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| Registros recuperados : 186 | |
| 9. |  | LEIVAS, J. F.; TEIXEIRA, A. H. de C.; SILVA, G. B. S. da. Aplicação de modelo agrometeorológico espectral no perímetro irrigado da bacia do São Francisco, utilizando imagens RAPIDEYE. In: SIMPÓSIO DA BACIA HIDROGRÁFICA DO RIO SÃO FRANCISCO, 1., 2016, Juazeiro, BA; Petrolina, PE. Anais... Juazeiro; Petrolina: CBHSF, 2016. 7 p.| Biblioteca(s): Embrapa Territorial. |
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| 12. | | SILVA, G. B. S. da; FORMAGGIO, A. R.; SHIMABUKURO, Y. E.; ADAMI, M.; SANO, E. E. Discriminação da cobertura vegetal do Cerrado matogrossense por meio de imagens MODIS. Pesquisa Agropecuária Brasileira, Brasília, DF, v. 45, n. 2, p. 186-194, fev. 2010 Título em inglês: Discrimination of Cerrado vegetation cover in the state of Mato Grosso using MODIS images.| Biblioteca(s): Embrapa Unidades Centrais. |
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| 15. | | TRABAQUINI, K.; SILVA, G. B. S. da; FORMAGGIO, A. R.; SHIMABUKURO, Y. E.; GALVÃO, L. S. Dynamics and distribution of anthropic occupation in the Cerrado of Mato Grosso in the period from 1990 to 2008. Geografia, Rio Claro, v. 38, n. 2, p. 209-224, maio/ago. 2013. p. 209-224| Biblioteca(s): Embrapa Territorial. |
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| Registros recuperados : 186 | |
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Registro Completo
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Biblioteca(s): |
Embrapa Meio Ambiente; Embrapa Pecuária Sudeste. |
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Data corrente: |
29/07/2020 |
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Data da última atualização: |
30/07/2020 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 1 |
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Autoria: |
CISNEROS, A.; FIORIO, P. R.; SANTOS, P. M.; PASQUALOTTO, N.; WITTENBERGHE, S. van; SILVA, G. B. S. da; NOGUEIRA, S. F. |
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Afiliação: |
AMPARO CISNEROS, ESALQ-USP; PETERSON FIORIO, ESALQ-USP; PATRICIA MENEZES SANTOS, CPPSE; NIEVES PASQUALOTTO, Universidad de Valencia; SHARI VAN WITTENBERGHE, Universidad de Valencia; GUSTAVO BAYMA SIQUEIRA DA SILVA, CNPMA; SANDRA FURLAN NOGUEIRA, CNPMA. |
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Título: |
Mapping productivity and essential biophysical parameters of cultivated tropical grasslands from sentinel-2 imagery. |
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Ano de publicação: |
2020 |
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Fonte/Imprenta: |
Agronomy, v. 10, n. 5, p. 1-23, 2020. Article 711. |
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Páginas: |
p. 1-23. |
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DOI: |
https://doi.org/10.3390/agronomy10050711 |
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Idioma: |
Inglês |
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Conteúdo: |
Abstract: Nitrogen (N) is the main nutrient element that maintains productivity in forages; it is inextricably linked to dry matter increase and plant support capacity. In recent years, high spectral and spatial resolution remote sensors, e.g., the European Space Agency (ESA)?s Sentinel satellite missions, have become freely available for agricultural science, and have proven to be powerful monitoring tools. The use of vegetation indices has been essential for crop monitoring and biomass estimation models. The objective of this work is to test and demonstrate the applicability of different vegetation indices to estimate the biomass productivity, the foliar nitrogen content (FNC), the plant height and the leaf area index (LAI) of several tropical grasslands species submitted to different nitrogen (N) rates in an experimental area of São Paulo, Brazil. Field reflectance data of Panicum maximum and Urochloa brizantha species' cultivars were taken and convoluted to the Sentinel-2 satellite bands. Subsequently, different vegetation indices (Normalized Difference Vegetation Index (NDI), Three Band Index (TBI), Difference light Height (DLH), Three Band Dall?Olmo (DO), and Normalized Area Over reflectance Curve (NAOC)) were tested for the experimental grassland areas, and composed of Urochloa decumbens and Urochloa brizantha grass species, which were sampled and destructively analyzed. Our results show the use of different relevant Sentinel-2 bands in the visible (VIS)-near infrared (NIR) regions for the estimation of the different biophysical parameters. The FNC obtained the best correlation for the TBI index combining blue, green and red bands with a determination coefficient (R2) of 0.38 and Root Mean Square Error (RMSE) of 3.4 g kg-1. The estimation of grassland productivity based on red-edge and NIR bands showed a R2 = 0.54 and a RMSE = 1800 kg ha-1. For the LAI, the best index was the NAOC (R2 = 0.57 and RMSE = 1.4 m2 m-2). High values of FNC, productivity and LAI based on different sets of Sentinel-2 bands were consistently obtained for areas under N fertilization. MenosAbstract: Nitrogen (N) is the main nutrient element that maintains