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Artigo de periodico
Geographic object-oriented analysis of UAV multispectral images for tree distribution mapping in mangroves (2025)
Conti, Luis Americo ; Barcellos, Roberto Lima ; Oliveira, Priscila Almeida de ; Nascimento Neto, Francisco Cordeiro ; Lignon, Marília Cunha
Source: Remote Sensing. Unidade: EACH
Assunto: ECOSSISTEMAS COSTEIROS
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CONTI, Luis Americo et al. Geographic object-oriented analysis of UAV multispectral images for tree distribution mapping in mangroves. Remote Sensing, v. 17, p. 01-26, 2025Tradução . . Disponível em: http://dx.doi.org/10.3390/rs17091500. Acesso em: 13 jul. 2025.
APA
Conti, L. A., Barcellos, R. L., Oliveira, P. A. de, Nascimento Neto, F. C., & Lignon, M. C. (2025). Geographic object-oriented analysis of UAV multispectral images for tree distribution mapping in mangroves. Remote Sensing, 17, 01-26. doi:10.3390/rs17091500
NLM
Conti LA, Barcellos RL, Oliveira PA de, Nascimento Neto FC, Lignon MC. Geographic object-oriented analysis of UAV multispectral images for tree distribution mapping in mangroves [Internet]. Remote Sensing. 2025 ; 17 01-26.[citado 2025 jul. 13 ] Available from: http://dx.doi.org/10.3390/rs17091500
Vancouver
Conti LA, Barcellos RL, Oliveira PA de, Nascimento Neto FC, Lignon MC. Geographic object-oriented analysis of UAV multispectral images for tree distribution mapping in mangroves [Internet]. Remote Sensing. 2025 ; 17 01-26.[citado 2025 jul. 13 ] Available from: http://dx.doi.org/10.3390/rs17091500
Artigo de periodico
A step forward in hybrid soil laboratory analysis: merging chemometric corrections, protocols and data-driven methods (2024)
Bartsch, Bruno dos Anjos ; Rosin, Nicolas Augusto ; Santos, Uemeson José dos ; Coblinski, João Augusto; Pelegrino, Marcelo Henrique Procópio ; Rosas, Jorge Tadeu Fim ; Poppiel, Raul Roberto ; Ortiz, Ednilson Batista; Kochinki, Viviane Cristina Vivian; Gallo, Paulo; Dor, Eyal Ben ; Falcioni, Renan ; Nanni, Marcos Rafael ; Gonçalves, João Vitor Ferreira ; Oliveira, Caio Almeida de; Vedana, Nicole Ghinzelli Vedana ; Furlanetto, Renato Herrig; Demattê, José Alexandre Melo
Source: Remote Sensing. Unidade: ESALQ
Subjects: ANÁLISE DO SOLO, ESPECTROSCOPIA, MODELAGEM DE DADOS, QUALIDADE DO SOLO, QUIMIOMETRIA, SENSORIAMENTO REMOTO, TÉCNICAS E PROCEDIMENTOS DE LABORATÓRIO
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BARTSCH, Bruno dos Anjos et al. A step forward in hybrid soil laboratory analysis: merging chemometric corrections, protocols and data-driven methods. Remote Sensing, v. 16, p. 1-17, 2024Tradução . . Disponível em: https://doi.org/10.3390/rs16234543. Acesso em: 13 jul. 2025.
APA
Bartsch, B. dos A., Rosin, N. A., Santos, U. J. dos, Coblinski, J. A., Pelegrino, M. H. P., Rosas, J. T. F., et al. (2024). A step forward in hybrid soil laboratory analysis: merging chemometric corrections, protocols and data-driven methods. Remote Sensing, 16, 1-17. doi:10.3390/rs16234543
NLM
Bartsch B dos A, Rosin NA, Santos UJ dos, Coblinski JA, Pelegrino MHP, Rosas JTF, Poppiel RR, Ortiz EB, Kochinki VCV, Gallo P, Dor EB, Falcioni R, Nanni MR, Gonçalves JVF, Oliveira CA de, Vedana NGV, Furlanetto RH, Demattê JAM. A step forward in hybrid soil laboratory analysis: merging chemometric corrections, protocols and data-driven methods [Internet]. Remote Sensing. 2024 ; 16 1-17.[citado 2025 jul. 13 ] Available from: https://doi.org/10.3390/rs16234543
Vancouver
Bartsch B dos A, Rosin NA, Santos UJ dos, Coblinski JA, Pelegrino MHP, Rosas JTF, Poppiel RR, Ortiz EB, Kochinki VCV, Gallo P, Dor EB, Falcioni R, Nanni MR, Gonçalves JVF, Oliveira CA de, Vedana NGV, Furlanetto RH, Demattê JAM. A step forward in hybrid soil laboratory analysis: merging chemometric corrections, protocols and data-driven methods [Internet]. Remote Sensing. 2024 ; 16 1-17.[citado 2025 jul. 13 ] Available from: https://doi.org/10.3390/rs16234543
Artigo de periodico
Advancing forest degradation and regeneration assessment Through light detection and ranging and hyperspectral imaging integration (2024)
Almeida, Catherine Torres de ; Galvão, Lênio Soares ; Ometto, Jean Pierre H. B ; Jacon, Aline Daniele ; Pereira, Francisca Rocha de Souza ; Sato, Luciane Yumie; Silva-Junior, Celso Henrique Leite ; Brancalion, Pedro Henrique Santin ; Aragão, Luiz Eduardo Oliveira e Cruz de
Source: Remote Sensing. Unidade: ESALQ
Subjects: APRENDIZADO COMPUTACIONAL, ECOLOGIA DA RESTAURAÇÃO, ESPECTROSCOPIA, FLORESTAS TROPICAIS, LUZ, TECNOLOGIA LIDAR, SENSORIAMENTO REMOTO
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ALMEIDA, Catherine Torres de et al. Advancing forest degradation and regeneration assessment Through light detection and ranging and hyperspectral imaging integration. Remote Sensing, v. 16, p. 1-26, 2024Tradução . . Disponível em: https://doi.org/10.3390/rs16213935. Acesso em: 13 jul. 2025.
