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Artigo de periodico
Linking urban floods to citizen science and low impact development in poorly gauged basins under climate changes for dynamic resilience evaluation (2022)
Fava, Maria Clara ; Macedo, Marina Batalini de ; Buarque, Ana Carolina Sarmento ; Saraiva, Antonio Mauro ; Delbem, Alexandre Cláudio Botazzo ; Mendiondo, Eduardo Mario
Source: Water. Unidades: EP, ICMC, EESC
Subjects: ENCHENTES URBANAS, SIMULAÇÃO, ANÁLISE DE DADOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
FAVA, Maria Clara et al. Linking urban floods to citizen science and low impact development in poorly gauged basins under climate changes for dynamic resilience evaluation. Water, v. 14, n. 9, p. 1-24, 2022Tradução . . Disponível em: https://doi.org/10.3390/w14091467. Acesso em: 14 nov. 2024.
APA
Fava, M. C., Macedo, M. B. de, Buarque, A. C. S., Saraiva, A. M., Delbem, A. C. B., & Mendiondo, E. M. (2022). Linking urban floods to citizen science and low impact development in poorly gauged basins under climate changes for dynamic resilience evaluation. Water, 14( 9), 1-24. doi:10.3390/w14091467
NLM
Fava MC, Macedo MB de, Buarque ACS, Saraiva AM, Delbem ACB, Mendiondo EM. Linking urban floods to citizen science and low impact development in poorly gauged basins under climate changes for dynamic resilience evaluation [Internet]. Water. 2022 ; 14( 9): 1-24.[citado 2024 nov. 14 ] Available from: https://doi.org/10.3390/w14091467
Vancouver
Fava MC, Macedo MB de, Buarque ACS, Saraiva AM, Delbem ACB, Mendiondo EM. Linking urban floods to citizen science and low impact development in poorly gauged basins under climate changes for dynamic resilience evaluation [Internet]. Water. 2022 ; 14( 9): 1-24.[citado 2024 nov. 14 ] Available from: https://doi.org/10.3390/w14091467
Artigo de periodico
Automatic spatial rainfall estimation on limited coverage areas (2021)
Fava, Maria Clara ; Silva, Roberto Fray da ; Gesualdo, Gabriela Chiquito ; Benso, Marcos Roberto ; Mendiondo, Eduardo Mario ; Saraiva, Antonio Mauro ; Delbem, Alexandre Cláudio Botazzo ; Padovani, Carlos Roberto
Source: Proceedings. Conference titles: IEEE International Workshop on Metrology for Agriculture and Forestry - MetroAgriFor. Unidades: EESC, EP, ICMC, IEA
Subjects: INTERPOLAÇÃO, CHUVA, PANTANAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
FAVA, Maria Clara et al. Automatic spatial rainfall estimation on limited coverage areas. Proceedings, 2021Tradução . . Disponível em: https://doi.org/10.1109/MetroAgriFor52389.2021.9628691. Acesso em: 14 nov. 2024.
APA
Fava, M. C., Silva, R. F. da, Gesualdo, G. C., Benso, M. R., Mendiondo, E. M., Saraiva, A. M., et al. (2021). Automatic spatial rainfall estimation on limited coverage areas. Proceedings. doi:10.1109/MetroAgriFor52389.2021.9628691
NLM
Fava MC, Silva RF da, Gesualdo GC, Benso MR, Mendiondo EM, Saraiva AM, Delbem ACB, Padovani CR. Automatic spatial rainfall estimation on limited coverage areas [Internet]. Proceedings. 2021 ;[citado 2024 nov. 14 ] Available from: https://doi.org/10.1109/MetroAgriFor52389.2021.9628691
Vancouver
Fava MC, Silva RF da, Gesualdo GC, Benso MR, Mendiondo EM, Saraiva AM, Delbem ACB, Padovani CR. Automatic spatial rainfall estimation on limited coverage areas [Internet]. Proceedings. 2021 ;[citado 2024 nov. 14 ] Available from: https://doi.org/10.1109/MetroAgriFor52389.2021.9628691
Trabalho de evento-anais periodico
A theoretical framework for multi-Hazard risk mapping on agricultural areas considering artificial intelligence, IoT, and climate change scenarios (2021)
Silva, Roberto Fray da ; Fava, Maria Clara ; Saraiva, Antonio Mauro ; Mendiondo, Eduardo Mario ; Cugnasca, Carlos Eduardo ; Delbem, Alexandre Cláudio Botazzo