productivity in forages; it is inextricably linked to dry matter increase and plant support capacity. In recent years, high spectral and spatial resolution remote sensors, e.g., the European Space Agency (ESA)?s Sentinel satellite missions, have become freely available for agricultural science, and have proven to be powerful monitoring tools. The use of vegetation indices has been essential for crop monitoring and biomass estimation models. The objective of this work is to test and demonstrate the applicability of different vegetation indices to estimate the biomass productivity, the foliar nitrogen content (FNC), the plant height and the leaf area index (LAI) of several tropical grasslands species submitted to different nitrogen (N) rates in an experimental area of São Paulo, Brazil. Field reflectance data of Panicum maximum and Urochloa brizantha species' cultivars were taken and convoluted to the Sentinel-2 satellite bands. Subsequently, different vegetation indices (Normalized Difference Vegetation Index (NDI), Three Band Index (TBI), Difference light Height (DLH), Three Band Dall?Olmo (DO), and Normalized Area Over reflectance Curve (NAOC)) were tested for the experimental grassland areas, and composed of Urochloa decumbens and Urochloa brizantha grass species, which were sampled and destructively analyzed. Our results show the use of different relevant Sentinel-2 bands in the visible (VIS)-near infrared... Mostrar Tudo |
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Palavras-Chave: |
Productivity; Sentinel-2. |
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Thesagro: |
Biomassa; Capim Urochloa; Nitrogênio; Pastagem; Sensoriamento Remoto. |
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Thesaurus NAL: |
Biomass production; Leaf area index; Nitrogen; Panicum; Pastures; Remote sensing; Tropical grasslands; Urochloa brizantha; Urochloa decumbens; Vegetation index. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/215015/1/MappingProductivityEssential.pdf
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Marc: |
LEADER 03309naa a2200421 a 4500
001 2124094
005 2020-07-30
008 2020 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.3390/agronomy10050711$2DOI
100 1 $aCISNEROS, A.
245 $aMapping productivity and essential biophysical parameters of cultivated tropical grasslands from sentinel-2 imagery.$h[electronic resource]
260 $c2020
300 $ap. 1-23.
520 $aAbstract: Nitrogen (N) is the main nutrient element that maintains productivity in forages; it is inextricably linked to dry matter increase and plant support capacity. In recent years, high spectral and spatial resolution remote sensors, e.g., the European Space Agency (ESA)?s Sentinel satellite missions, have become freely available for agricultural science, and have proven to be powerful monitoring tools. The use of vegetation indices has been essential for crop monitoring and biomass estimation models. The objective of this work is to test and demonstrate the applicability of different vegetation indices to estimate the biomass productivity, the foliar nitrogen content (FNC), the plant height and the leaf area index (LAI) of several tropical grasslands species submitted to different nitrogen (N) rates in an experimental area of São Paulo, Brazil. Field reflectance data of Panicum maximum and Urochloa brizantha species' cultivars were taken and convoluted to the Sentinel-2 satellite bands. Subsequently, different vegetation indices (Normalized Difference Vegetation Index (NDI), Three Band Index (TBI), Difference light Height (DLH), Three Band Dall?Olmo (DO), and Normalized Area Over reflectance Curve (NAOC)) were tested for the experimental grassland areas, and composed of Urochloa decumbens and Urochloa brizantha grass species, which were sampled and destructively analyzed. Our results show the use of different relevant Sentinel-2 bands in the visible (VIS)-near infrared (NIR) regions for the estimation of the different biophysical parameters. The FNC obtained the best correlation for the TBI index combining blue, green and red bands with a determination coefficient (R2) of 0.38 and Root Mean Square Error (RMSE) of 3.4 g kg-1. The estimation of grassland productivity based on red-edge and NIR bands showed a R2 = 0.54 and a RMSE = 1800 kg ha-1. For the LAI, the best index was the NAOC (R2 = 0.57 and RMSE = 1.4 m2 m-2). High values of FNC, productivity and LAI based on different sets of Sentinel-2 bands were consistently obtained for areas under N fertilization.
650 $aBiomass production
650 $aLeaf area index
650 $aNitrogen
650 $aPanicum
650 $aPastures
650 $aRemote sensing
650 $aTropical grasslands
650 $aUrochloa brizantha
650 $aUrochloa decumbens
650 $aVegetation index
650 $aBiomassa
650 $aCapim Urochloa
650 $aNitrogênio
650 $aPastagem
650 $aSensoriamento Remoto
653 $aProductivity
653 $aSentinel-2
700 1 $aFIORIO, P. R.
700 1 $aSANTOS, P. M.
700 1 $aPASQUALOTTO, N.
700 1 $aWITTENBERGHE, S. van
700 1 $aSILVA, G. B. S. da
700 1 $aNOGUEIRA, S. F.
773 $tAgronomy$gv. 10, n. 5, p. 1-23, 2020. Article 711.
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Embrapa Pecuária Sudeste (CPPSE) |
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