APA
Almeida, C. T. de, Galvão, L. S., Ometto, J. P. H. B., Jacon, A. D., Pereira, F. R. de S., Sato, L. Y., et al. (2024). Advancing forest degradation and regeneration assessment Through light detection and ranging and hyperspectral imaging integration. Remote Sensing, 16, 1-26. doi:10.3390/rs16213935
NLM
Almeida CT de, Galvão LS, Ometto JPHB, Jacon AD, Pereira FR de S, Sato LY, Silva-Junior CHL, Brancalion PHS, Aragão LEO e C de. Advancing forest degradation and regeneration assessment Through light detection and ranging and hyperspectral imaging integration [Internet]. Remote Sensing. 2024 ; 16 1-26.[citado 2025 jul. 13 ] Available from: https://doi.org/10.3390/rs16213935
Vancouver
Almeida CT de, Galvão LS, Ometto JPHB, Jacon AD, Pereira FR de S, Sato LY, Silva-Junior CHL, Brancalion PHS, Aragão LEO e C de. Advancing forest degradation and regeneration assessment Through light detection and ranging and hyperspectral imaging integration [Internet]. Remote Sensing. 2024 ; 16 1-26.[citado 2025 jul. 13 ] Available from: https://doi.org/10.3390/rs16213935
Artigo de periodico
Estimation of biochemical compounds in Tradescantia leaves using VIS-NIR-SWIR hyperspectral and chlorophyll a fluorescence sensors (2024)
Falcioni, Renan ; Oliveira, Roney Berti de ; Chicati, Marcelo Luiz ; Antunes, Werner Camargos ; Demattê, José Alexandre Melo ; Nanni, Marcos Rafael
Source: Remote Sensing. Unidade: ESALQ
Subjects: BIOQUÍMICA VEGETAL, CLOROFILA, COMMELINALES, COMPONENTES PRINCIPAIS, ESPECTROSCOPIA, FOLHAS (PLANTAS), FLUORESCÊNCIA, MÍNIMOS QUADRADOS, SENSORIAMENTO REMOTO
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FALCIONI, Renan et al. Estimation of biochemical compounds in Tradescantia leaves using VIS-NIR-SWIR hyperspectral and chlorophyll a fluorescence sensors. Remote Sensing, v. 16, p. 1-25, 2024Tradução . . Disponível em: https://doi.org/10.3390/rs16111910. Acesso em: 13 jul. 2025.
APA
Falcioni, R., Oliveira, R. B. de, Chicati, M. L., Antunes, W. C., Demattê, J. A. M., & Nanni, M. R. (2024). Estimation of biochemical compounds in Tradescantia leaves using VIS-NIR-SWIR hyperspectral and chlorophyll a fluorescence sensors. Remote Sensing, 16, 1-25. doi:10.3390/rs16111910
NLM
Falcioni R, Oliveira RB de, Chicati ML, Antunes WC, Demattê JAM, Nanni MR. Estimation of biochemical compounds in Tradescantia leaves using VIS-NIR-SWIR hyperspectral and chlorophyll a fluorescence sensors [Internet]. Remote Sensing. 2024 ; 16 1-25.[citado 2025 jul. 13 ] Available from: https://doi.org/10.3390/rs16111910
Vancouver
Falcioni R, Oliveira RB de, Chicati ML, Antunes WC, Demattê JAM, Nanni MR. Estimation of biochemical compounds in Tradescantia leaves using VIS-NIR-SWIR hyperspectral and chlorophyll a fluorescence sensors [Internet]. Remote Sensing. 2024 ; 16 1-25.[citado 2025 jul. 13 ] Available from: https://doi.org/10.3390/rs16111910
Artigo de periodico
Sugarcane yield estimation using satellite remote sensing data in empirical or mechanistic modeling: a systematic review (2024)
Silva, Nildson Rodrigues de França e; Chaves, Michel Eustáquio Dantas ; Luciano, Ana Cláudia dos Santos ; Sanches, Ieda Del’Arco ; Almeida, Cláudia Maria de; Adami, Marcos
Source: Remote Sensing. Unidade: ESALQ
Subjects: CANA-DE-AÇÚCAR, IMAGEAMENTO DE SATÉLITE, MODELAGEM DE DADOS, REVISÃO SISTEMÁTICA, SENSORIAMENTO REMOTO
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SILVA, Nildson Rodrigues de França e et al. Sugarcane yield estimation using satellite remote sensing data in empirical or mechanistic modeling: a systematic review. Remote Sensing, v. 16, p. 1-26, 2024Tradução . . Disponível em: https://doi.org/10.3390/rs16050863. Acesso em: 13 jul. 2025.
