Hudak, A. T., Vierling, L. A., Valbuena, R., Cardil, A., Mohan, M., et al. (2022). Treetop: A Shiny-based application and R package for extracting forest information from LiDAR data for ecologists and conservationists. Methods in Ecology and Evolution, 1–13. doi:10.1111/2041-210X.13830NLM
Silva CA, Hudak AT, Vierling LA, Valbuena R, Cardil A, Mohan M, Almeida DRA de, Broadbent EN, Zambrano AMA, Wilkinson B, Sharma A, Drake JB, Medley PB, Vogel JG, Prata GA, Atkins JW, Hamamura C, Johnson DJ, Klauberg C. Treetop: A Shiny-based application and R package for extracting forest information from LiDAR data for ecologists and conservationists [Internet]. Methods in Ecology and Evolution. 2022 ; 1–13.[citado 2024 nov. 11 ] Available from: https://doi.org/10.1111/2041-210X.13830Vancouver
Silva CA, Hudak AT, Vierling LA, Valbuena R, Cardil A, Mohan M, Almeida DRA de, Broadbent EN, Zambrano AMA, Wilkinson B, Sharma A, Drake JB, Medley PB, Vogel JG, Prata GA, Atkins JW, Hamamura C, Johnson DJ, Klauberg C. Treetop: A Shiny-based application and R package for extracting forest information from LiDAR data for ecologists and conservationists [Internet]. Methods in Ecology and Evolution. 2022 ; 1–13.[citado 2024 nov. 11 ] Available from: https://doi.org/10.1111/2041-210X.13830
