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Artigo de periodico
Real-time and post-mission heading alignment for drone navigation based on single-antenna GNSS and MEMs-IMU sensors (2025)
Contreras, João F. ; Vassaram, Jitesh A. M. ; Fernandes, Marcos Rogério ; Val, João Bosco Ribeiro do
Source: Drones. Unidade: EESC
Subjects: SENSOR, PROCESSAMENTO DE SINAIS, AERONAVES NÃO TRIPULADAS, ENGENHARIA ELÉTRICA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
CONTRERAS, João F. et al. Real-time and post-mission heading alignment for drone navigation based on single-antenna GNSS and MEMs-IMU sensors. Drones, v. 9, n. 3, p. 1-18, 2025Tradução . . Disponível em: https://dx.doi.org/10.3390/drones9030169. Acesso em: 03 jan. 2026.
APA
Contreras, J. F., Vassaram, J. A. M., Fernandes, M. R., & Val, J. B. R. do. (2025). Real-time and post-mission heading alignment for drone navigation based on single-antenna GNSS and MEMs-IMU sensors. Drones, 9( 3), 1-18. doi:10.3390/drones9030169
NLM
Contreras JF, Vassaram JAM, Fernandes MR, Val JBR do. Real-time and post-mission heading alignment for drone navigation based on single-antenna GNSS and MEMs-IMU sensors [Internet]. Drones. 2025 ; 9( 3): 1-18.[citado 2026 jan. 03 ] Available from: https://dx.doi.org/10.3390/drones9030169
Vancouver
Contreras JF, Vassaram JAM, Fernandes MR, Val JBR do. Real-time and post-mission heading alignment for drone navigation based on single-antenna GNSS and MEMs-IMU sensors [Internet]. Drones. 2025 ; 9( 3): 1-18.[citado 2026 jan. 03 ] Available from: https://dx.doi.org/10.3390/drones9030169
Artigo de periodico
Assessing the temporal and spatial variability of coffee plantation using RPA-based RGB imaging (2022)
Martello, Maurício ; Molin, José Paulo ; Angnes, Graciele ; Acorsi, Matheus Gabriel
Source: Drones. Unidade: ESALQ
Subjects: AERONAVES NÃO TRIPULADAS, AGRICULTURA DE PRECISÃO, CAFÉ, IMAGEM 3D, VARIABILIDADE ESPACIAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
MARTELLO, Maurício et al. Assessing the temporal and spatial variability of coffee plantation using RPA-based RGB imaging. Drones, v. 6, p. 1-17, 2022Tradução . . Disponível em: https://doi.org/10.3390/drones6100267. Acesso em: 03 jan. 2026.
APA
Martello, M., Molin, J. P., Angnes, G., & Acorsi, M. G. (2022). Assessing the temporal and spatial variability of coffee plantation using RPA-based RGB imaging. Drones, 6, 1-17. doi:10.3390/drones6100267
NLM
Martello M, Molin JP, Angnes G, Acorsi MG. Assessing the temporal and spatial variability of coffee plantation using RPA-based RGB imaging [Internet]. Drones. 2022 ; 6 1-17.[citado 2026 jan. 03 ] Available from: https://doi.org/10.3390/drones6100267
Vancouver
Martello M, Molin JP, Angnes G, Acorsi MG. Assessing the temporal and spatial variability of coffee plantation using RPA-based RGB imaging [Internet]. Drones. 2022 ; 6 1-17.[citado 2026 jan. 03 ] Available from: https://doi.org/10.3390/drones6100267
Artigo de periodico
High-Density UAV-LiDAR in an Integrated Crop-Livestock-Forest System: Sampling Forest Inventory or Forest Inventory Based on Individual Tree Detection (ITD) (2022)
Corte, Ana Paula Dalla ; Cunha Neto, Ernandes Macedo da ; Rex, Franciel Eduardo; Souza, Deivison ; Behling, Alexandre; Mohan, Midhun; Sanquetta, Mateus Niroh Inoue ; Silva, Carlos Alberto ; Klauberg, Carine; Sanquetta, Carlos Roberto; Veras, Hudson Franklin Pessoa; Almeida, Danilo Roberti Alves de ; Prata, Gabriel ; Zambrano, Angelica Maria Almeyda ; Trautenmüller, Jonathan William; Moraes, Anibal de; Karasinski, Mauro Alessandro; Broadbent, Eben North
Source: Drones. Unidade: ESALQ
Subjects: AERONAVES NÃO TRIPULADAS, AMOSTRAGEM, EUCALIPTO, INVENTÁRIO FLORESTAL, SISTEMAS AGROSSILVIPASTORIS, TECNOLOGIA LIDAR
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
CORTE, Ana Paula Dalla et al. High-Density UAV-LiDAR in an Integrated Crop-Livestock-Forest System: Sampling Forest Inventory or Forest Inventory Based on Individual Tree Detection (ITD). Drones, v. 6, p. 1-18, 2022Tradução . . Disponível em: https://doi.org/10.3390/drones6020048. Acesso em: 03 jan. 2026.
APA
Corte, A. P. D., Cunha Neto, E. M. da, Rex, F. E., Souza, D., Behling, A., Mohan, M., et al. (2022). High-Density UAV-LiDAR in an Integrated Crop-Livestock-Forest System: Sampling Forest Inventory or Forest Inventory Based on Individual Tree Detection (ITD). Drones, 6, 1-18. doi:10.3390/drones6020048
NLM
Corte APD, Cunha Neto EM da, Rex FE, Souza D, Behling A, Mohan M, Sanquetta MNI, Silva CA, Klauberg C, Sanquetta CR, Veras HFP, Almeida DRA de, Prata G, Zambrano AMA, Trautenmüller JW, Moraes A de, Karasinski MA, Broadbent EN. High-Density UAV-LiDAR in an Integrated Crop-Livestock-Forest System: Sampling Forest Inventory or Forest Inventory Based on Individual Tree Detection (ITD) [Internet]. Drones. 2022 ; 6 1-18.[citado 2026 jan. 03 ] Available from: https://doi.org/10.3390/drones6020048
Vancouver
Corte APD, Cunha Neto EM da, Rex FE, Souza D, Behling A, Mohan M, Sanquetta MNI, Silva CA, Klauberg C, Sanquetta CR, Veras HFP, Almeida DRA de, Prata G, Zambrano AMA, Trautenmüller JW, Moraes A de, Karasinski MA, Broadbent EN. High-Density UAV-LiDAR in an Integrated Crop-Livestock-Forest System: Sampling Forest Inventory or Forest Inventory Based on Individual Tree Detection (ITD) [Internet]. Drones. 2022 ; 6 1-18.[citado 2026 jan. 03 ] Available from: https://doi.org/10.3390/drones6020048

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