APA
Silva, N. R. de F. e, Chaves, M. E. D., Luciano, A. C. dos S., Sanches, I. D. ’A., Almeida, C. M. de, & Adami, M. (2024). Sugarcane yield estimation using satellite remote sensing data in empirical or mechanistic modeling: a systematic review. Remote Sensing, 16, 1-26. doi:10.3390/rs16050863
NLM
Silva NR de F e, Chaves MED, Luciano AC dos S, Sanches ID’A, Almeida CM de, Adami M. Sugarcane yield estimation using satellite remote sensing data in empirical or mechanistic modeling: a systematic review [Internet]. Remote Sensing. 2024 ; 16 1-26.[citado 2025 jul. 13 ] Available from: https://doi.org/10.3390/rs16050863
Vancouver
Silva NR de F e, Chaves MED, Luciano AC dos S, Sanches ID’A, Almeida CM de, Adami M. Sugarcane yield estimation using satellite remote sensing data in empirical or mechanistic modeling: a systematic review [Internet]. Remote Sensing. 2024 ; 16 1-26.[citado 2025 jul. 13 ] Available from: https://doi.org/10.3390/rs16050863
Artigo de periodico
Generalization of VIS-NIR-SWIR spectral models for nitrogen prediction in sugarcane leaves (2024)
Silva, Carlos Augusto Alves Cardoso ; Rizzo, Rodnei ; Silva, Marcelo Andrade da ; Caron, Matheus Luís ; Fiorio, Peterson Ricardo
Source: Remote Sensing. Unidade: ESALQ
Subjects: CANA-DE-AÇÚCAR, NITROGÊNIO, MAPEAMENTO DO SOLO, SENSORIAMENTO REMOTO, AGRICULTURA DE PRECISÃO
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SILVA, Carlos Augusto Alves Cardoso et al. Generalization of VIS-NIR-SWIR spectral models for nitrogen prediction in sugarcane leaves. Remote Sensing, v. 16, p. 1-18, 2024Tradução . . Disponível em: https://doi.org/10.3390/rs16224250. Acesso em: 13 jul. 2025.
APA
Silva, C. A. A. C., Rizzo, R., Silva, M. A. da, Caron, M. L., & Fiorio, P. R. (2024). Generalization of VIS-NIR-SWIR spectral models for nitrogen prediction in sugarcane leaves. Remote Sensing, 16, 1-18. doi:10.3390/rs16224250
NLM
Silva CAAC, Rizzo R, Silva MA da, Caron ML, Fiorio PR. Generalization of VIS-NIR-SWIR spectral models for nitrogen prediction in sugarcane leaves [Internet]. Remote Sensing. 2024 ; 16 1-18.[citado 2025 jul. 13 ] Available from: https://doi.org/10.3390/rs16224250
Vancouver
Silva CAAC, Rizzo R, Silva MA da, Caron ML, Fiorio PR. Generalization of VIS-NIR-SWIR spectral models for nitrogen prediction in sugarcane leaves [Internet]. Remote Sensing. 2024 ; 16 1-18.[citado 2025 jul. 13 ] Available from: https://doi.org/10.3390/rs16224250
Artigo de periodico
Integrated use of synthetic aperture radar and optical data in mapping native vegetation: a study in a transitional brazilian Cerrado–Atlantic Forest interface (2024)
Santos, Allita Rezende dos ; Barbosa, Mariana Abibi Guimarâes Araujo; Anjinho, Phelipe da Silva; Parizotto, Denise; Mauad, Frederico Fábio
Source: Remote Sensing. Unidade: EESC
Subjects: VEGETAÇÃO, BIOMA, RADAR, ENGENHARIA HIDRÁULICA
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ABNT
SANTOS, Allita Rezende dos et al. Integrated use of synthetic aperture radar and optical data in mapping native vegetation: a study in a transitional brazilian Cerrado–Atlantic Forest interface. Remote Sensing, v. 16, n. 14, p. 1-15, 2024Tradução . . Disponível em: https://dx.doi.org/10.3390/rs16142559. Acesso em: 13 jul. 2025.
APA
Santos, A. R. dos, Barbosa, M. A. G. A., Anjinho, P. da S., Parizotto, D., & Mauad, F. F. (2024). Integrated use of synthetic aperture radar and optical data in mapping native vegetation: a study in a transitional brazilian Cerrado–Atlantic Forest interface. Remote Sensing, 16( 14), 1-15. doi:10.3390/rs16142559
NLM
Santos AR dos, Barbosa MAGA, Anjinho P da S, Parizotto D, Mauad FF. Integrated use of synthetic aperture radar and optical data in mapping native vegetation: a study in a transitional brazilian Cerrado–Atlantic Forest interface [Internet]. Remote Sensing. 2024 ; 16( 14): 1-15.[citado 2025 jul. 13 ] Available from: https://dx.doi.org/10.3390/rs16142559
Vancouver
Santos AR dos, Barbosa MAGA, Anjinho P da S, Parizotto D, Mauad FF. Integrated use of synthetic aperture radar and optical data in mapping native vegetation: a study in a transitional brazilian Cerrado–Atlantic Forest interface [Internet]. Remote Sensing. 2024 ; 16( 14): 1-15.[citado 2025 jul. 13 ] Available from: https://dx.doi.org/10.3390/rs16142559
Artigo de periodico
The use of Vis-NIR-SWIR spectroscopy and X-ray fluorescence in the development of predictive models: a step forward in the quantification of nitrogen, total organic carbon and humic fractions in ferralsols (2024)
Lima, Bruna Coelho de ; Demattê, José Alexandre Melo ; Santos, Carlos H. dos; Tiritan, Carlos S; Poppiel, Raul Roberto ; Nanni, Marcos R. ; Falcioni, Renan ; Oliveira, Caio A. de; Vedana, Nicole G; Zimmermann, Guilherme; Reis, Amanda S
Source: Remote Sensing. Unidade: ESALQ
Subjects: APRENDIZADO COMPUTACIONAL, CARBONO, ESPECTROSCOPIA, FLUORESCÊNCIA, RAIOS X, MATÉRIA ORGÂNICA DO SOLO, NITROGÊNIO, SOLO ARENOSO
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ABNT
LIMA, Bruna Coelho de et al. The use of Vis-NIR-SWIR spectroscopy and X-ray fluorescence in the development of predictive models: a step forward in the quantification of nitrogen, total organic carbon and humic fractions in ferralsols. Remote Sensing, v. 16, p. 1-19, 2024Tradução . . Disponível em: https://doi.org/10.3390/rs16163009. Acesso em: 13 jul. 2025.
