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| Registros recuperados : 23 | |
| 4. |  | PEREIRA, A. A.; BARROS, D. A. de; ACERBI JUNIOR, F. W.; PEREIRA, J. A. A.; REIS, A. A. dos. Análise da distribuição espacial de áreas queimadas através da função K de Ripley. Scientia Forestalis, Piracicaba, v. 41, n. 100, p. 445-455, dez. 2013.| Biblioteca(s): Embrapa Florestas. |
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| 6. | | PROTÁSIO, T. de P.; COUTO, A. M.; REIS, A. A. dos; TRUGILHO, P. F.; GODINHO, T. P. Potencial siderúrgico e energético do carvão vegetal de clones de Eucalyptus spp. aos 42 meses de idade. Pesquisa Florestal Brasileira, Colombo, v. 33, n. 74, p. 137-149, abr./jun. 2013.| Biblioteca(s): Embrapa Florestas. |
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| 7. | | GUEDES, I. C. de L.; MELLO, J. M. de; SILVEIRA, E. M. de O.; MELLO, C. R. de; REIS, A. A. dos; GOMIDE, L. R. Continuidade espacial de características dendrométricas em povoamentos clonais de eucalyptus sp. avaliada ao longo do tempo. Revista Cerne, Lavras, v. 21, n. 4, p. 527-534, out./dez. 2015.| Biblioteca(s): Embrapa Florestas. |
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| 8. | | REIS, A. A. dos; MELLO, J. M. de; RAIMUNDO, M. R.; ACERBI JUNIOR, F. W.; OLIVEIRA, M. S. de; DINIZ, J. M. F. de S. Estratificação de um povoamento de eucalipto por interpoladores geoestatísticos e sensoriamento remoto. Pesquisa Agropecuária Brasileira, Brasília, DF, v. 51, n. 10, p. 1751-1761, out. 2016. Título em inglês: Stratification of an eucalyptus plantation through geostatistical interpolators and remote sensing.| Biblioteca(s): Embrapa Unidades Centrais. |
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| 10. | | REIS, A. A. dos; PROTÁSIO, T. de P.; MELO, I. C. N. A. de; TRUGILHO, P. F.; CARNEIRO, A. de C. O. Composição da madeira e do carvão vegetal de Eucalyptus urophylla em diferentes locais de plantio. Pesquisa Florestal Brasileira, Colombo, v. 32, n. 71, p. 277-290, jul./set. 2012.| Biblioteca(s): Embrapa Florestas. |
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| 11. | | BATISTA, A. P. B.; MELLO, J. M. de; RAIMUNDO, M. R.; SCOLFORO, H. F.; REIS, A. A. dos; SCOLFORO, J. R. S. Species richness and diversity in shrub savanna using ordinary kriging. Pesquisa Agropecuária Brasileira, Brasília, DF, v. 51, n. 8, p. 958-966, ago. 2016. Título em português: Riqueza e diversidade de espécies em um fragmento de campo cerrado por meio de krigagem ordinária.| Biblioteca(s): Embrapa Unidades Centrais. |
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| 12. | | SILVA, S. T. da; MELLO, J. M. de; ARCEBI JUNIOR, F. W.; REIS, A. A. dos; RAIMUNDO, M. R.; SILVA, I. L. G.; SCOLFORO, J. R. S. Uso de imagens de sensoriamento remoto para estratificação do cerrado em inventários florestais. Pesquisa Florestal Brasileira, Colombo, v. 34, n. 80, p. 337-343, out./dez. 2014.| Biblioteca(s): Embrapa Florestas. |
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| 13. | | PEREIRA, F. R. da S.; REIS, A. A. dos; FREITAS, R. G.; OLIVEIRA, S. R. de M.; AMARAL, L. R. do; FIGUEIREDO, G. K. D. A.; ANTUNES, J. F. G.; LAMPARELLI, R. A. C.; MORO, E.; MAGALHÃES, P. S. G. Imputation of missing parts in UAV orthomosaics using PlanetScope and Sentinel-2 data: a case study in a grass-dominated área. International Journal of Geo-Information, v. 12, n. 2, 41, Feb. 2023.| Biblioteca(s): Embrapa Agricultura Digital. |
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| 14. | | REIS, A. A. dos; WERNER, J. P. S.; SILVA, B. C. da; ANTUNES, J. F. G.; ESQUERDO, J. C. D. M.; FIGUEIREDO, G. K. D. A.; COUTINHO, A. C.; LAMPARELLI, R. A. C.; MAGALHÃES, P. S. G. Can canopy height of mixed pastures in integrated crop-livestock systems be estimated using planetscope imagery? In: WORLD CONGRESS ON INTEGRATED CROP-LIVESTOCK-FORESTRY SYSTEMS, 2., 2021. Proceedings reference. Brasília, DF: Embrapa, 2021. p. 658-663. WCCLF 2021. Evento online.| Biblioteca(s): Embrapa Agricultura Digital. |
