Viabilidade do uso de imagens de drone para o monitoramento de falhas em cana-de-açúcar

Abstract

Given the low effectiveness of these manual surveys, the use of images captured by drones can be a more accurate alternative, providing more robust information for the producer's decision-making. In this work, two methods of surveying flaws in sugarcane were used, where we collected data manually through sampling, a method developed by Stolf, and also via drone, capturing images and monitoring the areas in their total size, which were later They were processed by the semi-automatic software InfoRow, which provides us with failure reports and actions according to the program, improving decision making. At the end of the experiment, we found that precision agriculture, when using drones, was more efficient when compared to manual farming, as long as the lots are well managed, thus enabling its use.