APA
Lima, B. C. de, Demattê, J. A. M., Santos, C. H. dos, Tiritan, C. S., Poppiel, R. R., Nanni, M. R., et al. (2024). The use of Vis-NIR-SWIR spectroscopy and X-ray fluorescence in the development of predictive models: a step forward in the quantification of nitrogen, total organic carbon and humic fractions in ferralsols. Remote Sensing, 16, 1-19. doi:10.3390/rs16163009
NLM
Lima BC de, Demattê JAM, Santos CH dos, Tiritan CS, Poppiel RR, Nanni MR, Falcioni R, Oliveira CA de, Vedana NG, Zimmermann G, Reis AS. The use of Vis-NIR-SWIR spectroscopy and X-ray fluorescence in the development of predictive models: a step forward in the quantification of nitrogen, total organic carbon and humic fractions in ferralsols [Internet]. Remote Sensing. 2024 ; 16 1-19.[citado 2025 jul. 13 ] Available from: https://doi.org/10.3390/rs16163009
Vancouver
Lima BC de, Demattê JAM, Santos CH dos, Tiritan CS, Poppiel RR, Nanni MR, Falcioni R, Oliveira CA de, Vedana NG, Zimmermann G, Reis AS. The use of Vis-NIR-SWIR spectroscopy and X-ray fluorescence in the development of predictive models: a step forward in the quantification of nitrogen, total organic carbon and humic fractions in ferralsols [Internet]. Remote Sensing. 2024 ; 16 1-19.[citado 2025 jul. 13 ] Available from: https://doi.org/10.3390/rs16163009
Artigo de periodico
Assessment of Atmospheric Correction Algorithms for Sentinel-3 OLCI in the Amazon River Continuum (2024)
Valério, Aline de Matos ; Kampel, Milton ; Vantrepotte, Vincent; Ballester, Maria Victoria Ramos ; Richey, Jeffrey Edward
Source: Remote Sensing. Unidade: CENA
Subjects: RIOS, ÁGUA PLUVIAL, COR, SENSORIAMENTO REMOTO
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VALÉRIO, Aline de Matos et al. Assessment of Atmospheric Correction Algorithms for Sentinel-3 OLCI in the Amazon River Continuum. Remote Sensing, v. 16, p. 1-23, 2024Tradução . . Disponível em: https://doi.org/10.3390/rs16142663. Acesso em: 13 jul. 2025.
APA
Valério, A. de M., Kampel, M., Vantrepotte, V., Ballester, M. V. R., & Richey, J. E. (2024). Assessment of Atmospheric Correction Algorithms for Sentinel-3 OLCI in the Amazon River Continuum. Remote Sensing, 16, 1-23. doi:10.3390/rs16142663
NLM
Valério A de M, Kampel M, Vantrepotte V, Ballester MVR, Richey JE. Assessment of Atmospheric Correction Algorithms for Sentinel-3 OLCI in the Amazon River Continuum [Internet]. Remote Sensing. 2024 ; 16 1-23.[citado 2025 jul. 13 ] Available from: https://doi.org/10.3390/rs16142663
Vancouver
Valério A de M, Kampel M, Vantrepotte V, Ballester MVR, Richey JE. Assessment of Atmospheric Correction Algorithms for Sentinel-3 OLCI in the Amazon River Continuum [Internet]. Remote Sensing. 2024 ; 16 1-23.[citado 2025 jul. 13 ] Available from: https://doi.org/10.3390/rs16142663
Artigo de periodico
Spatio-temporal generalization of VIS-NIR-SWIR spectral models for nitrogen prediction in sugarcane leaves (2024)
Silva, Carlos Augusto Alves Cardoso ; Rizzo, Rodnei ; Silva, Marcelo Andrade da ; Caron, Matheus Luís ; Fiorio, Peterson Ricardo
Source: Remote Sensing. Unidade: ESALQ
Subjects: AGRICULTURA DE PRECISÃO, CANA-DE-AÇÚCAR, DIAGNOSE FOLIAR, ESPECTROSCOPIA, FERTILIZANTES NITROGENADOS, NITROGÊNIO, SENSORIAMENTO REMOTO
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ABNT
SILVA, Carlos Augusto Alves Cardoso et al. Spatio-temporal generalization of VIS-NIR-SWIR spectral models for nitrogen prediction in sugarcane leaves. Remote Sensing, v. 16, p. 1-18, 2024Tradução . . Disponível em: https://doi.org/10.3390/rs16224250. Acesso em: 13 jul. 2025.
APA
Silva, C. A. A. C., Rizzo, R., Silva, M. A. da, Caron, M. L., & Fiorio, P. R. (2024). Spatio-temporal generalization of VIS-NIR-SWIR spectral models for nitrogen prediction in sugarcane leaves. Remote Sensing, 16, 1-18. doi:10.3390/rs16224250
NLM
Silva CAAC, Rizzo R, Silva MA da, Caron ML, Fiorio PR. Spatio-temporal generalization of VIS-NIR-SWIR spectral models for nitrogen prediction in sugarcane leaves [Internet]. Remote Sensing. 2024 ; 16 1-18.[citado 2025 jul. 13 ] Available from: https://doi.org/10.3390/rs16224250
Vancouver
Silva CAAC, Rizzo R, Silva MA da, Caron ML, Fiorio PR. Spatio-temporal generalization of VIS-NIR-SWIR spectral models for nitrogen prediction in sugarcane leaves [Internet]. Remote Sensing. 2024 ; 16 1-18.[citado 2025 jul. 13 ] Available from: https://doi.org/10.3390/rs16224250
Artigo de periodico
Towards Unified Online-Coupled Aerosol Parameterization for the Brazilian Global Atmospheric Model (BAM): Aerosol-Cloud Microphysical-Radiation Interactions (2023)
Pendharkar, Jayant ; Nobre, Paulo ; Herdies, Dirceu Luis ; Figueroa, Silvio Nilo ; Vara-Vela, Angel ; Krishna, Ravuri Phani Murali ; Schuch, Daniel ; Kubota, Paulo Yoshio; Alvim, Débora Souza ; Vendrasco, Éder Paulo ; Gomes, Helber Barros
Source: Remote Sensing. Unidade: EEL
Assunto: AEROSSOL
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ABNT
PENDHARKAR, Jayant et al. Towards Unified Online-Coupled Aerosol Parameterization for the Brazilian Global Atmospheric Model (BAM): Aerosol-Cloud Microphysical-Radiation Interactions. Remote Sensing, v. 15, n. 1, p. 1-25, 2023Tradução . . Disponível em: https://doi.org/10.3390/rs15010278. Acesso em: 13 jul. 2025.
