ReP USP - Resultado da busca

Artigo de periodico
A new methodological framework for geophysical sensor combinations associated with machine learning algorithms to understand soil attributes (2022)
Mello, Danilo César de ; Veloso, Gustavo Vieira ; Lana, Marcos Guedes de; Mello, Fellipe Alcantara de Oliveira ; Poppiel, Raul Roberto ; Cabrero, Diego Ribeiro Oquendo; Di Raimo, Luis Augusto Di Loreto ; Schaefer, Carlos Ernesto Gonçalves Reynaud; Fernandes Filho, Elpídio Inácio ; Leite, Emilson Pereira; Demattê, José Alexandre Melo
Fonte: Geoscientific Model Development. Unidade: ESALQ
Assuntos: ALGORITMOS, APRENDIZADO COMPUTACIONAL, FRAMEWORKS, GEOFÍSICA, MODELAGEM DE DADOS, SENSOR, SOLOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
MELLO, Danilo César de et al. A new methodological framework for geophysical sensor combinations associated with machine learning algorithms to understand soil attributes. Geoscientific Model Development, v. 15, p. 1219–1246, 2022Tradução . . Disponível em: https://doi.org/10.5194/gmd-15-1219-2022. Acesso em: 30 nov. 2025.
APA
Mello, D. C. de, Veloso, G. V., Lana, M. G. de, Mello, F. A. de O., Poppiel, R. R., Cabrero, D. R. O., et al. (2022). A new methodological framework for geophysical sensor combinations associated with machine learning algorithms to understand soil attributes. Geoscientific Model Development, 15, 1219–1246. doi:10.5194/gmd-15-1219-2022
NLM
Mello DC de, Veloso GV, Lana MG de, Mello FA de O, Poppiel RR, Cabrero DRO, Di Raimo LADL, Schaefer CEGR, Fernandes Filho EI, Leite EP, Demattê JAM. A new methodological framework for geophysical sensor combinations associated with machine learning algorithms to understand soil attributes [Internet]. Geoscientific Model Development. 2022 ; 15 1219–1246.[citado 2025 nov. 30 ] Available from: https://doi.org/10.5194/gmd-15-1219-2022
Vancouver
Mello DC de, Veloso GV, Lana MG de, Mello FA de O, Poppiel RR, Cabrero DRO, Di Raimo LADL, Schaefer CEGR, Fernandes Filho EI, Leite EP, Demattê JAM. A new methodological framework for geophysical sensor combinations associated with machine learning algorithms to understand soil attributes [Internet]. Geoscientific Model Development. 2022 ; 15 1219–1246.[citado 2025 nov. 30 ] Available from: https://doi.org/10.5194/gmd-15-1219-2022
Artigo de periodico
Topography-based local spherical Voronoi grid refinement on classical and moist shallow-water finite-volume models (2021)
Santos, Luan da Fonseca ; Peixoto, Pedro da Silva
Fonte: Geoscientific Model Development. Unidade: IME
Assuntos: MÉTODOS NUMÉRICOS, EQUAÇÕES DIFERENCIAIS, GEODÉSIA ESPACIAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SANTOS, Luan da Fonseca e PEIXOTO, Pedro da Silva. Topography-based local spherical Voronoi grid refinement on classical and moist shallow-water finite-volume models. Geoscientific Model Development, v. 14, n. 11, p. 6919-6944, 2021Tradução . . Disponível em: https://doi.org/10.5194/gmd-14-6919-2021. Acesso em: 30 nov. 2025.
APA
Santos, L. da F., & Peixoto, P. da S. (2021). Topography-based local spherical Voronoi grid refinement on classical and moist shallow-water finite-volume models. Geoscientific Model Development, 14( 11), 6919-6944. doi:10.5194/gmd-14-6919-2021
NLM
