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| Registros recuperados : 117 | |
| 42. |  | BRANDÃO, Z. N.; CARNEIRO, F. C.; SILVA JUNIOR, C. A. da; SHIRATSUCHI, L. S. Desenvolvimento de técnica para aplicação de desfolhante em taxa variável no algodoeiro. In: SILVA-MATOS, R. R. S. da; DOIHARA, I. P.; LINHARES, S. C. (org.). Medio ambiente: Agricultura, desarrollo y sustentabilidad 2. Ponta Grossa, PR: Atena, 2023. c. 2. p. 10-20.| Biblioteca(s): Embrapa Algodão. |
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| 44. | | ZONTA, J. H.; BRANDÃO, Z. N.; RODRIGUES, J. I. S.; BRAUN, H.; SOFIATTI, V. Avaliação da qualidade da fibra do algodoeiro irrigado sob estresse hídrico. In: SILVA-MATOS, R. R. S. da; MORAES, L. F.; SILVA, F. L. de S. (org.). Desenvolvimento da pesquisa científica, tecnologia e inovação na agronomia 3. Ponta Grossa: Atena, 2022. cap. 4, p. 38-51. 234 p.| Biblioteca(s): Embrapa Algodão. |
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| 47. | | BRANDAO, Z. N.; SOFIATTI, V.; BEZERRA, J. R. C.; FERREIRA, G. B. Estimativa da produtividade do algodoeiro através de imagens de satélite. In: CONGRESSO BRASILEIRO DO ALGODÃO, 8.; COTTON EXPO, 1., 2011, São Paulo. Evolução da cadeia para construção de um setor forte: Anais. Campina Grande, PB: Embrapa Algodão, 2011. p.1602-1609| Biblioteca(s): Embrapa Algodão. |
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| 48. | | BRANDAO, Z. N.; ZONTA, J. H.; MEDEIROS, J. da C.; SANA, R. S.; FERREIRA, G. B. Condutividade elétrica aparente e sua correlação com o pH em solos no cerrado de Goiás. In: INAMASU, R. Y.; NAIME, J. de M.; RESENDE A. V. de; BASSOI, L. H. BERNARDI, A. C. de C. (Ed.). Agricultura de precisão: um novo olhar. São Carlos : Embrapa Instrumentação, 2011. p. 162-167| Biblioteca(s): Embrapa Algodão. |
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| 49. | | BRANDAO, Z. N.; SOFIATTI, V.; BEZERRA, J. R. C.; FERREIRA, G. B.; MEDEIROS, J. da C. Macronutrientes no tecido foliar de plantas de algodão em diferentes estádios fenológicos. In: CONGRESSO BRASILEIRO DO ALGODÃO, 8.; COTTON EXPO, 1., 2011, São Paulo. Evolução da cadeia para construção de um setor forte: Anais. Campina Grande, PB: Embrapa Algodão, 2011. p.1618-1625| Biblioteca(s): Embrapa Algodão. |
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| 50. | | BRANDAO, Z. N.; GREGO, C. R.; JORGE, L. A. de C.; MANJOLIN, R. C. Multispectral reflectance and geostatistic methods to estimate leaf nitrogen content and cotton yield. In: SILVA-MATOS, R. R. S. da; MORAES, L. F.; SILVA, F. L. de S. (org.). Desenvolvimento da pesquisa científica, tecnologia e inovação na agronomia 3. Ponta Grossa: Atena, 2022. cap. 14, p. 143-154.| Biblioteca(s): Embrapa Agricultura Digital; Embrapa Algodão; Embrapa Instrumentação. |
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| 52. | | GONDIM, T. M. de S.; ARAÚJO, J. B. de; BRANDÃO, Z. N.; MEDEIROS, E. P. de. Prospecção de genótipos de agave para obtenção de suco para bioinseticida. In: SILVA-MATOS, R. R. S. da; MORAES, L. F.; SILVA, F. L. de S. (org.). Desenvolvimento da pesquisa científica, tecnologia e inovação na agronomia 3. Ponta Grossa: Atena, 2022. cap. 12, p. 129-137. 234 p.| Biblioteca(s): Embrapa Algodão. |
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| 54. | | BRANDAO, Z. N.; SOFIATTI, V.; BEZERRA, J. R. C.; BEZERRA, B. G.; ZONTA, J. H. Uso do sensoriamento remoto na estimativa da necessidade hídrica do algodoeiro. In: CONGRESSO BRASILEIRO DO ALGODÃO, 8.; COTTON EXPO, 1., 2011, São Paulo. Evolução da cadeia para construção de um setor forte: Anais. Campina Grande, PB: Embrapa Algodão, 2011. p.1725-1734| Biblioteca(s): Embrapa Algodão. |
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| 58. | | ZONTA, J. H.; BEZERRA, J. R. C.; SOFIATTI, V.; BRANDAO, Z. N. Yield of cotton cultivars under different irrigation depths in the Brazilian semi-arid region. Revista Brasileira de Engenharia Agrícola e Ambiental, Campina Grande, PB, v. 19, n. 8, p.748-754, 2015.| Biblioteca(s): Embrapa Algodão. |