APA
Pendharkar, J., Nobre, P., Herdies, D. L., Figueroa, S. N., Vara-Vela, A., Krishna, R. P. M., et al. (2023). Towards Unified Online-Coupled Aerosol Parameterization for the Brazilian Global Atmospheric Model (BAM): Aerosol-Cloud Microphysical-Radiation Interactions. Remote Sensing, 15( 1), 1-25. doi:10.3390/rs15010278
NLM
Pendharkar J, Nobre P, Herdies DL, Figueroa SN, Vara-Vela A, Krishna RPM, Schuch D, Kubota PY, Alvim DS, Vendrasco ÉP, Gomes HB. Towards Unified Online-Coupled Aerosol Parameterization for the Brazilian Global Atmospheric Model (BAM): Aerosol-Cloud Microphysical-Radiation Interactions [Internet]. Remote Sensing. 2023 ; 15( 1): 1-25.[citado 2025 jul. 13 ] Available from: https://doi.org/10.3390/rs15010278
Vancouver
Pendharkar J, Nobre P, Herdies DL, Figueroa SN, Vara-Vela A, Krishna RPM, Schuch D, Kubota PY, Alvim DS, Vendrasco ÉP, Gomes HB. Towards Unified Online-Coupled Aerosol Parameterization for the Brazilian Global Atmospheric Model (BAM): Aerosol-Cloud Microphysical-Radiation Interactions [Internet]. Remote Sensing. 2023 ; 15( 1): 1-25.[citado 2025 jul. 13 ] Available from: https://doi.org/10.3390/rs15010278
Artigo de periodico
Towards Unified Online-Coupled Aerosol Parameterization for the Brazilian Global Atmospheric Model (BAM): Aerosol-Cloud Microphysical-Radiation Interactions (2023)
Pendharkar, Jayant ; Nobre, Paulo ; Herdies, Dirceu Luis ; Figueroa, Silvio Nilo ; Vara-Vela, Angel ; Krishna, Ravuri Phani Murali ; Schuch, Daniel ; Kubota, Paulo Yoshio; Alvim, Débora Souza ; Vendrasco, Éder Paulo ; Gomes, Helber Barros
Source: Remote Sensing. Unidade: EEL
Assunto: AEROSSOL
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ABNT
PENDHARKAR, Jayant et al. Towards Unified Online-Coupled Aerosol Parameterization for the Brazilian Global Atmospheric Model (BAM): Aerosol-Cloud Microphysical-Radiation Interactions. Remote Sensing, v. 15, n. 1, p. 1-25, 2023Tradução . . Disponível em: https://doi.org/10.3390/rs15010278. Acesso em: 13 jul. 2025.
APA
Pendharkar, J., Nobre, P., Herdies, D. L., Figueroa, S. N., Vara-Vela, A., Krishna, R. P. M., et al. (2023). Towards Unified Online-Coupled Aerosol Parameterization for the Brazilian Global Atmospheric Model (BAM): Aerosol-Cloud Microphysical-Radiation Interactions. Remote Sensing, 15( 1), 1-25. doi:10.3390/rs15010278
NLM
Pendharkar J, Nobre P, Herdies DL, Figueroa SN, Vara-Vela A, Krishna RPM, Schuch D, Kubota PY, Alvim DS, Vendrasco ÉP, Gomes HB. Towards Unified Online-Coupled Aerosol Parameterization for the Brazilian Global Atmospheric Model (BAM): Aerosol-Cloud Microphysical-Radiation Interactions [Internet]. Remote Sensing. 2023 ;15( 1): 1-25.[citado 2025 jul. 13 ] Available from: https://doi.org/10.3390/rs15010278
Vancouver
Pendharkar J, Nobre P, Herdies DL, Figueroa SN, Vara-Vela A, Krishna RPM, Schuch D, Kubota PY, Alvim DS, Vendrasco ÉP, Gomes HB. Towards Unified Online-Coupled Aerosol Parameterization for the Brazilian Global Atmospheric Model (BAM): Aerosol-Cloud Microphysical-Radiation Interactions [Internet]. Remote Sensing. 2023 ;15( 1): 1-25.[citado 2025 jul. 13 ] Available from: https://doi.org/10.3390/rs15010278
Artigo de periodico
Estimating black oat biomass using digital surface models and a vegetation index derived from RGB-based aerial images (2023)
Trevisan, Lucas Renato ; Brichi, Lisiane ; Gomes, Tamara Maria ; Rossi, Fabricio
Source: Remote Sensing. Unidades: FZEA, ESALQ
Subjects: AEROFOTOGRAMETRIA, AERONAVES NÃO TRIPULADAS, AVEIA PRETA, BIOMASSA, CRESCIMENTO VEGETAL, SENSORIAMENTO REMOTO, VISÃO COMPUTACIONAL
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ABNT
TREVISAN, Lucas Renato et al. Estimating black oat biomass using digital surface models and a vegetation index derived from RGB-based aerial images. Remote Sensing, v. 15, p. 1-19, 2023Tradução . . Disponível em: https://doi.org/10.3390/rs15051363. Acesso em: 13 jul. 2025.