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| 15. | | ALMEIDA, H. S. L.; REIS, A. A. dos; WERNER, J. P. S.; ANTUNES, J. F. G.; ZHONG, L.; FIGUEIREDO, G. K. D. A.; ESQUERDO, J. C. D. M.; COUTINHO, A. C.; LAMPARELLI, R. A. C.; MAGALHÃES, P. S. G. Deep neural networks for mapping integrated crop-livestock systems using PlanetScope time series. IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, 2021, Brussels. Proceedings [...]. [S. l.]: IEEE, 2021. p. 4224-4227. IGARSS 2021. Paper WE2.MM-8.3.| Biblioteca(s): Embrapa Agricultura Digital. |
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| 16. | | REIS, A. A. dos; SILVA, M. A. da; SANTOS, F. C. dos; ALBUQUERQUE FILHO, M. R. de; SILVEIRA, M. C. T. da; TEIXEIRA, E. C.; VASCONCELOS, A. de A.; BORGES, I. D.; SOUZA, W. G. Impacto do sistema de pastejo no estoque de carbono lábil do solo arenoso. In: CONGRESO INTERNACIONAL DE SISTEMAS SILVOPASTORILES, 12.; CONGRESO DE LA RED GLOBAL DE SISTEMAS SILVOPASTORILES, 2.; IV SEMINARIO NACIONAL DE SISTEMAS SILVOPASTORILES, 4., 2023, Montevideo; CONGRESO NACIONAL SISTEMAS SILVOPASTORILES, 5., 2023, Buenos Aires. Sistemas silvopastoriles: hacia una diversificación sostenible. Cali: CIPAV, 2023. p. 842-848.| Biblioteca(s): Embrapa Milho e Sorgo. |
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| 17. | | TORO, A. P. S. G. D.; WERNER, J. P. S.; REIS, A. A. dos; ESQUERDO, J. C. D. M.; ANTUNES, J. F. G.; COUTINHO, A. C.; LAMPARELLI, R. A. C.; MAGALHÃES, P. S. G.; FIGUEIREDO, G. K. D. A. Evaluation of early season mapping of integrated crop livestock systems using Sentinel-2 data. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, v. 43, B3, p. 1335-1340, 2022. Edition of proceedings of the 2022 edition of the XXIVth ISPRS Congress, Nice, France.| Biblioteca(s): Embrapa Agricultura Digital. |
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| 18. | | BUENO, I. T.; ANTUNES, J. F. G.; REIS, A. A. dos; WERNER, J. P. S.; TORO, A. P.; FIGUEIREDO, G. K. D. A.; ESQUERDO, J. C. D. M.; LAMPARELLI, R. A. C.; COUTINHO, A. C.; MAGALHÃES, P. S. G. Mapping integrated crop-livestock systems in Brazil with planetscope time series and deep learning. Remote Sensing of Environment, v. 299, 113886, Dec. 2023.| Biblioteca(s): Embrapa Agricultura Digital. |
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| 19. | | REIS, A. A. dos; WERNER, J. P. S.; SILVA, B. C.; FIGUEIREDO, G. K. D. A.; ANTUNES, J. F. G.; ESQUERDO, J. C. D. M.; COUTINHO, A. C.; LAMPARELLI, R. A. C.; ROCHA, J. V.; MAGALHÃES, P. S. G. Monitoring pasture aboveground biomass and canopy height in an integrated crop-livestock system using textural information from PlanetScope imagery. Remote Sensing, v. 12, n. 16, p. 1-21, Aug. 2020. Article number: 2534.| Biblioteca(s): Embrapa Agricultura Digital. |
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| 20. | | ANTUNES, J. F. G.; REIS, A. A. dos; ALMEIDA, H. S. L.; WERNER, J. P. S.; FIGUEIREDO, G. K. D. A.; ESQUERDO, J. C. D. M.; BUENO, I. T.; TORO, A. P. S. G. D.; LAMPARELLI, R. A. C.; COUTINHO, A. C.; MAGALHÃES, P. S. G. Classification of integrated crop-livestock systems using PlanetScope time series. In: SIMPÓSIO BRASILEIRO DE SENSORIAMENTO REMOTO, 20., 2023, Florianópolis. Anais [...]. São José dos Campos: Instituto Nacional de Pesquisas Espaciais, 2023. p. 916-919. Editores: Douglas Francisco Marcolino Gherardi, Ieda Del´Arco Sanches, Luiz Eduardo Oliveira e Cruz de Aragão.| Biblioteca(s): Embrapa Agricultura Digital. |
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| Registros recuperados : 23 | |
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Registro Completo
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Biblioteca(s): |
Embrapa Agricultura Digital. |
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Data corrente: |
24/08/2022 |
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Data da última atualização: |
25/08/2022 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
B - 3 |
