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| Registros recuperados : 11 | |
| 3. |  | CHINO, D. Y. T.; GONÇALVES, R. R. V.; ROMANI, L. A. S.; TRAINA JÚNIOR, C.; TRAINA, A. J. M. TrieMotif: a new and efficient method to mine frequent K-motifs from large time series. In: INTERNATIONAL CONFERENCE ON ENTERPRISE INFORMATION SYSTEMS, 16.; INTERNATIONAL CONFERENCE ON EVALUATION OF NOVEL APPROACHES TO SOFTWARE ENGINEERING, 9., 2014, Lisbon. Proceedings... [S.l.]: Scitepress, 2014. p. 60-69. ICEIS 2014.| Biblioteca(s): Embrapa Agricultura Digital. |
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| 4. | | CHINO, D. Y. T.; GONCALVES, R. R. V.; ROMANI, L. A. S.; TRAINA JÚNIOR, C.; TRAINA, A. J. M. Discovering frequent patterns on agrometeorological data with TrieMotif. In: INTERNATIONAL CONFERENCE ON ENTERPRISE INFORMATION SYSTEMS, 16., 2014, Lisbon. Enterprise information systems: ICEIS 2014: revised selected papers. Switzerland: Springer, 2015. p. 91-107. (Lecture notes in business information processing, 227). Editores: José Cordeiro, Slimane Hammoudi, Leszek Maciaszek, Olivier Camp, Joaquim Filipe.| Biblioteca(s): Embrapa Agricultura Digital. |
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| 6. | | AMARAL, B. F.; CHINO, D. Y.; ROMANI, L. A. S.; GONÇALVES, R. R. V.; SOUSA, E. P. M. de; TRAINA, A. J. M. Análise e mineração de dados de sensores orbitais para acompanhamento de safras de cana-de-açúcar. In: CONGRESSO DA SOCIEDADE BRASILEIRA DE COMPUTAÇÃO, 31; WORKSHOP DE COMPUTAÇÃO APLICADA À GESTÃO DO MEIO AMBIENTE E RECURSOS NATURAIS, 3., 2011, Natal. Computação para todos: no caminho da evolução social: anais. Natal: UFRN, 2O11. p. 1472-1481. WCAMA 2011.| Biblioteca(s): Embrapa Agricultura Digital. |
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| 7. | | CHINO, D. Y. T.; ROMANI, L. A. S.; AVALHAIS, L. P. S.; OLIVEIRA, W. D.; GONÇALVES, R. R. V.; TRAINA JÚNIOR, C.; TRAINA, A. J. M. The NInA Framework using gesture to improve interaction and collaboration in geographical information systems. In: INTERNATIONAL CONFERENCE ON ENTERPRISE INFORMATION SYSTEMS, 15.; INTERNATIONAL CONFERENCE ON EVALUATION OF NOVEL APPROACHES TO SOFTWARE ENGINEERING, 8., 2013, Angers Loire Valley. Proceedings... [S.l.]: Scitepress, 2013. p. 35-43. ICEIS 2013. ENASE 2013.| Biblioteca(s): Embrapa Agricultura Digital. |
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| 8. | | ROMANI, L. A. S.; AVILA, A. M. H. de; CHINO, D. Y. T.; ZULLO JÚNIOR, J.; CHBEIR, R.; TRAINA JÚNIOR, C.; TRAINA, A. J. M. A new time series mining approach applied to multitemporal remote sensing imagery. IEEE transactions on geoscience and remote sensing, New York, v. 51, n. 1, p. 140-150, Jan. 2013.| Biblioteca(s): Embrapa Agricultura Digital. |
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| 9. | | ROMANI, L. A. S.; CHINO, D. Y. T.; AVALHAIS, L. P. S.; OLIVEIRA, W. D.; GONÇALVES, R. R. V.; TRAINA JÚNIOR, C.; TRAINA, A. J. M. Involving users in the gestural language definition process for the NInA framework. In: BRAZILIAN SYMPOSIUM ON HUMAN FACTORS IN COMPUTING SYSTEMS, 12., 2013, Manaus. Proceedings... Porto Alegre: SBC, 2013. p. 280-283. IHC 2013.| Biblioteca(s): Embrapa Agricultura Digital. |
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| 10. | | AMARAL, B. F.; CHINO, D. Y. T.; ROMANI, L. A. S.; GONÇALVES, R. R. V.; TRAINA, A. J. M.; SOUSA, E. P. M. The SITSMining framework: a data mining approach for satellite image time series. In: INTERNATIONAL CONFERENCE ON ENTERPRISE INFORMATION SYSTEMS, 16.; INTERNATIONAL CONFERENCE ON EVALUATION OF NOVEL APPROACHES TO SOFTWARE ENGINEERING, 9., 2014, Lisbon. Proceedings... [S.l.]: Scitepress, 2014. p. 225-232. ICEIS 2014.| Biblioteca(s): Embrapa Agricultura Digital. |
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| 11. | | ROMANI, L. A. S.; GONÇALVES, R. R. V.; AMARAL, B. F.; CHINO, D. Y. T.; ZULLO JUNIOR, J.; TRAINA JUNIOR, C.; SOUSA, E. P. M.; TRAINA, A. J. M. TRAINA. Clustering analysis applied to NOAA/AVHRR multitemporal images to improve the monitoring process of sugarcane crops. In: INTERNATIONAL WORKSHOP ON THE ANALYSIS OF MULTI-TEMPORAL REMOTE SENSING IMAGES, 6., 2011, Trento. Proceedings... Piscataway: IEEE; Italy: University of Trento, 2011. p. 33-36.| Biblioteca(s): Embrapa Agricultura Digital. |
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| Registros recuperados : 11 | |
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 | Acesso ao texto completo restrito à biblioteca da Embrapa Agricultura Digital. Para informações adicionais entre em contato com cnptia.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Agricultura Digital. |
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Data corrente: |
04/12/2014 |
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Data da última atualização: |
