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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: 09 nov. 2024.
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 2024 nov. 09 ] 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 2024 nov. 09 ] Available from: https://doi.org/10.3390/rs16163009
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
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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: 09 nov. 2024.
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 2024 nov. 09 ] 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 2024 nov. 09 ] Available from: https://doi.org/10.3390/rs15235464
Artigo de periodico
A conceptual model for detecting small-scale forest disturbances based on ecosystem worphological traits (2022)
Stoddart, Jaz; Almeida, Danilo Roberti Alves de ; Silva, Carlos Alberto; Görgens, Eric Bastos; Keller, Michael; Valbuena, Ruben
Source: Remote Sensing. Unidade: ESALQ
Subjects: CARBONO, CORTE (PLANTAS), DOSSEL (BOTÂNICA), ECOSSISTEMAS FLORESTAIS, FLORESTAS TROPICAIS, MODELAGEM DE DADOS, SENSORIAMENTO REMOTO, TECNOLOGIA LIDAR
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ABNT
STODDART, Jaz et al. A conceptual model for detecting small-scale forest disturbances based on ecosystem worphological traits. Remote Sensing, v. 14, p. 1-20, 2022Tradução . . Disponível em: https://doi.org/10.3390/rs14040933. Acesso em: 09 nov. 2024.
APA
Stoddart, J., Almeida, D. R. A. de, Silva, C. A., Görgens, E. B., Keller, M., & Valbuena, R. (2022). A conceptual model for detecting small-scale forest disturbances based on ecosystem worphological traits. Remote Sensing, 14, 1-20. doi:10.3390/rs14040933
NLM
Stoddart J, Almeida DRA de, Silva CA, Görgens EB, Keller M, Valbuena R. A conceptual model for detecting small-scale forest disturbances based on ecosystem worphological traits [Internet]. Remote Sensing. 2022 ; 14 1-20.[citado 2024 nov. 09 ] Available from: https://doi.org/10.3390/rs14040933
Vancouver
Stoddart J, Almeida DRA de, Silva CA, Görgens EB, Keller M, Valbuena R. A conceptual model for detecting small-scale forest disturbances based on ecosystem worphological traits [Internet]. Remote Sensing. 2022 ; 14 1-20.[citado 2024 nov. 09 ] Available from: https://doi.org/10.3390/rs14040933
Artigo de periodico
Earth observation data-driven cropland soil monitoring: a review (2021)
Tziolas, Nikolaos ; Tsakiridis, Nikolaos; Chabrillat, Sabine ; Demattê, José Alexandre Melo ; Ben-Dor, Eyal; Gholizadeh, Asa ; Zalidis, George; Van Wesemael, Bas
Source: Remote Sensing. Unidade: ESALQ
Subjects: ANÁLISE ESPECTRAL, APRENDIZADO COMPUTACIONAL, CARBONO, MAPEAMENTO DO SOLO, REVISÃO SISTEMÁTICA, SENSORIAMENTO REMOTO, SOLO AGRÍCOLA
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ABNT
TZIOLAS, Nikolaos et al. Earth observation data-driven cropland soil monitoring: a review. Remote Sensing, v. 13, p. 1-29, 2021Tradução . . Disponível em: https://doi.org/10.3390/rs13214439. Acesso em: 09 nov. 2024.