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Autoria: |
SANTOS, L. T. dos; WERNER, J. P. S.; REIS, A. A. dos; TORO, A. P. G.; ANTUNES, J. F. G.; COUTINHO, A. C.; LAMPARELLI, R. A. C.; MAGALHÃES, P. S. G.; ESQUERDO, J. C. D. M.; FIGUEIREDO, G. K. D. A. |
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Afiliação: |
FEAGRI/UNICAMP; FEAGRI/UNICAMP; UNICAMP; FEAGRI/UNICAMP; JOAO FRANCISCO GONCALVES ANTUNES, CNPTIA; ALEXANDRE CAMARGO COUTINHO, CNPTIA; UNICAMP; UNICAMP; JULIO CESAR DALLA MORA ESQUERDO, CNPTIA, FEAGRI/UNICAMP; FEAGRI/UNICAMP. |
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Título: |
Multitemporal segmentation of Sentinel-2 images in an agricultural intensification region in Brazil. |
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Ano de publicação: |
2022 |
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Fonte/Imprenta: |
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, v. V-3-2022, p. 389-395, 2022. |
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DOI: |
https://doi.org/10.5194/isprs-annals-V-3-2022-389-2022 |
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Idioma: |
Inglês |
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Notas: |
Edition of proceedings of the 2022 edition of the XXIVth ISPRS Congress, Nice, France. |
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Conteúdo: |
ABSTRACT: With the recent evolution in the sensor's spatial resolution, such as the MultiSpectral Imager (MSI) of the Sentinel-2 mission, the need to use segmentation techniques in satellite images has increased. Although the advantages of image segmentation to delineate agricultural fields in images are already known, the literature shows that it is rarely used to consider temporal changes in highly managed regions with the intensification of agricultural activities. Therefore, this work aimed to evaluate a multitemporal segmentation method based on the coefficient of variation of spectral bands and vegetation indices obtained from Sentinel-2 images, considering two agricultural years (2018-2019 and 2019-2020) in an area with agricultural intensification. Images of the coefficient of variation represented the spectro-temporal dynamics within the study area. These images were also used to apply an edge detection filter (Sobel) to verify their performance. The region-based algorithm Watershed Segmentation (WS) was used in the segmentation process. Subsequently, to assess the quality of the segmentation results produced, the metrics Potential Segmentation Error (PSE), Number-of-Segments Ratio (NSR), and Euclidean Distance 2 (ED2) were calculated from manually delineated reference objects. The segmentation achieved its best performance when applied to the unfiltered coefficient of variation images of spectral bands with an ED2 equal to 7.289 and 2.529 for 2018-2019 and 2019-2020, respectively. There was a tendency for the WS algorithm to produce over-segmentation in the study area; however, its use proved to be effective in identifying objects in a dynamic area with the intensification of agricultural activities. MenosABSTRACT: With the recent evolution in the sensor's spatial resolution, such as the MultiSpectral Imager (MSI) of the Sentinel-2 mission, the need to use segmentation techniques in satellite images has increased. Although the advantages of image segmentation to delineate agricultural fields in images are already known, the literature shows that it is rarely used to consider temporal changes in highly managed regions with the intensification of agricultural activities. Therefore, this work aimed to evaluate a multitemporal segmentation method based on the coefficient of variation of spectral bands and vegetation indices obtained from Sentinel-2 images, considering two agricultural years (2018-2019 and 2019-2020) in an area with agricultural intensification. Images of the coefficient of variation represented the spectro-temporal dynamics within the study area. These images were also used to apply an edge detection filter (Sobel) to verify their performance. The region-based algorithm Watershed Segmentation (WS) was used in the segmentation process. Subsequently, to assess the quality of the segmentation results produced, the metrics Potential Segmentation Error (PSE), Number-of-Segments Ratio (NSR), and Euclidean Distance 2 (ED2) were calculated from manually delineated reference objects. The segmentation achieved its best performance when applied to the unfiltered coefficient of variation images of spectral bands with an ED2 equal to 7.289 and 2.529 for 2018-2019 and 2019-202... Mostrar Tudo |
