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Registros recuperados: 47 | |
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BECKER, W. R.; RICHETTI, J.; MERCANTE, E.; ESQUERDO, J. C. D. M.; SILVA JUNIOR, C. A. da; PALUDO, A.; JOHANN, J. A.. |
Abstract. Knowledge of the agricultural calendar of crops is essential to better estimate and forecast the cultivation of large-scale crops. The aim of this study was to estimate sowing date (SD), date of maximum vegetative development (DMVD), and harvest date (HD) of soybean and corn in the state of Paraná, Brazil. Dates from 120 farms and the Enhanced Vegetation Index (EVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS) from 2011 to 2014 were used into a seasonal trend analysis to obtain soybean and corn seasonal patterns. The results indicate that the majority soybean is sown during October and the DMVD occurs between the second ten-day period of December and the first ten-day period of January. Owing to the spatial variability of the... |
Tipo: Artigo de periódico |
Palavras-chave: Índice de vegetação melhorado; Índice de Vegetação Aprimorado; Data de Colheita; Data de Semeadura; Enhanced Vegetation Index; Timesat; Soja; Milho; Vegetation index; Soybeans; Corn; Sowing date; Harvest date. |
Ano: 2020 |
URL: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1126956 |
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Perea,Alberto Jesús; Meroño,José Emilio; Aguilera,María Jesús. |
The objective of this paper was the development of a methodology for the classification of digital aerial images, which, with the aid of object-based classification and the Normalized Difference Vegetation Index (NDVI), can quantify agricultural areas, by using algorithms of expert classification, with the aim of improving the final results of thematic classifications. QuickBird satellite images and data of 2532 plots in Hinojosa del Duque, Spain, were used to validate the different classifications, obtaining an overall classification accuracy of 91.9% and an excellent Kappa statistic (87.6%) for the algorithm of expert classification. |
Tipo: Journal article |
Palavras-chave: Expert classification; Vegetation index; Land cover; Object-based classification. |
Ano: 2009 |
URL: http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-58392009000300013 |
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Damian,Júnior Melo; Pias,Osmar Henrique de Castro; Cherubin,Maurício Roberto; Fonseca,Alencar Zachi da; Fornari,Ezequiel Zibetti; Santi,Antônio Luis. |
ABSTRACT: The utilization of Normalized Difference Vegetation Index (NDVI) data obtained through satellite images can technically improve the process of delimiting management zones (MZ) for annual crops, resulting in socio-economic and environmental benefits. The aim of this study was to compare delimited MZ, using crop productivity data, with delimited MZ using the NDVI obtained from satellite images in areas under a no-tillage system. The study was carried out in three areas located in the state of Rio Grande do Sul, Brazil. Three crop productivity maps, from 2009 to 2015, were used for each area, whereby the NDVI was calculated for each crop productivity map using images from the Landsat series of satellites. Descriptive and geostatistical analysis were... |
Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Fuzzy c-means clustering; Productivity data; Aerial images; Vegetation index. |
Ano: 2020 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162020000100101 |
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ANDRADE, R. G.; HOTT, M. C.; MAGALHAES JUNIOR, W. C. P. de; PACIULLO, D. S. C.; GOMIDE, C. A. de M.. |
Traditional procedures for biomass estimation usually use destructive methods with great demands on time, resources, and labor. The development of models for automated estimation of pasture biomass, particularly from images captured by Unmanned Aerial Vehicle (UAV), in addition to high spatiotemporal resolution combined with flexibility in image acquisition, provides agility, the economy of resources, and labor. The objective of this work was to establish a technical feasibility study for the use of multispectral sensors onboard an Unmanned Aerial Vehicle (UAV) to estimate the vigor classes of Brachiaria ruziziensis pastures. For this purpose, imaging cameras in the visible (RGB), near-infrared and red edge ranges were used for continuous monitoring of 20... |
Tipo: Artigo de periódico |
Palavras-chave: Índice de vegetação; UAV; Forragem; Sensoriamento Remoto; Forage; Remote sensing; Vegetation index. |
Ano: 2021 |
URL: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1138479 |
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Carvalho,Daniel C. De; Pessoa,Mayara M. De L.; Pereira,Marcos G.; Delgado,Rafael C.. |
ABSTRACT This study aimed to assess vegetal cover evolution on a river island within the Ecological Station of (EEP), by remote sensing. For this purpose, Normalized Difference Vegetation Indexes were generated for Landsat 1 (1973) and Landsat 5 (1984, 1990, 2000 and 2011) images. Five landscape units were identified in the field: bare soil, Rough savanna, Typical savanna, Forested savanna and Evergreen dry woods. Only Forested savanna and Evergreen dry woods showed poor spectral splitting, being thus considered as a forestry complex. Changes throughout time have occurred in all units, with decreasing in bare soil areas (-2.56 ha year−1), Rough savanna (-0.66 ha year−1) and Typical savanna (-0.94 ha year−1) and with an increase in the Forested savanna... |
Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Remote sensing; Environmental monitoring; Vegetation index. |
Ano: 2016 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162016000601186 |
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JUNGES, A. H.; PAULETO, H.; HOFF, R.; DUCATI, J. R.; ALBERI, R.. |
O objetivo deste trabalho foi empregar imagens Landsat na definição do perfil temporal médio de NDVI de vinhedo da região da CampanhaGaúcha. Para isso, foi avaliada a disponibilidade de imagens NDVI/Landsat8-OLIsem presença de nuvens na área de estudo (vinhedo comercial de ?Cabernet Sauvignon?), de julho de 2013 a julho de 2018, para extração de valoresmédios de NDVI e elaboração do perfil temporal médio. Os resultados indicaram que primavera foi a estação com menor disponibilidade média de imagens NDVI/Landsat sempresença de nuvens. O perfil médio de NDVI foi coerente com a evolução temporal da biomassa verde em vinhedos, refletindo o ciclo vegetativo e operíodo de repouso hibernal dasvideiras, quando oíndice pode ser associado à vegetação de cobertura... |
Tipo: Anais e Proceedings de eventos |
Palavras-chave: Cabernet Sauvignon; Índice de vegetação; Viticultura; Vegetation index; Viticulture. |
Ano: 2019 |
URL: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1116354 |
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CISNEROS, A.; FIORIO, P. R.; SANTOS, P. M.; PASQUALOTTO, N.; WITTENBERGHE, S. van; SILVA, G. B. S. da; NOGUEIRA, S. F.. |
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... |
Tipo: Artigo de periódico |
Palavras-chave: Productivity; Sentinel-2; Pastagem; Capim Urochloa; Biomassa; Nitrogênio; Sensoriamento Remoto; Leaf area index; Tropical grasslands; Pastures; Biomass production; Nitrogen; Remote sensing; Vegetation index; Urochloa brizantha; Urochloa decumbens; Panicum. |
Ano: 2020 |
URL: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1124094 |
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Registros recuperados: 47 | |
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