APA
Trevisan, L. R., Brichi, L., Gomes, T. M., & Rossi, F. (2023). Estimating black oat biomass using digital surface models and a vegetation index derived from RGB-based aerial images. Remote Sensing, 15, 1-19. doi:10.3390/rs15051363
NLM
Trevisan LR, Brichi L, Gomes TM, Rossi F. Estimating black oat biomass using digital surface models and a vegetation index derived from RGB-based aerial images [Internet]. Remote Sensing. 2023 ; 15 1-19.[citado 2025 jul. 13 ] Available from: https://doi.org/10.3390/rs15051363
Vancouver
Trevisan LR, Brichi L, Gomes TM, Rossi F. Estimating black oat biomass using digital surface models and a vegetation index derived from RGB-based aerial images [Internet]. Remote Sensing. 2023 ; 15 1-19.[citado 2025 jul. 13 ] Available from: https://doi.org/10.3390/rs15051363
Artigo de periodico
COVID-19 Pandemic: Impacts on Air Quality during Partial Lockdown in the Metropolitan Area of São Paulo (2023)
Alvim, Débora Souza ; Figueroa, Silvio Nilo ; Herdies, Dirceu Luis ; Corrêa, Sérgio Machado ; Basso, Luana Santamaria; Khalid, Bushra; Silva, Gabriella Fernandes Prazeres; Oyerinde, Gabriel ; Carvalho, Nicolli Albuquerque de; Coelho, Simone Marilene Sievert da Costa
Source: Remote Sensing. Unidade: EEL
Subjects: POLUIÇÃO ATMOSFÉRICA, PANDEMIAS, COVID-19, SÃO PAULO (SP)
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
ALVIM, Débora Souza et al. COVID-19 Pandemic: Impacts on Air Quality during Partial Lockdown in the Metropolitan Area of São Paulo. Remote Sensing, v. 15, n. 5, p. 1-30, 2023Tradução . . Disponível em: https://doi.org/10.3390/rs15051262. Acesso em: 13 jul. 2025.
APA
Alvim, D. S., Figueroa, S. N., Herdies, D. L., Corrêa, S. M., Basso, L. S., Khalid, B., et al. (2023). COVID-19 Pandemic: Impacts on Air Quality during Partial Lockdown in the Metropolitan Area of São Paulo. Remote Sensing, 15( 5), 1-30. doi:10.3390/rs15051262
NLM
Alvim DS, Figueroa SN, Herdies DL, Corrêa SM, Basso LS, Khalid B, Silva GFP, Oyerinde G, Carvalho NA de, Coelho SMS da C. COVID-19 Pandemic: Impacts on Air Quality during Partial Lockdown in the Metropolitan Area of São Paulo [Internet]. Remote Sensing. 2023 ;15( 5): 1-30.[citado 2025 jul. 13 ] Available from: https://doi.org/10.3390/rs15051262
Vancouver
Alvim DS, Figueroa SN, Herdies DL, Corrêa SM, Basso LS, Khalid B, Silva GFP, Oyerinde G, Carvalho NA de, Coelho SMS da C. COVID-19 Pandemic: Impacts on Air Quality during Partial Lockdown in the Metropolitan Area of São Paulo [Internet]. Remote Sensing. 2023 ;15( 5): 1-30.[citado 2025 jul. 13 ] Available from: https://doi.org/10.3390/rs15051262
Artigo de periodico
Crown-level structure and fuel load characterization from airborne and terrestrial laser scanning in a longleaf pine (Pinus palustris Mill.) forest ecosystem (2023)
Rocha, Kleydson Diego; Silva, Carlos Alberto ; Cosenza, Diogo N ; Mohan, Midhun ; Klauberg, Carine ; Schlickmann, Monique Bohora ; Xia, Jinyi; Leite, Rodrigo V; Almeida, Danilo Roberti Alves de ; Atkins, Jeff W; Cardil, Adrian ; Rowell, Eric; Parsons, Russ ; Sánchez-López, Nuria ; Prichard, Susan J; Hudak, Andrew T
Source: Remote Sensing. Unidade: ESALQ
Subjects: APRENDIZADO COMPUTACIONAL, DOSSEL (BOTÂNICA), ECOSSISTEMAS FLORESTAIS, PINHEIRO, SENSORIAMENTO REMOTO, TECNOLOGIA LIDAR
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
ROCHA, Kleydson Diego et al. Crown-level structure and fuel load characterization from airborne and terrestrial laser scanning in a longleaf pine (Pinus palustris Mill.) forest ecosystem. Remote Sensing, v. 15, p. 1-21, 2023Tradução . . Disponível em: https://doi.org/10.3390/rs15041002. Acesso em: 13 jul. 2025.