08/01/2020 |
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Tipo da produção científica: |
Artigo em Anais de Congresso |
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Autoria: |
AMARAL, B. F.; CHINO, D. Y. T.; ROMANI, L. A. S.; GONÇALVES, R. R. V.; TRAINA, A. J. M.; SOUSA, E. P. M. |
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Afiliação: |
BRUNO F. AMARAL, ICMC/USP; DANIEL Y. T. CHINO, ICMC/USP; LUCIANA ALVIM SANTOS ROMANI, CNPTIA; RENATA R. V. GONÇALVES, Cepagri/Unicamp; AGMA J. M. TRAINA, ICMC/USP; ELAINE P. M. SOUSA, ICMC/USP. |
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Título: |
The SITSMining framework: a data mining approach for satellite image time series. |
|
Ano de publicação: |
2014 |
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Fonte/Imprenta: |
In: INTERNATIONAL CONFERENCE ON ENTERPRISE INFORMATION SYSTEMS, 16.; INTERNATIONAL CONFERENCE ON EVALUATION OF NOVEL APPROACHES TO SOFTWARE ENGINEERING, 9., 2014, Lisbon. Proceedings... [S.l.]: Scitepress, 2014. |
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Páginas: |
p. 225-232. |
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ISBN: |
978-989-758-027-7 |
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Idioma: |
Inglês |
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Notas: |
ICEIS 2014. |
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Conteúdo: |
Abstract: The amount of data generated and stored in many domains has increased in the last years. In remote sensing, this scenario of bursting data is not different. As the volume of satellite images stored in databases grows, the demand for computational algorithms that can handle and analyze this volume of data and extract useful patterns has increased. In this context, the computational support for satellite images data analysis becomes essential. In this work, we present the SITSMining framework, which applies a methodology based on data mining techniques to extract patterns and information from time series obtained from satellite images. In Brazil, as the agricultural production provides great part of the national resources, the analysis of satellite images is a valuable way to help crops monitoring over seasons, which is an important task to the economy of the country. Thus, we apply the framework to analyze multitemporal satellite images, aiming to help crop monitoring and forecasting of Brazilian agriculture. |
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Palavras-Chave: |
Data mining; Imagens de satélite; Mineração de dados; Multivariate time series; Séries temporais multivariadas. |
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Thesagro: |
Sensoriamento Remoto. |
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Thesaurus NAL: |
Remote sensing; Time series analysis. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
|
Marc: |
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008 2014 bl uuuu u00u1 u #d
020 $a978-989-758-027-7
100 1 $aAMARAL, B. F.
245 $aThe SITSMining framework$ba data mining approach for satellite image time series.$h[electronic resource]
260 $aIn: INTERNATIONAL CONFERENCE ON ENTERPRISE INFORMATION SYSTEMS, 16.; INTERNATIONAL CONFERENCE ON EVALUATION OF NOVEL APPROACHES TO SOFTWARE ENGINEERING, 9., 2014, Lisbon. Proceedings... [S.l.]: Scitepress$c2014
300 $ap. 225-232.
500 $aICEIS 2014.
520 $aAbstract: The amount of data generated and stored in many domains has increased in the last years. In remote sensing, this scenario of bursting data is not different. As the volume of satellite images stored in databases grows, the demand for computational algorithms that can handle and analyze this volume of data and extract useful patterns has increased. In this context, the computational support for satellite images data analysis becomes essential. In this work, we present the SITSMining framework, which applies a methodology based on data mining techniques to extract patterns and information from time series obtained from satellite images. In Brazil, as the agricultural production provides great part of the national resources, the analysis of satellite images is a valuable way to help crops monitoring over seasons, which is an important task to the economy of the country. Thus, we apply the framework to analyze multitemporal satellite images, aiming to help crop monitoring and forecasting of Brazilian agriculture.
650 $aRemote sensing
650 $aTime series analysis
650 $aSensoriamento Remoto
653 $aData mining
653 $aImagens de satélite
653 $aMineração de dados
653 $aMultivariate time series
653 $aSéries temporais multivariadas
700 1 $aCHINO, D. Y. T.
700 1 $aROMANI, L. A. S.
700 1 $aGONÇALVES, R. R. V.
700 1 $aTRAINA, A. J. M.
700 1 $aSOUSA, E. P. M.
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