A conceptual model for detecting small-scale forest disturbances based on ecosystem worphological traits (2022)
- Authors:
- Autor USP: ALMEIDA, DANILO ROBERTI ALVES DE - ESALQ
- Unidade: ESALQ
- DOI: 10.3390/rs14040933
- Subjects: CARBONO; CORTE (PLANTAS); DOSSEL (BOTÂNICA); ECOSSISTEMAS FLORESTAIS; FLORESTAS TROPICAIS; MODELAGEM DE DADOS; SENSORIAMENTO REMOTO; TECNOLOGIA LIDAR
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Título do periódico: Remote Sensing
- ISSN: 2072-4292
- Volume/Número/Paginação/Ano: v. 14, art. 933, p. 1-20, February 2022
- 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
STODDART, Jaz et al. A conceptual model for detecting small-scale forest disturbances based on ecosystem worphological traits. Remote Sensing, v. 14, p. 1-20, 2022Tradução . . Disponível em: https://doi.org/10.3390/rs14040933. Acesso em: 20 maio 2024. -
APA
Stoddart, J., Almeida, D. R. A. de, Silva, C. A., Görgens, E. B., Keller, M., & Valbuena, R. (2022). A conceptual model for detecting small-scale forest disturbances based on ecosystem worphological traits. Remote Sensing, 14, 1-20. doi:10.3390/rs14040933 -
NLM
Stoddart J, Almeida DRA de, Silva CA, Görgens EB, Keller M, Valbuena R. A conceptual model for detecting small-scale forest disturbances based on ecosystem worphological traits [Internet]. Remote Sensing. 2022 ; 14 1-20.[citado 2024 maio 20 ] Available from: https://doi.org/10.3390/rs14040933 -
Vancouver
Stoddart J, Almeida DRA de, Silva CA, Görgens EB, Keller M, Valbuena R. A conceptual model for detecting small-scale forest disturbances based on ecosystem worphological traits [Internet]. Remote Sensing. 2022 ; 14 1-20.[citado 2024 maio 20 ] Available from: https://doi.org/10.3390/rs14040933 - High-Density UAV-LiDAR in an Integrated Crop-Livestock-Forest System: Sampling Forest Inventory or Forest Inventory Based on Individual Tree Detection (ITD)
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Informações sobre o DOI: 10.3390/rs14040933 (Fonte: oaDOI API)
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