APA
Rocha, K. D., Silva, C. A., Cosenza, D. N., Mohan, M., Klauberg, C., Schlickmann, M. B., et al. (2023). Crown-level structure and fuel load characterization from airborne and terrestrial laser scanning in a longleaf pine (Pinus palustris Mill.) forest ecosystem. Remote Sensing, 15, 1-21. doi:10.3390/rs15041002
NLM
Rocha KD, Silva CA, Cosenza DN, Mohan M, Klauberg C, Schlickmann MB, Xia J, Leite RV, Almeida DRA de, Atkins JW, Cardil A, Rowell E, Parsons R, Sánchez-López N, Prichard SJ, Hudak AT. Crown-level structure and fuel load characterization from airborne and terrestrial laser scanning in a longleaf pine (Pinus palustris Mill.) forest ecosystem [Internet]. Remote Sensing. 2023 ; 15 1-21.[citado 2025 jul. 13 ] Available from: https://doi.org/10.3390/rs15041002
Vancouver
Rocha KD, Silva CA, Cosenza DN, Mohan M, Klauberg C, Schlickmann MB, Xia J, Leite RV, Almeida DRA de, Atkins JW, Cardil A, Rowell E, Parsons R, Sánchez-López N, Prichard SJ, Hudak AT. Crown-level structure and fuel load characterization from airborne and terrestrial laser scanning in a longleaf pine (Pinus palustris Mill.) forest ecosystem [Internet]. Remote Sensing. 2023 ; 15 1-21.[citado 2025 jul. 13 ] Available from: https://doi.org/10.3390/rs15041002
Artigo de periodico
Rainfall-Induced Shallow Landslide Recognition and Transferability Using Object-Based Image Analysis in Brazil (2023)
Dias, Helen Cristina ; Holbling,Daniel ; Grohmann, Carlos Henrique
Source: Remote Sensing. Unidade: IEE
Assunto: SENSORIAMENTO REMOTO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
DIAS, Helen Cristina e HOLBLING, Daniel e GROHMANN, Carlos Henrique. Rainfall-Induced Shallow Landslide Recognition and Transferability Using Object-Based Image Analysis in Brazil. Remote Sensing, v. 15, n. 21, p. art.5137/1-16, 2023Tradução . . Disponível em: https://doi.org/10.3390/rs15215137. Acesso em: 13 jul. 2025.
APA
Dias, H. C., Holbling, D., & Grohmann, C. H. (2023). Rainfall-Induced Shallow Landslide Recognition and Transferability Using Object-Based Image Analysis in Brazil. Remote Sensing, 15(21), art.5137/1-16. Recuperado de https://doi.org/10.3390/rs15215137
NLM
Dias HC, Holbling D, Grohmann CH. Rainfall-Induced Shallow Landslide Recognition and Transferability Using Object-Based Image Analysis in Brazil [Internet]. Remote Sensing. 2023 ; 15(21):art.5137/1-16.[citado 2025 jul. 13 ] Available from: https://doi.org/10.3390/rs15215137
Vancouver
Dias HC, Holbling D, Grohmann CH. Rainfall-Induced Shallow Landslide Recognition and Transferability Using Object-Based Image Analysis in Brazil [Internet]. Remote Sensing. 2023 ; 15(21):art.5137/1-16.[citado 2025 jul. 13 ] Available from: https://doi.org/10.3390/rs15215137
Artigo de periodico
Soil erosion satellite-based estimation in cropland for soil conservation (2023)
Gallo, Bruna Cristina ; Magalhães, Paulo Sérgio Graziano ; Demattê, José Alexandre Melo ; Cervi, Walter Rossi; Carvalho, João Luís Nunes ; Barbosa, Leandro Carneiro ; Bellinaso, Henrique ; Mello, Danilo César de ; Veloso, Gustavo Vieira ; Alves, Marcelo Rodrigo; Fernandes-Filho, Elpídio Inácio ; Francelino, Márcio Rocha ; Schaefer, Carlos Ernesto Gonçalves Reynaud
Source: Remote Sensing. Unidade: ESALQ
Subjects: BIOENERGIA, CONSERVAÇÃO DO SOLO, DEGRADAÇÃO DO SOLO, EROSÃO, IMAGEAMENTO DE SATÉLITE, RESÍDUOS AGRÍCOLAS, SENSORIAMENTO REMOTO, USO DO SOLO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
GALLO, Bruna Cristina et al. Soil erosion satellite-based estimation in cropland for soil conservation. Remote Sensing, v. 15, p. 11-24, 2023Tradução . . Disponível em: https://doi.org/10.3390/rs15010020. Acesso em: 13 jul. 2025.
APA
Gallo, B. C., Magalhães, P. S. G., Demattê, J. A. M., Cervi, W. R., Carvalho, J. L. N., Barbosa, L. C., et al. (2023). Soil erosion satellite-based estimation in cropland for soil conservation. Remote Sensing, 15, 11-24. doi:10.3390/rs15010020
NLM
Gallo BC, Magalhães PSG, Demattê JAM, Cervi WR, Carvalho JLN, Barbosa LC, Bellinaso H, Mello DC de, Veloso GV, Alves MR, Fernandes-Filho EI, Francelino MR, Schaefer CEGR. Soil erosion satellite-based estimation in cropland for soil conservation [Internet]. Remote Sensing. 2023 ; 15 11-24.[citado 2025 jul. 13 ] Available from: https://doi.org/10.3390/rs15010020
Vancouver
Gallo BC, Magalhães PSG, Demattê JAM, Cervi WR, Carvalho JLN, Barbosa LC, Bellinaso H, Mello DC de, Veloso GV, Alves MR, Fernandes-Filho EI, Francelino MR, Schaefer CEGR. Soil erosion satellite-based estimation in cropland for soil conservation [Internet]. Remote Sensing. 2023 ; 15 11-24.[citado 2025 jul. 13 ] Available from: https://doi.org/10.3390/rs15010020
Artigo de periodico
Assessment of combined reflectance, transmittance, and absorbance hyperspectral sensors for prediction of chlorophyll a fluorescence parameters (2023)
Falcioni, Renan ; Antunes, Werner Camargos ; Oliveira, Roney Berti de ; Chicati, Marcelo Luiz ; Demattê, José Alexandre Melo ; Nanni, Marcos Rafael
Source: Remote Sensing. Unidade: ESALQ
Subjects: ANÁLISE MULTIVARIADA, CLOROFILA, FLUORESCÊNCIA, ESPECTROSCOPIA, FOLHAS (PLANTAS), GERÂNIO, HIBISCO, MODELOS MATEMÁTICOS, SENSORIAMENTO REMOTO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
FALCIONI, Renan et al. Assessment of combined reflectance, transmittance, and absorbance hyperspectral sensors for prediction of chlorophyll a fluorescence parameters. Remote Sensing, v. 15, p. 1-23, 2023Tradução . . Disponível em: https://doi.org/10.3390/rs15205067. Acesso em: 13 jul. 2025.