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| 59. | | MEGNA, P. R.; SANTOS, F. D.; BRANDAO, Z. N.; ZONTA, J. H. Zoneamento agrícola de risco climático do município de São João do Cariri-PB através de sistema de informação geográfica. In: FURTADO, D. A.; BARACUHY, J. G. DE V.; FRANCISCO, P. R. M.; FERNANES NETO, S.; SOUSA, V. A. DE (Org.). Tecnologias adaptadas para o desenvolvimento sustentável do semiárido brasileiro. Campina Grande: EPGRAF, 2014. cap. 21| Biblioteca(s): Embrapa Algodão. |
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| Registros recuperados : 117 | |
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Registro Completo
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Biblioteca(s): |
Embrapa Territorial. |
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Data corrente: |
02/12/2014 |
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Data da última atualização: |
02/12/2014 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
B - 1 |
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Autoria: |
BRANDAO, Z. N.; GREGO, C. R.; INAMASU, R. Y.; JORGE, L. A. de C. |
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Afiliação: |
ZIANY NEIVA BRANDAO, CNPA; CELIA REGINA GREGO, CNPM; RICARDO YASSUSHI INAMASU, CNPDIA; LUCIO ANDRE DE CASTRO JORGE, CNPDIA. |
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Título: |
Spectral reflectance of satellite images using geostatistics methods to estimate growth and cotton yield. |
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Ano de publicação: |
2014 |
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Fonte/Imprenta: |
Proceedings of SPIE, v. 9239, p. 923920-1 - 923920-8, 2014. |
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ISBN: |
0277-786X |
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DOI: |
10.1117/12.2067257 |
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Idioma: |
Inglês |
|
Notas: |
Presented at the 16th Remote Sensing for Agriculture, Ecosystems, and Hydrology. |
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Conteúdo: |
The objective of this study was the spatial identification of the NDVI index and cotton yield distributions through different crop phenological stages using geostatistical methods in Goiás state, Brazil. The experiment was carried out in a commercial field with 47.4 ha, in 80x80m georeferenced grid with 74 plots. Yield monitor data and multispectral satellite images at 56 m spatial resolution were collected in a rainfed cotton field in two dates to monitor the plant vigor. Satellite images of AWiFS sensor were acquired on 08/02/2011 and 01/04/2011, during the first flowering and fruiting cotton stages, respectively, corresponding to 70 and 120DAE (days after emergence). Measures of canopy reflectance, plant height and leaf nitrogen content were determined and cotton yield was obtained by mechanical harvest in August, 2011. Data were analyzed using descriptive statistics, correlation and geostatistical analyses by building and setting semivariograms and kriging interpolation. Best correlation was found between NDVI and cotton yield at 120DAE. At first flowering, the NDVI and cotton yield showed strong spatial dependence, while for 120DAE there was no dependence, probably due to the enlargement of vegetated coverage. There were similarities in the bottom left of the study area with high values of NDVI, as well as the highest values of cotton yield due to excellent plant vigor in the cotton flowering stage. Identifications of spatial differences were possible using geostatistical methods with remote sensing data obtained from medium resolution satellite images, allowing to identify distinct stages of plant growth and also to predict the cotton yield. MenosThe objective of this study was the spatial identification of the NDVI index and cotton yield distributions through different crop phenological stages using geostatistical methods in Goiás state, Brazil. The experiment was