Source: Engineering Proceedings. Conference titles: EFITA International Conference. Unidades: EP, EESC, ICMC
Subjects: INTELIGÊNCIA ARTIFICIAL, MUDANÇA CLIMÁTICA, MONITORAMENTO AMBIENTAL, INTERNET DAS COISAS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SILVA, Roberto Fray da et al. A theoretical framework for multi-Hazard risk mapping on agricultural areas considering artificial intelligence, IoT, and climate change scenarios. Engineering Proceedings. Basel: Escola Politécnica, Universidade de São Paulo. Disponível em: https://doi.org/10.3390/engproc2021009039. Acesso em: 14 nov. 2024. , 2021
APA
Silva, R. F. da, Fava, M. C., Saraiva, A. M., Mendiondo, E. M., Cugnasca, C. E., & Delbem, A. C. B. (2021). A theoretical framework for multi-Hazard risk mapping on agricultural areas considering artificial intelligence, IoT, and climate change scenarios. Engineering Proceedings. Basel: Escola Politécnica, Universidade de São Paulo. doi:10.3390/engproc2021009039
NLM
Silva RF da, Fava MC, Saraiva AM, Mendiondo EM, Cugnasca CE, Delbem ACB. A theoretical framework for multi-Hazard risk mapping on agricultural areas considering artificial intelligence, IoT, and climate change scenarios [Internet]. Engineering Proceedings. 2021 ; 9( 1): 1-4.[citado 2024 nov. 14 ] Available from: https://doi.org/10.3390/engproc2021009039
Vancouver
Silva RF da, Fava MC, Saraiva AM, Mendiondo EM, Cugnasca CE, Delbem ACB. A theoretical framework for multi-Hazard risk mapping on agricultural areas considering artificial intelligence, IoT, and climate change scenarios [Internet]. Engineering Proceedings. 2021 ; 9( 1): 1-4.[citado 2024 nov. 14 ] Available from: https://doi.org/10.3390/engproc2021009039
Artigo de periodico
A data-driven framework for identifying productivity zones and the impact of agricultural droughts in sugarcane using SPI and unsupervised learning (2021)
Silva, Roberto Fray da ; Gesualdo, Gabriela Chiquito ; Benso, Marcos Roberto ; Fava, Maria Clara ; Mendiondo, Eduardo Mario ; Saraiva, Antonio Mauro ; Delbem, Alexandre Cláudio Botazzo
Source: Proceedings. Conference titles: IEEE International Workshop on Metrology for Agriculture and Forestry - MetroAgriFor. Unidades: EESC, EP, ICMC, IEA
Subjects: CANA-DE-AÇÚCAR, ZONA AGRÍCOLA, SECA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SILVA, Roberto Fray da et al. A data-driven framework for identifying productivity zones and the impact of agricultural droughts in sugarcane using SPI and unsupervised learning. Proceedings, 2021Tradução . . Disponível em: https://doi.org/10.1109/MetroAgriFor52389.2021.9628570. Acesso em: 14 nov. 2024.
APA
Silva, R. F. da, Gesualdo, G. C., Benso, M. R., Fava, M. C., Mendiondo, E. M., Saraiva, A. M., & Delbem, A. C. B. (2021). A data-driven framework for identifying productivity zones and the impact of agricultural droughts in sugarcane using SPI and unsupervised learning. Proceedings. doi:10.1109/MetroAgriFor52389.2021.9628570
NLM
Silva RF da, Gesualdo GC, Benso MR, Fava MC, Mendiondo EM, Saraiva AM, Delbem ACB. A data-driven framework for identifying productivity zones and the impact of agricultural droughts in sugarcane using SPI and unsupervised learning [Internet]. Proceedings. 2021 ;[citado 2024 nov. 14 ] Available from: https://doi.org/10.1109/MetroAgriFor52389.2021.9628570
Vancouver
Silva RF da, Gesualdo GC, Benso MR, Fava MC, Mendiondo EM, Saraiva AM, Delbem ACB. A data-driven framework for identifying productivity zones and the impact of agricultural droughts in sugarcane using SPI and unsupervised learning [Internet]. Proceedings. 2021 ;[citado 2024 nov. 14 ] Available from: https://doi.org/10.1109/MetroAgriFor52389.2021.9628570

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