APA
Falcioni, R., Antunes, W. C., Oliveira, R. B. de, Chicati, M. L., Demattê, J. A. M., & Nanni, M. R. (2023). Assessment of combined reflectance, transmittance, and absorbance hyperspectral sensors for prediction of chlorophyll a fluorescence parameters. Remote Sensing, 15, 1-23. doi:10.3390/rs15205067
NLM
Falcioni R, Antunes WC, Oliveira RB de, Chicati ML, Demattê JAM, Nanni MR. Assessment of combined reflectance, transmittance, and absorbance hyperspectral sensors for prediction of chlorophyll a fluorescence parameters [Internet]. Remote Sensing. 2023 ; 15 1-23.[citado 2025 jul. 13 ] Available from: https://doi.org/10.3390/rs15205067
Vancouver
Falcioni R, Antunes WC, Oliveira RB de, Chicati ML, Demattê JAM, Nanni MR. Assessment of combined reflectance, transmittance, and absorbance hyperspectral sensors for prediction of chlorophyll a fluorescence parameters [Internet]. Remote Sensing. 2023 ; 15 1-23.[citado 2025 jul. 13 ] Available from: https://doi.org/10.3390/rs15205067
Artigo de periodico
Monitoring geological risk areas in the city of São Paulo based on multi-temporal high-resolution 3D models (2023)
Sousa, Amanda Mendes de ; Viana, Camila Duelis ; Garcia, Guilherme Pereira Bento ; Grohmann, Carlos Henrique
Source: Remote Sensing. Unidades: IGC, IEE
Subjects: GEOLOGIA AMBIENTAL, MONITORAMENTO AMBIENTAL, DESLIZAMENTO DE TERRA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SOUSA, Amanda Mendes de et al. Monitoring geological risk areas in the city of São Paulo based on multi-temporal high-resolution 3D models. Remote Sensing, v. 15, n. 12, p. 3028-, 2023Tradução . . Disponível em: https://doi.org/10.3390/rs15123028. Acesso em: 13 jul. 2025.
APA
Sousa, A. M. de, Viana, C. D., Garcia, G. P. B., & Grohmann, C. H. (2023). Monitoring geological risk areas in the city of São Paulo based on multi-temporal high-resolution 3D models. Remote Sensing, 15( 12), 3028-. doi:10.3390/rs15123028
NLM
Sousa AM de, Viana CD, Garcia GPB, Grohmann CH. Monitoring geological risk areas in the city of São Paulo based on multi-temporal high-resolution 3D models [Internet]. Remote Sensing. 2023 ; 15( 12): 3028-.[citado 2025 jul. 13 ] Available from: https://doi.org/10.3390/rs15123028
Vancouver
Sousa AM de, Viana CD, Garcia GPB, Grohmann CH. Monitoring geological risk areas in the city of São Paulo based on multi-temporal high-resolution 3D models [Internet]. Remote Sensing. 2023 ; 15( 12): 3028-.[citado 2025 jul. 13 ] Available from: https://doi.org/10.3390/rs15123028
Artigo de periodico
Sentinel-1 imagery used for estimation of soil organic carbon by dual-polarization SAR vegetation indices (2023)
Santos, Erli Pinto dos ; Moreira, Michel Castro; Fernandes-Filho, Elpídio Inácio ; Demattê, José Alexandre Melo ; Dionizio, Emily Ane ; Silva, Demetrius David da ; Cruz, Renata Ranielly Pedroza; Moura-Bueno, Jean Michel; Santos, Uemeson José dos ; Costa, Marcos Heil
Source: Remote Sensing. Unidade: ESALQ
Subjects: APRENDIZADO COMPUTACIONAL, CARBONO, IMAGEAMENTO DE RADAR, MAPEAMENTO DO SOLO, SENSORIAMENTO REMOTO, SOLO DE CERRADO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SANTOS, Erli Pinto dos et al. Sentinel-1 imagery used for estimation of soil organic carbon by dual-polarization SAR vegetation indices. Remote Sensing, v. 15, p. 1-20, 2023Tradução . . Disponível em: https://doi.org/10.3390/rs15235464. Acesso em: 13 jul. 2025.
APA
Santos, E. P. dos, Moreira, M. C., Fernandes-Filho, E. I., Demattê, J. A. M., Dionizio, E. A., Silva, D. D. da, et al. (2023). Sentinel-1 imagery used for estimation of soil organic carbon by dual-polarization SAR vegetation indices. Remote Sensing, 15, 1-20. doi:10.3390/rs15235464
NLM
Santos EP dos, Moreira MC, Fernandes-Filho EI, Demattê JAM, Dionizio EA, Silva DD da, Cruz RRP, Moura-Bueno JM, Santos UJ dos, Costa MH. Sentinel-1 imagery used for estimation of soil organic carbon by dual-polarization SAR vegetation indices [Internet]. Remote Sensing. 2023 ; 15 1-20.[citado 2025 jul. 13 ] Available from: https://doi.org/10.3390/rs15235464
Vancouver
Santos EP dos, Moreira MC, Fernandes-Filho EI, Demattê JAM, Dionizio EA, Silva DD da, Cruz RRP, Moura-Bueno JM, Santos UJ dos, Costa MH. Sentinel-1 imagery used for estimation of soil organic carbon by dual-polarization SAR vegetation indices [Internet]. Remote Sensing. 2023 ; 15 1-20.[citado 2025 jul. 13 ] Available from: https://doi.org/10.3390/rs15235464

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