ReP USP - Resultado da busca

Artigo de periodico
Radiative transfer model-integrated approach for hyperspectral simulation of mixed soil-vegetation scenarios and soil organic carbon estimation (2025)
Abdelbaki, Asmaa; Milewski, Robert; Saberioon, Mohammadmehdi; Berger, Katja; Demattê, Jose Alexandre Melo ; Chabrillat, Sabine
Source: Remote Sensing. Unidade: ESALQ
Subjects: CARBONO, COBERTURA DO SOLO, CRESCIMENTO VEGETAL, ESPECTROSCOPIA, RELAÇÃO SOLO-ÁGUA-PLANTA-ATMOSFERA, SENSORIAMENTO REMOTO, SIMULAÇÃO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
ABDELBAKI, Asmaa et al. Radiative transfer model-integrated approach for hyperspectral simulation of mixed soil-vegetation scenarios and soil organic carbon estimation. Remote Sensing, v. 17, p. 1-20, 2025Tradução . . Disponível em: https://doi.org/10.3390/rs17142355. Acesso em: 24 nov. 2025.
APA
Abdelbaki, A., Milewski, R., Saberioon, M., Berger, K., Demattê, J. A. M., & Chabrillat, S. (2025). Radiative transfer model-integrated approach for hyperspectral simulation of mixed soil-vegetation scenarios and soil organic carbon estimation. Remote Sensing, 17, 1-20. doi:10.3390/rs17142355
NLM
Abdelbaki A, Milewski R, Saberioon M, Berger K, Demattê JAM, Chabrillat S. Radiative transfer model-integrated approach for hyperspectral simulation of mixed soil-vegetation scenarios and soil organic carbon estimation [Internet]. Remote Sensing. 2025 ; 17 1-20.[citado 2025 nov. 24 ] Available from: https://doi.org/10.3390/rs17142355
Vancouver
Abdelbaki A, Milewski R, Saberioon M, Berger K, Demattê JAM, Chabrillat S. Radiative transfer model-integrated approach for hyperspectral simulation of mixed soil-vegetation scenarios and soil organic carbon estimation [Internet]. Remote Sensing. 2025 ; 17 1-20.[citado 2025 nov. 24 ] Available from: https://doi.org/10.3390/rs17142355
Artigo de periodico
High-throughput identification and prediction of early stress markers in soybean under progressive water regimes via hyperspectral spectroscopy and machine learning (2025)
Oliveira, Caio Almeida de; Vedana, Nicole Ghinzelli ; Mendonça, Weslei Augusto; Gonçalves, João Vitor Ferreira ; Matos, Dheynne Heyre Silva de; Furlanetto, Renato Herrig; Crusiol, Luis Guilherme Teixeira; Reis, Amanda Silveira; Antunes, Werner Camargos ; Oliveira, Roney Berti de ; Chicati, Marcelo Luiz ; Demattê, José Alexandre Melo ; Nanni, Marcos Rafael ; Falcioni, Renan
Source: Remote Sensing. Unidade: ESALQ
Subjects: AGRICULTURA DE PRECISÃO, APRENDIZADO COMPUTACIONAL, DEFICIT HÍDRICO, ESPECTROSCOPIA, SENSORIAMENTO REMOTO, SOJA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
OLIVEIRA, Caio Almeida de et al. High-throughput identification and prediction of early stress markers in soybean under progressive water regimes via hyperspectral spectroscopy and machine learning. Remote Sensing, v. 17, p. 1-31, 2025Tradução . . Disponível em: https://doi.org/10.3390/rs17203409. Acesso em: 24 nov. 2025.
APA
Oliveira, C. A. de, Vedana, N. G., Mendonça, W. A., Gonçalves, J. V. F., Matos, D. H. S. de, Furlanetto, R. H., et al. (2025). High-throughput identification and prediction of early stress markers in soybean under progressive water regimes via hyperspectral spectroscopy and machine learning. Remote Sensing, 17, 1-31. doi:10.3390/rs17203409
NLM
Oliveira CA de, Vedana NG, Mendonça WA, Gonçalves JVF, Matos DHS de, Furlanetto RH, Crusiol LGT, Reis AS, Antunes WC, Oliveira RB de, Chicati ML, Demattê JAM, Nanni MR, Falcioni R. High-throughput identification and prediction of early stress markers in soybean under progressive water regimes via hyperspectral spectroscopy and machine learning [Internet]. Remote Sensing. 2025 ; 17 1-31.[citado 2025 nov. 24 ] Available from: https://doi.org/10.3390/rs17203409
Vancouver
Oliveira CA de, Vedana NG, Mendonça WA, Gonçalves JVF, Matos DHS de, Furlanetto RH, Crusiol LGT, Reis AS, Antunes WC, Oliveira RB de, Chicati ML, Demattê JAM, Nanni MR, Falcioni R. High-throughput identification and prediction of early stress markers in soybean under progressive water regimes via hyperspectral spectroscopy and machine learning [Internet]. Remote Sensing. 2025 ; 17 1-31.[citado 2025 nov. 24 ] Available from: https://doi.org/10.3390/rs17203409
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
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
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: 24 nov. 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 nov. 24 ] 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 nov. 24 ] Available from: http://dx.doi.org/10.3390/rs17091500
