| |
|
|
| Registros recuperados : 6 | |
| 6. |  | SCRIVANI, R.; AMARAL, B. F. do; GONÇALVES, R. R. do V.; SOUSA, E. P. M. de; ZULLO JÚNIOR, J.; ROMANI, L. A. S. Identificação da mudança de uso da terra usando técnicas de agrupamento de séries temporais de imagens de satélite. In: SIMPÓSIO DE GEOTECNOLOGIAS NO PANTANAL, 5., 2014, Campo Grande, MS. Anais... São José dos Campos: INPE, 2014. p. 554-563. 1 CD-ROM. Geopantanal 2014.| Biblioteca(s): Embrapa Agricultura Digital. |
|    |
| Registros recuperados : 6 | |
|
|
|
 | 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: |
09/01/2019 |
|
Data da última atualização: |
07/01/2020 |
|
Tipo da produção científica: |
Artigo em Anais de Congresso |
|
Autoria: |
SCRIVANI, R.; ZULLO, J.; ROMANI, L. A. S. |
|
Afiliação: |
RACHEL SCRIVANI, Unicamp; JURANDIR ZULLO JUNIOR, Unicamp; LUCIANA ALVIM SANTOS ROMANI, CNPTIA. |
|
Título: |
SITS for estimating sugarcane production. |
|
Ano de publicação: |
2017 |
|
Fonte/Imprenta: |
In: INTERNATIONAL WORKSHOP ON THE ANALYSIS OF MULTITEMPORAL REMOTE SENSING IMAGES, 9., 2017, Brugge. Proceedings... Piscataway: IEEE, 2017. |
|
Páginas: |
4 p. |
|
DOI: |
10.1109/Multi-Temp.2017.8035254 |
|
Idioma: |
Inglês |
|
Conteúdo: |
Abstract - Given the global importance of sugarcane, its monitoring is strategic. There is a huge amount of agrometeorological and environmental data generated by satellites that can be used for this purpose bringing countless advantages, such as economy, agility and precision in the analysis. This paper analyses the utility of the time series of remote sensing data in the generation of numerical models for estimate the sugarcane production through multiple linear regression analysis using the variables NDVI / MODIS, WRSI and planted area. The study area was formed by seven municipalities in the state of São Paulo, Brazil, the first national sugarcane producers. The good models accuracy was shown by the correlation coefficient (R 2 ) above 0.94 for all generated models. We have identified that the time series of remote sensing data were useful for longer periods of data rather than each individual crop season considered. |
|
Palavras-Chave: |
Multiple Linear Regression; Numerical models; Séries temporais. |
|
Thesagro: |
Cana de Açúcar; Sensoriamento Remoto. |
|
Thesaurus NAL: |
Remote sensing; Sugarcane; Time series analysis. |
|
Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
|
Marc: |
LEADER 01746nam a2200253 a 4500
001 2103421
005 2020-01-07
008 2017 bl uuuu u00u1 u #d
024 7 $a10.1109/Multi-Temp.2017.8035254$2DOI
100 1 $aSCRIVANI, R.
245 $aSITS for estimating sugarcane production.$h[electronic resource]
260 $aIn: INTERNATIONAL WORKSHOP ON THE ANALYSIS OF MULTITEMPORAL REMOTE SENSING IMAGES, 9., 2017, Brugge. Proceedings... Piscataway: IEEE$c2017
300 $a4 p.
520 $aAbstract - Given the global importance of sugarcane, its monitoring is strategic. There is a huge amount of agrometeorological and environmental data generated by satellites that can be used for this purpose bringing countless advantages, such as economy, agility and precision in the analysis. This paper analyses the utility of the time series of remote sensing data in the generation of numerical models for estimate the sugarcane production through multiple linear regression analysis using the variables NDVI / MODIS, WRSI and planted area. The study area was formed by seven municipalities in the state of São Paulo, Brazil, the first national sugarcane producers. The good models accuracy was shown by the correlation coefficient (R 2 ) above 0.94 for all generated models. We have identified that the time series of remote sensing data were useful for longer periods of data rather than each individual crop season considered.
650 $aRemote sensing
650 $aSugarcane
650 $aTime series analysis
650 $aCana de Açúcar
650 $aSensoriamento Remoto
653 $aMultiple Linear Regression
653 $aNumerical models
653 $aSéries temporais
700 1 $aZULLO, J.
700 1 $aROMANI, L. A. S.
Download
Esconder MarcMostrar Marc Completo |
|
Registro original: |
Embrapa Agricultura Digital (CNPTIA) |
|
|
Biblioteca |
ID |
Origem |
Tipo/Formato |
Classificação |
Cutter |
Registro |
Volume |
Status |
Fechar
|
| Nenhum registro encontrado para a expressão de busca informada. |
|
|
