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| Picoli,Michelle Cristina Araujo; Duft,Daniel Garbellini; Machado,Pedro Gerber. |
| Abstract: The objective of this work was to evaluate the potential of several spectral indices, used on moderate resolution imaging spectroradiometer (Modis) images, in identifying drought events in sugarcane. Images of Terra and Aqua satellites were used to calculate the spectral indices, using visible (red), near infrared, and shortwave infrared bands, and eight indices were selected: NDVI, EVI2, GVMI, NDI6, NDI7, NDWI, SRWI, and MSI. The indices were calculated using images between October and April of the crop years 2007/08, 2008/09, 2009/10, and 2013/14. These indices were then correlated with the standardized precipitation-evapotranspiration index (SPEI), calculated for 1, 3, and 6 months. Four of them had significant correlations with SPEI: GVMI,... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Saccharum officinarum; Drought stress; Image processing; Satellite imagery; SPEI; Warning systems. |
| Ano: 2017 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-204X2017001101063 |
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| Johann,Jerry Adriani; Rocha,Jansle Vieira; Duft,Daniel Garbellini; Lamparelli,Rubens Augusto Camargo. |
| O objetivo deste trabalho foi estimar e mapear as áreas com as culturas de soja e milho, no Paraná, com uso de imagens multitemporais EVI/Modis. Foram avaliados os anos‑safra de 2004/2005 a 2007/2008. Em razão da alta dinâmica temporal e da heterogeneidade de datas de semeadura das culturas no estado, foram utilizadas cenas que contemplavam as fases de pré‑plantio e de desenvolvimento inicial das culturas, para gerar a imagem de mínimo EVI (IMIE), e cenas que consideravam o pico vegetativo das culturas, para gerar a imagem de máximo EVI (IMAE). Estas imagens foram utilizadas para gerar a composição colorida RGB (R, IMAE; GB, IMIE), o que permitiu a confecção de máscara das áreas com soja e milho. As estimativas das áreas de máscara por município foram... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Classificação de imagens; Distribuição espacial de culturas; Índice de vegetação; Mapeamento; Previsão de safras; Sensoriamento remoto. |
| Ano: 2012 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-204X2012000900015 |
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| Sanches,Guilherme Martineli; Paula,Maria Thereza Nonato de; Magalhães,Paulo Sérgio Graziano; Duft,Daniel Garbellini; Vitti,André César; Kolln,Oriel Tiago; Borges,Bernardo Melo Montes Nogueira; Franco,Henrique Coutinho Junqueira. |
| ABSTRACT: Sugarcane (saccharum spp.) in Brazil is managed on the basis of “production environments”. These “production environments” are used for many purposes, such as variety allocation, application of fertilizers and definition of the planting and harvesting periods. A quality classification is essential to ensure high economic returns. However, the classification is carried out by few and, most of the time, non-representative soil samples, showing unreal local conditions of soil spatial variability and resulting in classifications that are imprecise. One of the important tools in the precision agriculture technological package is the apparent electrical conductivity (ECa) sensors that can quickly map soil spatial variability with high-resolution and at... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Proximal soil sensors; Site-specific soil management; Soil apparent electrical conductivity; Precision agriculture technologies. |
| Ano: 2019 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162019000100010 |
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