Estimation of Infection Severity in Sugarcane Using Satellite Images
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Abstract
Brown rust (Puccinia melanocephala) contamination in sugarcane (Saccharum spp.) is a major problem because of the costs it imposes on growers. Based on a recent study using hyperspectral analysis at the laboratory level as well as multispectral analysis by unmanned aerial vehicle (UAV), this work undertook the task of estimating brown rust infection using multispectral images (MSI) from the Sentinel-2 satellite constellation. The results show a high agreement between the estimation by UAV, the one obtained by satellite images and the one observed in the field by a specialist. These results make it possible to extend the estimation of the infection of this disease to large areas, reducing the costs involved in moving the UAV to the regions to be studied, where it can only cover a limited space in each flight.
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