| |
|
|
 | Acesso ao texto completo restrito à biblioteca da Embrapa Agricultura Digital. Para informações adicionais entre em contato com cnptia.biblioteca@embrapa.br. |
|
Registro Completo |
|
Biblioteca(s): |
Embrapa Agricultura Digital. |
|
Data corrente: |
10/08/2009 |
|
Data da última atualização: |
15/01/2020 |
|
Tipo da produção científica: |
Artigo em Anais de Congresso / Nota Técnica |
|
Autoria: |
ROMANI, L. A. S.; ZULLO JÚNIOR, J.; NASCIMENTO, C. R.; GONÇALVES, R. R. V.; TRAINA, C; TRAINA, A. J. M. |
|
Afiliação: |
LUCIANA ALVIM SANTOS ROMANI, CNPTIA; JURANDIR ZULLO JÚNIOR, CEPAGRI/UNICAMP; C. R. NASCIMENTO, FEAGRI/UNICAMP; R. R. V. GONÇALVES, FEAGRI/UNICAMP; C. TRAINA, ICMC/USP; A. J. M. TRAINA, ICMC/USP. |
|
Título: |
Monitoring sugar cane crops through DTW-based method for similarity search in NDVI time series. |
|
Ano de publicação: |
2009 |
|
Fonte/Imprenta: |
In: INTERNATIONAL WORKSHOP ON THE ANALYSIS OF MULTI-TEMPORAL REMOTE SENSING IMAGES, 5., 2009, Groton, Connecticut. Proceedings... Storrs: UConn, 2009. |
|
Páginas: |
p. 171-178. |
|
Idioma: |
Inglês |
|
Notas: |
MultiTemp 2009. |
|
Conteúdo: |
Brazil is an important sugar cane producer, which is the main resource for ethanol production, a renewable source of energy. Due to the strategical importance of this agricultural commodity, it is necessary to improve models that assist the crops monitoring process. Recently, remote sensing images have also been used to crops monitoring. Vegetation index images obtained by operations between satellite channels, for instance, can be taken over a season, showing the development of crops. Specialists in agrometeorology need methods which aim at understanding and mining these datasets to discover interesting patterns and knowledge. Accordingly, this paper presents a methodology to analyze NDVI time series using a distance function based on dynamic time warping distance (DTW) to perform similarity search. The experiments were done for NDVI multi-temporal images from seven harvests regarding the period from April/2001 to March/2008. NDVI time series was generated from NOAA-AVHRR images of a relevant sugar cane producer region in Brazil. Two different distance functions were compared and DTW reached better results than Euclidean distance. The proposed method allowed comparing harvests in different regions and in the same time series. Results of similarity search on NDVI time series demonstrate the efficacy of the use of distance function to similarity search in remote sensing data. This approach is appropriate to assess patterns in a long time series of multi-temporal images and can assist in the process of decision making by agricultural entrepreneurs. MenosBrazil is an important sugar cane producer, which is the main resource for ethanol production, a renewable source of energy. Due to the strategical importance of this agricultural commodity, it is necessary to improve models that assist the crops monitoring process. Recently, remote sensing images have also been used to crops monitoring. Vegetation index images obtained by operations between satellite channels, for instance, can be taken over a season, showing the development of crops. Specialists in agrometeorology need methods which aim at understanding and mining these datasets to discover interesting patterns and knowledge. Accordingly, this paper presents a methodology to analyze NDVI time series using a distance function based on dynamic time warping distance (DTW) to perform similarity search. The experiments were done for NDVI multi-temporal images from seven harvests regarding the period from April/2001 to March/2008. NDVI time series was generated from NOAA-AVHRR images of a relevant sugar cane producer region in Brazil. Two different distance functions were compared and DTW reached better results than Euclidean distance. The proposed method allowed comparing harvests in different regions and in the same time series. Results of similarity search on NDVI time series demonstrate the efficacy of the use of distance function to similarity search in remote sensing data. This approach is appropriate to assess patterns in a long time series of multi-temporal images and ca... Mostrar Tudo |
|
Palavras-Chave: |
Agrometeorologia; Imagens multitemporais de NDVI; Imagens NOAA-AVHRR. |
|
Thesagro: |
Agricultura; Cana de açúcar; Sensoriamento remoto. |
|
Thesaurus Nal: |
Agrometeorology; Remote sensing; Sugarcane. |
|
Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
|
Marc: |
LEADER 02571nam a2200301 a 4500
001 1256605
005 2020-01-15
008 2009 bl uuuu u00u1 u #d
100 1 $aROMANI, L. A. S.
245 $aMonitoring sugar cane crops through DTW-based method for similarity search in NDVI time series.$h[electronic resource]
260 $aIn: INTERNATIONAL WORKSHOP ON THE ANALYSIS OF MULTI-TEMPORAL REMOTE SENSING IMAGES, 5., 2009, Groton, Connecticut. Proceedings... Storrs: UConn$c2009
300 $ap. 171-178.
500 $aMultiTemp 2009.