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Palavras-Chave: |
AssesSeg; Coefficient of variation; Coeficiente de variação; Detecção de bordas; Edge detection; Índice de vegetação; Intensificação agrícola; OBIA; Segmentação de bacias hidrográficas; Sobel; Watershed segmentation. |
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Thesaurus NAL: |
Vegetation index. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/doc/1145716/1/AP-Multitemporal-segmentation-Sentinel2-2022.pdf
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Marc: |
LEADER 03126naa a2200397 a 4500
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008 2022 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.5194/isprs-annals-V-3-2022-389-2022$2DOI
100 1 $aSANTOS, L. T. dos
245 $aMultitemporal segmentation of Sentinel-2 images in an agricultural intensification region in Brazil.$h[electronic resource]
260 $c2022
500 $aEdition of proceedings of the 2022 edition of the XXIVth ISPRS Congress, Nice, France.
520 $aABSTRACT: With the recent evolution in the sensor's spatial resolution, such as the MultiSpectral Imager (MSI) of the Sentinel-2 mission, the need to use segmentation techniques in satellite images has increased. Although the advantages of image segmentation to delineate agricultural fields in images are already known, the literature shows that it is rarely used to consider temporal changes in highly managed regions with the intensification of agricultural activities. Therefore, this work aimed to evaluate a multitemporal segmentation method based on the coefficient of variation of spectral bands and vegetation indices obtained from Sentinel-2 images, considering two agricultural years (2018-2019 and 2019-2020) in an area with agricultural intensification. Images of the coefficient of variation represented the spectro-temporal dynamics within the study area. These images were also used to apply an edge detection filter (Sobel) to verify their performance. The region-based algorithm Watershed Segmentation (WS) was used in the segmentation process. Subsequently, to assess the quality of the segmentation results produced, the metrics Potential Segmentation Error (PSE), Number-of-Segments Ratio (NSR), and Euclidean Distance 2 (ED2) were calculated from manually delineated reference objects. The segmentation achieved its best performance when applied to the unfiltered coefficient of variation images of spectral bands with an ED2 equal to 7.289 and 2.529 for 2018-2019 and 2019-2020, respectively. There was a tendency for the WS algorithm to produce over-segmentation in the study area; however, its use proved to be effective in identifying objects in a dynamic area with the intensification of agricultural activities.
650 $aVegetation index
653 $aAssesSeg
653 $aCoefficient of variation
653 $aCoeficiente de variação
653 $aDetecção de bordas
653 $aEdge detection
653 $aÍndice de vegetação
653 $aIntensificação agrícola
653 $aOBIA
653 $aSegmentação de bacias hidrográficas
653 $aSobel
653 $aWatershed segmentation
700 1 $aWERNER, J. P. S.
700 1 $aREIS, A. A. dos
700 1 $aTORO, A. P. G.
700 1 $aANTUNES, J. F. G.
700 1 $aCOUTINHO, A. C.
700 1 $aLAMPARELLI, R. A. C.
700 1 $aMAGALHÃES, P. S. G.
700 1 $aESQUERDO, J. C. D. M.
700 1 $aFIGUEIREDO, G. K. D. A.
773 $tISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences$gv. V-3-2022, p. 389-395, 2022.
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