APA
Tziolas, N., Tsakiridis, N., Chabrillat, S., Demattê, J. A. M., Ben-Dor, E., Gholizadeh, A., et al. (2021). Earth observation data-driven cropland soil monitoring: a review. Remote Sensing, 13, 1-29. doi:10.3390/rs13214439
NLM
Tziolas N, Tsakiridis N, Chabrillat S, Demattê JAM, Ben-Dor E, Gholizadeh A, Zalidis G, Van Wesemael B. Earth observation data-driven cropland soil monitoring: a review [Internet]. Remote Sensing. 2021 ; 13 1-29.[citado 2024 nov. 09 ] Available from: https://doi.org/10.3390/rs13214439
Vancouver
Tziolas N, Tsakiridis N, Chabrillat S, Demattê JAM, Ben-Dor E, Gholizadeh A, Zalidis G, Van Wesemael B. Earth observation data-driven cropland soil monitoring: a review [Internet]. Remote Sensing. 2021 ; 13 1-29.[citado 2024 nov. 09 ] Available from: https://doi.org/10.3390/rs13214439
Artigo de periodico
Drivers of Organic Carbon Stocks in Different LULC History and Along Soil Depth for a 30 Years Image Time Series (2021)
Tayebi, Mahboobeh ; Rosas, Jorge Tadeu Fim ; Mendes, Wanderson de Sousa ; Poppiel, Raul Roberto ; Ostovari, Yaser; Ruiz, Luis Fernando Chimelo ; Santos, Natasha Valadares dos ; Cerri, Carlos Eduardo Pellegrino ; Silva, Sérgio Henrique Godinho ; Curi, Nilton ; Quiñonez Silvero, Nélida Elizabet ; Demattê, Jose Alexandre Melo
Source: Remote Sensing. Unidade: ESALQ
Subjects: APRENDIZADO COMPUTACIONAL, CARBONO, IMAGEAMENTO DE SATÉLITE, MONITORAMENTO AMBIENTAL, SENSORIAMENTO REMOTO, USO DO SOLO
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ABNT
TAYEBI, Mahboobeh et al. Drivers of Organic Carbon Stocks in Different LULC History and Along Soil Depth for a 30 Years Image Time Series. Remote Sensing, v. 13, p. 1-32, 2021Tradução . . Disponível em: https://doi.org/10.3390/rs13112223. Acesso em: 09 nov. 2024.
APA
Tayebi, M., Rosas, J. T. F., Mendes, W. de S., Poppiel, R. R., Ostovari, Y., Ruiz, L. F. C., et al. (2021). Drivers of Organic Carbon Stocks in Different LULC History and Along Soil Depth for a 30 Years Image Time Series. Remote Sensing, 13, 1-32. doi:10.3390/rs13112223
NLM
Tayebi M, Rosas JTF, Mendes W de S, Poppiel RR, Ostovari Y, Ruiz LFC, Santos NV dos, Cerri CEP, Silva SHG, Curi N, Quiñonez Silvero NE, Demattê JAM. Drivers of Organic Carbon Stocks in Different LULC History and Along Soil Depth for a 30 Years Image Time Series [Internet]. Remote Sensing. 2021 ; 13 1-32.[citado 2024 nov. 09 ] Available from: https://doi.org/10.3390/rs13112223
Vancouver
Tayebi M, Rosas JTF, Mendes W de S, Poppiel RR, Ostovari Y, Ruiz LFC, Santos NV dos, Cerri CEP, Silva SHG, Curi N, Quiñonez Silvero NE, Demattê JAM. Drivers of Organic Carbon Stocks in Different LULC History and Along Soil Depth for a 30 Years Image Time Series [Internet]. Remote Sensing. 2021 ; 13 1-32.[citado 2024 nov. 09 ] Available from: https://doi.org/10.3390/rs13112223
Artigo de periodico
Individual tree attribute estimation and uniformity assessment in fast-growing eucalyptus spp. Forest plantations using lidar and linear mixed-effects models (2020)
Leite, R. V; Silva, C. A; Mohan, M; Cardil, A; Almeida, Danilo Roberti Alves de ; Carvalho, S. P. C. de
Source: Remote Sensing. Unidade: ESALQ
Subjects: CARBONO, DENDROMETRIA, EUCALIPTO, INVENTÁRIO FLORESTAL, MODELOS MATEMÁTICOS, SENSORIAMENTO REMOTO, TECNOLOGIA LIDAR
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ABNT
LEITE, R. V et al. Individual tree attribute estimation and uniformity assessment in fast-growing eucalyptus spp. Forest plantations using lidar and linear mixed-effects models. Remote Sensing, v. 12, p. 1-20, 2020Tradução . . Disponível em: https://doi.org/10.3390/rs12213599. Acesso em: 09 nov. 2024.
