Evaluating observed versus predicted forest biomass: R-squared, index of agreement or maximal information coefficient? (2019)
- Authors:
- Autor USP: ALMEIDA, DANILO ROBERTI ALVES DE - ESALQ
- Unidade: ESALQ
- DOI: 10.1080/22797254.2019.1605624
- Subjects: BIOMASSA; FLORESTAS; MODELOS MATEMÁTICOS; TECNOLOGIA LIDAR
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Título: European Journal of Remote Sensing
- ISSN: 2279-7254
- Volume/Número/Paginação/Ano: v. 52, n. 1, p. 345-358, 2019
- 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
VALBUENA, Ruben et al. Evaluating observed versus predicted forest biomass: R-squared, index of agreement or maximal information coefficient?. European Journal of Remote Sensing, v. 52, n. 1, p. 345-358, 2019Tradução . . Disponível em: https://doi.org/10.1080/22797254.2019.1605624. Acesso em: 27 dez. 2025. -
APA
Valbuena, R., Hernando, A., Manzanera, J. A., Görgens, E. B., Almeida, D. R. A. de, Silva, C. A., & García-Abril, A. (2019). Evaluating observed versus predicted forest biomass: R-squared, index of agreement or maximal information coefficient? European Journal of Remote Sensing, 52( 1), 345-358. doi:10.1080/22797254.2019.1605624 -
NLM
Valbuena R, Hernando A, Manzanera JA, Görgens EB, Almeida DRA de, Silva CA, García-Abril A. Evaluating observed versus predicted forest biomass: R-squared, index of agreement or maximal information coefficient? [Internet]. European Journal of Remote Sensing. 2019 ; 52( 1): 345-358.[citado 2025 dez. 27 ] Available from: https://doi.org/10.1080/22797254.2019.1605624 -
Vancouver
Valbuena R, Hernando A, Manzanera JA, Görgens EB, Almeida DRA de, Silva CA, García-Abril A. Evaluating observed versus predicted forest biomass: R-squared, index of agreement or maximal information coefficient? [Internet]. European Journal of Remote Sensing. 2019 ; 52( 1): 345-358.[citado 2025 dez. 27 ] Available from: https://doi.org/10.1080/22797254.2019.1605624 - Assessing tropical forest degradation and restoration through lidar remote sensing
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Informações sobre o DOI: 10.1080/22797254.2019.1605624 (Fonte: oaDOI API)
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