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
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
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: 24 nov. 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 nov. 24 ] 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 nov. 24 ] Available from: https://doi.org/10.3390/rs16213935
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
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
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: 24 nov. 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 nov. 24 ] 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 nov. 24 ] Available from: https://doi.org/10.3390/rs16234543
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
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
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: 24 nov. 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 nov. 24 ] 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 nov. 24 ] 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
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
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: 24 nov. 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 nov. 24 ] 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 nov. 24 ] Available from: https://doi.org/10.3390/rs16050863
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
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
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: 24 nov. 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 nov. 24 ] 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 nov. 24 ] Available from: https://dx.doi.org/10.3390/rs16142559
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
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
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: 24 nov. 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 nov. 24 ] 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 nov. 24 ] Available from: https://doi.org/10.3390/rs16224250
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
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
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: 24 nov. 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 nov. 24 ] 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 nov. 24 ] 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
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
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: 24 nov. 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 nov. 24 ] 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 nov. 24 ] Available from: https://doi.org/10.3390/rs16142663
Artigo de periodico
Near-surface geophysical characterization of a marble deposit to promote a sustainable small-scale mining (2024)
Penna, Nathália de Souza ; Porsani, Jorge Luís ; Rangel, Rodrigo Corrêa ; Costa, Victor Hugo Hott; Oliveira, Nicolas Correa de; Stangari, Marcelo Cesar; Sousa, Conrado de Carvalho Braz de Faria
Source: Remote Sensing. Unidade: IAG
Subjects: GEOFÍSICA APLICADA, GEOELETRICIDADE, RADAR DE PENETRAÇÃO NO SOLO, MÁRMORE, MINERAÇÃO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
PENNA, Nathália de Souza et al. Near-surface geophysical characterization of a marble deposit to promote a sustainable small-scale mining. Remote Sensing, v. 16, p. 1-19, 2024Tradução . . Disponível em: https://doi.org/10.3390/rs16071147. Acesso em: 24 nov. 2025.
APA
Penna, N. de S., Porsani, J. L., Rangel, R. C., Costa, V. H. H., Oliveira, N. C. de, Stangari, M. C., & Sousa, C. de C. B. de F. (2024). Near-surface geophysical characterization of a marble deposit to promote a sustainable small-scale mining. Remote Sensing, 16, 1-19. doi:10.3390/rs16071147
NLM
Penna N de S, Porsani JL, Rangel RC, Costa VHH, Oliveira NC de, Stangari MC, Sousa C de CB de F. Near-surface geophysical characterization of a marble deposit to promote a sustainable small-scale mining [Internet]. Remote Sensing. 2024 ; 16 1-19.[citado 2025 nov. 24 ] Available from: https://doi.org/10.3390/rs16071147
Vancouver
Penna N de S, Porsani JL, Rangel RC, Costa VHH, Oliveira NC de, Stangari MC, Sousa C de CB de F. Near-surface geophysical characterization of a marble deposit to promote a sustainable small-scale mining [Internet]. Remote Sensing. 2024 ; 16 1-19.[citado 2025 nov. 24 ] Available from: https://doi.org/10.3390/rs16071147