APA
Leite, R. V., Silva, C. A., Mohan, M., Cardil, A., Almeida, D. R. A. de, & Carvalho, S. P. C. de. (2020). Individual tree attribute estimation and uniformity assessment in fast-growing eucalyptus spp. Forest plantations using lidar and linear mixed-effects models. Remote Sensing, 12, 1-20. doi:10.3390/rs12213599
NLM
Leite RV, Silva CA, Mohan M, Cardil A, Almeida DRA de, Carvalho SPC de. Individual tree attribute estimation and uniformity assessment in fast-growing eucalyptus spp. Forest plantations using lidar and linear mixed-effects models [Internet]. Remote Sensing. 2020 ; 12 1-20.[citado 2024 nov. 09 ] Available from: https://doi.org/10.3390/rs12213599
Vancouver
Leite RV, Silva CA, Mohan M, Cardil A, Almeida DRA de, Carvalho SPC de. Individual tree attribute estimation and uniformity assessment in fast-growing eucalyptus spp. Forest plantations using lidar and linear mixed-effects models [Internet]. Remote Sensing. 2020 ; 12 1-20.[citado 2024 nov. 09 ] Available from: https://doi.org/10.3390/rs12213599
Artigo de periodico
Performance of laser-based electronic devices for structural analysis of amazonian terra-firme forests (2019)
Pereira, Iokanam Sales; Nascimento, Henrique E. Mendonça do; Vicari, Matheus Boni; Disney, Mathias; DeLucia, Evan H.; Domingues, Tomas Ferreira ; Kruijt, Bart; Lapola, David; Meir, Patrick; Norby, Richard J.; Ometto, Jean P. H. B.; Quesada, Carlos A.; Rammig, Anja; Hofhansl, Florian
Source: Remote Sensing. Unidade: FFCLRP
Subjects: FLORESTAS, BIOMASSA, CARBONO, ECOSSISTEMAS FLORESTAIS, SENSORIAMENTO REMOTO
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ABNT
PEREIRA, Iokanam Sales et al. Performance of laser-based electronic devices for structural analysis of amazonian terra-firme forests. Remote Sensing, v. 11, n. 5, p. 1-25, 2019Tradução . . Disponível em: https://doi.org/10.3390/rs11050510. Acesso em: 09 nov. 2024.
APA
Pereira, I. S., Nascimento, H. E. M. do, Vicari, M. B., Disney, M., DeLucia, E. H., Domingues, T. F., et al. (2019). Performance of laser-based electronic devices for structural analysis of amazonian terra-firme forests. Remote Sensing, 11( 5), 1-25. doi:10.3390/rs11050510
NLM
Pereira IS, Nascimento HEM do, Vicari MB, Disney M, DeLucia EH, Domingues TF, Kruijt B, Lapola D, Meir P, Norby RJ, Ometto JPHB, Quesada CA, Rammig A, Hofhansl F. Performance of laser-based electronic devices for structural analysis of amazonian terra-firme forests [Internet]. Remote Sensing. 2019 ; 11( 5): 1-25.[citado 2024 nov. 09 ] Available from: https://doi.org/10.3390/rs11050510
Vancouver
Pereira IS, Nascimento HEM do, Vicari MB, Disney M, DeLucia EH, Domingues TF, Kruijt B, Lapola D, Meir P, Norby RJ, Ometto JPHB, Quesada CA, Rammig A, Hofhansl F. Performance of laser-based electronic devices for structural analysis of amazonian terra-firme forests [Internet]. Remote Sensing. 2019 ; 11( 5): 1-25.[citado 2024 nov. 09 ] Available from: https://doi.org/10.3390/rs11050510

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