520 $aBrazil is an important sugar cane producer, which is the main resource for ethanol production, a renewable source of energy. Due to the strategical importance of this agricultural commodity, it is necessary to improve models that assist the crops monitoring process. Recently, remote sensing images have also been used to crops monitoring. Vegetation index images obtained by operations between satellite channels, for instance, can be taken over a season, showing the development of crops. Specialists in agrometeorology need methods which aim at understanding and mining these datasets to discover interesting patterns and knowledge. Accordingly, this paper presents a methodology to analyze NDVI time series using a distance function based on dynamic time warping distance (DTW) to perform similarity search. The experiments were done for NDVI multi-temporal images from seven harvests regarding the period from April/2001 to March/2008. NDVI time series was generated from NOAA-AVHRR images of a relevant sugar cane producer region in Brazil. Two different distance functions were compared and DTW reached better results than Euclidean distance. The proposed method allowed comparing harvests in different regions and in the same time series. Results of similarity search on NDVI time series demonstrate the efficacy of the use of distance function to similarity search in remote sensing data. This approach is appropriate to assess patterns in a long time series of multi-temporal images and can assist in the process of decision making by agricultural entrepreneurs.
650 $aAgrometeorology
650 $aRemote sensing
650 $aSugarcane
650 $aAgricultura
650 $aCana de açúcar
650 $aSensoriamento remoto
653 $aAgrometeorologia
653 $aImagens multitemporais de NDVI
653 $aImagens NOAA-AVHRR
700 1 $aZULLO JÚNIOR, J.
700 1 $aNASCIMENTO, C. R.
700 1 $aGONÇALVES, R. R. V.
700 1 $aTRAINA, C
700 1 $aTRAINA, A. J. M.
Download
Esconder MarcMostrar Marc Completo |
|
Registro original: |
Embrapa Agricultura Digital (CNPTIA) |
|
|
Biblioteca |
ID |
Origem |
Tipo/Formato |
Classificação |
Cutter |
Registro |
Volume |
Status |
URL |
Voltar
|
|
|
| Registros recuperados : 41 | |
| 4. |  | PANIAGO, C. F. A.; TRAINA, A. J. M. Um sistema de compressão de imagens digitais. In: WORKSHOP DE DISSERTAÇÕES DEFENDIDAS EM CIÊNCIAS DE COMPUTAÇÃO E MATEMÁTICA OPERACIONAL; SEMANA COMEMORATIVA DOS 20 ANOS DA PÓS-GRADUAÇÃO EM CIÊNCIAS DE COMPUTAÇÃO E MATEMÁTICA COMPUTACIONAL, 1995, São Carlos. Anais... São Carlos: USP-ICMSC, 1995. p. 179-192. folhas avulsas| Tipo: Artigo em Anais de Congresso |
| Biblioteca(s): Embrapa Territorial. |
|    |
| 12. | | GONÇALVES, R. R. V.; ZULLO JÚNIOR, J.; ROMANI, L. A. S.; NASCIMENTO, C. R.; TRAINA, A. J. M. Analysis of NDVI time series using cross-correlation and forecasting methods for monitoring sugarcane fields in Brazil. International Journal of Remote Sensing, Basingstoke, v. 33, n. 15, p. 4653-4672, Aug. 2012.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 2 |
| Biblioteca(s): Embrapa Agricultura Digital. |
|  |
| 14. | | ROMANI, L. A. S.; ZULLO JÚNIOR, J.; NASCIMENTO, C. R.; GONÇALVES, R. R. V.; TRAINA, C; TRAINA, A. J. M. Monitoring sugar cane crops through DTW-based method for similarity search in NDVI time series. In: INTERNATIONAL WORKSHOP ON THE ANALYSIS OF MULTI-TEMPORAL REMOTE SENSING IMAGES, 5., 2009, Groton, Connecticut. Proceedings... Storrs: UConn, 2009. p. 171-178. MultiTemp 2009.| Tipo: Artigo em Anais de Congresso / Nota Técnica |
| Biblioteca(s): Embrapa Agricultura Digital. |
| |
| 17. | | 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.| Tipo: Artigo em Anais de Congresso |
| Biblioteca(s): Embrapa Agricultura Digital. |
| |
| 19. | | 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.| Tipo: Artigo em Anais de Congresso |
| Biblioteca(s): Embrapa Agricultura Digital. |
| |
| 20. | | NUNES, S. A.; AVILA, A. M. H.; ROMANI, L. A. S.; TRAINA, A. J. M.; COLTRI, P. P.; SOUSA, E. P. M. To be or not to be real: fractal analysis of data streams from a regional climate change model. In: Annual ACM Symposium on Applied Computing, 27., 2012, 2, Riva del Garda. Proceedings... New York: ACM, 2012. p. 831-832. SAC '12.| Tipo: Resumo em Anais de Congresso |
| Biblioteca(s): Embrapa Agricultura Digital. |
| |
| Registros recuperados : 41 | |
|
| Nenhum registro encontrado para a expressão de busca informada. |
|
|
