Mapping and Separation of Summer Crops Soybean/Corn - Bueno Mafra, Joyce
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Brazil is one of the leaders in agricultural production, with one of the most prosperous grain productions on the planet and the capacity to define itself as the world's leading food producer. Monitoring agricultural crops, including soybeans and corn, is of great importance to the national economy, but also individually for each producer. This allows producers to make decisions about quantity and product to be sown, enabling them to plan the crop from sowing to harvest. Although the methodology used by official bodies is still widespread, the incorporation of new methods is important for…mehr

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Produktbeschreibung
Brazil is one of the leaders in agricultural production, with one of the most prosperous grain productions on the planet and the capacity to define itself as the world's leading food producer. Monitoring agricultural crops, including soybeans and corn, is of great importance to the national economy, but also individually for each producer. This allows producers to make decisions about quantity and product to be sown, enabling them to plan the crop from sowing to harvest. Although the methodology used by official bodies is still widespread, the incorporation of new methods is important for optimising the agricultural production data collection process. Thus, remote sensing presents itself as a tool with enormous potential, mainly because it is based on technologies that are relatively inexpensive for the end user, considering that the tools under study are images that are made available free of charge by the official institutions that own them, thus enabling data to be acquired without the need to send personnel to collect samples.
Autorenporträt
Graduated in Agricultural Engineering in 2016 from the State University of Western Paraná (UNIOESTE). She was part of the Applied Geostatistics Research Group (GGEA), where she was a scientific initiation scholarship holder and carried out research activities at the Applied Statistics Laboratory (LEA) in the area of remote sensing applied to agriculture.