Santos L da F, Peixoto P da S. Topography-based local spherical Voronoi grid refinement on classical and moist shallow-water finite-volume models [Internet]. Geoscientific Model Development. 2021 ; 14( 11): 6919-6944.[citado 2025 nov. 30 ] Available from: https://doi.org/10.5194/gmd-14-6919-2021
Vancouver
Santos L da F, Peixoto P da S. Topography-based local spherical Voronoi grid refinement on classical and moist shallow-water finite-volume models [Internet]. Geoscientific Model Development. 2021 ; 14( 11): 6919-6944.[citado 2025 nov. 30 ] Available from: https://doi.org/10.5194/gmd-14-6919-2021
Artigo de periodico
The biophysics, ecology, and biogeochemistry of functionally diverse, vertically and horizontally heterogeneous ecosystems: the Ecosystem Demography model, version 2.2 – Part 2: Model evaluation for tropical South America (2019)
Longo, Marcos; Knox, Ryan G; Levine, Naomi M; Swann, Abigail L. S; Medvigy, David M; Dietze, Michael C; Kim, Yeonjoo; Zhang, Ke; Bonal, Damien; Burban, Benoit; Camargo, Plinio Barbosa de ; Hayek, Matthew N; Saleska, Scott R; Silva, Rodrigo da ; Bras, Rafael L; Wofsy, Steven C; Moorcroft, Paul R
Fonte: Geoscientific Model Development. Unidade: CENA
Assuntos: ÁGUA, BIOFÍSICA, CARBONO, CICLOS BIOGEOQUÍMICOS, ENERGIA, ECOSSISTEMAS TERRESTRES
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
LONGO, Marcos et al. The biophysics, ecology, and biogeochemistry of functionally diverse, vertically and horizontally heterogeneous ecosystems: the Ecosystem Demography model, version 2.2 – Part 2: Model evaluation for tropical South America. Geoscientific Model Development, v. 12, p. 4347-4374, 2019Tradução . . Disponível em: https://doi.org/10.5194/gmd-12-4347-2019. Acesso em: 30 nov. 2025.
APA
Longo, M., Knox, R. G., Levine, N. M., Swann, A. L. S., Medvigy, D. M., Dietze, M. C., et al. (2019). The biophysics, ecology, and biogeochemistry of functionally diverse, vertically and horizontally heterogeneous ecosystems: the Ecosystem Demography model, version 2.2 – Part 2: Model evaluation for tropical South America. Geoscientific Model Development, 12, 4347-4374. doi:10.5194/gmd-12-4347-2019
NLM
Longo M, Knox RG, Levine NM, Swann ALS, Medvigy DM, Dietze MC, Kim Y, Zhang K, Bonal D, Burban B, Camargo PB de, Hayek MN, Saleska SR, Silva R da, Bras RL, Wofsy SC, Moorcroft PR. The biophysics, ecology, and biogeochemistry of functionally diverse, vertically and horizontally heterogeneous ecosystems: the Ecosystem Demography model, version 2.2 – Part 2: Model evaluation for tropical South America [Internet]. Geoscientific Model Development. 2019 ; 12 4347-4374.[citado 2025 nov. 30 ] Available from: https://doi.org/10.5194/gmd-12-4347-2019
Vancouver
Longo M, Knox RG, Levine NM, Swann ALS, Medvigy DM, Dietze MC, Kim Y, Zhang K, Bonal D, Burban B, Camargo PB de, Hayek MN, Saleska SR, Silva R da, Bras RL, Wofsy SC, Moorcroft PR. The biophysics, ecology, and biogeochemistry of functionally diverse, vertically and horizontally heterogeneous ecosystems: the Ecosystem Demography model, version 2.2 – Part 2: Model evaluation for tropical South America [Internet]. Geoscientific Model Development. 2019 ; 12 4347-4374.[citado 2025 nov. 30 ] Available from: https://doi.org/10.5194/gmd-12-4347-2019

Unidades USP

ReP

Filtros

Autores

Autores USP

Assuntos

Agência de fomento

Afiliação dos autores externos não normalizada

País das instituições de afiliação dos autores externos