carried out in a commercial field with 47.4 ha, in 80x80m georeferenced grid with 74 plots. Yield monitor data and multispectral satellite images at 56 m spatial resolution were collected in a rainfed cotton field in two dates to monitor the plant vigor. Satellite images of AWiFS sensor were acquired on 08/02/2011 and 01/04/2011, during the first flowering and fruiting cotton stages, respectively, corresponding to 70 and 120DAE (days after emergence). Measures of canopy reflectance, plant height and leaf nitrogen content were determined and cotton yield was obtained by mechanical harvest in August, 2011. Data were analyzed using descriptive statistics, correlation and geostatistical analyses by building and setting semivariograms and kriging interpolation. Best correlation was found between NDVI and cotton yield at 120DAE. At first flowering, the NDVI and cotton yield showed strong spatial dependence, while for 120DAE there was no dependence, probably due to the enlargement of vegetated coverage. There were similarities in the bottom left of the study area with high values of NDVI, as well as the highest values of cotton yield due to excellent plant vigor in the cotton flowering stage. Identifications of spatial differences were possible using geostatistic... Mostrar Tudo |
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Palavras-Chave: |
Geostatistical analyses. |
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Thesaurus NAL: |
Normalized difference vegetation index; Precision agriculture. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/112770/1/4199.pdf
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Marc: |
LEADER 02479naa a2200229 a 4500
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022 $a0277-786X
024 7 $a10.1117/12.2067257$2DOI
100 1 $aBRANDAO, Z. N.
245 $aSpectral reflectance of satellite images using geostatistics methods to estimate growth and cotton yield.$h[electronic resource]
260 $c2014
500 $aPresented at the 16th Remote Sensing for Agriculture, Ecosystems, and Hydrology.
520 $aThe objective of this study was the spatial identification of the NDVI index and cotton yield distributions through different crop phenological stages using geostatistical methods in Goiás state, Brazil. The experiment was carried out in a commercial field with 47.4 ha, in 80x80m georeferenced grid with 74 plots. Yield monitor data and multispectral satellite images at 56 m spatial resolution were collected in a rainfed cotton field in two dates to monitor the plant vigor. Satellite images of AWiFS sensor were acquired on 08/02/2011 and 01/04/2011, during the first flowering and fruiting cotton stages, respectively, corresponding to 70 and 120DAE (days after emergence). Measures of canopy reflectance, plant height and leaf nitrogen content were determined and cotton yield was obtained by mechanical harvest in August, 2011. Data were analyzed using descriptive statistics, correlation and geostatistical analyses by building and setting semivariograms and kriging interpolation. Best correlation was found between NDVI and cotton yield at 120DAE. At first flowering, the NDVI and cotton yield showed strong spatial dependence, while for 120DAE there was no dependence, probably due to the enlargement of vegetated coverage. There were similarities in the bottom left of the study area with high values of NDVI, as well as the highest values of cotton yield due to excellent plant vigor in the cotton flowering stage. Identifications of spatial differences were possible using geostatistical methods with remote sensing data obtained from medium resolution satellite images, allowing to identify distinct stages of plant growth and also to predict the cotton yield.
650 $aNormalized difference vegetation index
650 $aPrecision agriculture
653 $aGeostatistical analyses
700 1 $aGREGO, C. R.
700 1 $aINAMASU, R. Y.
700 1 $aJORGE, L. A. de C.
773 $tProceedings of SPIE$gv. 9239, p. 923920-1 - 923920-8, 2014.
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