Artigo de periodico
Assessing forest degradation through remote sensing in the brazilian Amazon: implications and perspectives for sustainable forest management (2024)
Oliveira, Afonso Henrique Moraes; Matricardi, Eraldo Aparecido ; Aragão, Luiz Eduardo Oliveira e Cruz de ; Felix, Iara Musse; Chaves, José Humberto; Magliano, Mauro Mendonça; Oliveira-Junior, José Max Barbosa ; Vieira, Thiago Almeida ; Santos, Lizandra Elizeário dos; Reis, Leonardo Pequeno ; Pereira, Diogo Otávio Scália; Dias, Carlos Tadeu dos Santos ; Gama, João Ricardo Vasconcellos; Martorano, Lucieta Guerreiro
Source: Remote Sensing. Unidade: ESALQ
Subjects: DEGRADAÇÃO AMBIENTAL, FLORESTAS TROPICAIS, EXPLORAÇÃO FLORESTAL, IMPACTOS AMBIENTAIS, MADEIRA, MANEJO FLORESTAL, SENSORIAMENTO REMOTO, SILVICULTURA SUSTENTÁVEL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
OLIVEIRA, Afonso Henrique Moraes et al. Assessing forest degradation through remote sensing in the brazilian Amazon: implications and perspectives for sustainable forest management. Remote Sensing, v. 16, p. 1-24, 2024Tradução . . Disponível em: https://doi.org/10.3390/rs16234557. Acesso em: 24 nov. 2025.
APA
Oliveira, A. H. M., Matricardi, E. A., Aragão, L. E. O. e C. de, Felix, I. M., Chaves, J. H., Magliano, M. M., et al. (2024). Assessing forest degradation through remote sensing in the brazilian Amazon: implications and perspectives for sustainable forest management. Remote Sensing, 16, 1-24. doi:10.3390/rs16234557
NLM
Oliveira AHM, Matricardi EA, Aragão LEO e C de, Felix IM, Chaves JH, Magliano MM, Oliveira-Junior JMB, Vieira TA, Santos LE dos, Reis LP, Pereira DOS, Dias CT dos S, Gama JRV, Martorano LG. Assessing forest degradation through remote sensing in the brazilian Amazon: implications and perspectives for sustainable forest management [Internet]. Remote Sensing. 2024 ; 16 1-24.[citado 2025 nov. 24 ] Available from: https://doi.org/10.3390/rs16234557
Vancouver
Oliveira AHM, Matricardi EA, Aragão LEO e C de, Felix IM, Chaves JH, Magliano MM, Oliveira-Junior JMB, Vieira TA, Santos LE dos, Reis LP, Pereira DOS, Dias CT dos S, Gama JRV, Martorano LG. Assessing forest degradation through remote sensing in the brazilian Amazon: implications and perspectives for sustainable forest management [Internet]. Remote Sensing. 2024 ; 16 1-24.[citado 2025 nov. 24 ] Available from: https://doi.org/10.3390/rs16234557
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
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
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: 24 nov. 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 nov. 24 ] 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 nov. 24 ] 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
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
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: 24 nov. 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 nov. 24 ] 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 nov. 24 ] 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
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
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: 24 nov. 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 nov. 24 ] 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 nov. 24 ] 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
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
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: 24 nov. 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 nov. 24 ] 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 nov. 24 ] 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: 24 nov. 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 nov. 24 ] 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 nov. 24 ] 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: 24 nov. 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 nov. 24 ] 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 nov. 24 ] 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: 24 nov. 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 nov. 24 ] 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 nov. 24 ] Available from: https://doi.org/10.3390/rs15215137

USP Schools

ReP

Filtros

USP Schools

Departament

Authors

USP affiliated authors

Date published

Subjects

Funding Agencies

Indexado em

Non normalized affiliation

Countries of institutions of collaboration