Detection of Vineyard Rows with U-NET Using Remote Sensing Data

One of the key steps in agricultural land management today is the detection of objects using Earth remote sensing data. The availability of high-resolution satellite imagery has led to new methods for image classification and analysis. The purpose of this study is to evaluate the effectiveness of machine learning algorithms for determining vineyard yields. It is proposed to use a neural network with U-N et architecture to extract information about the rows of a vineyard from satellite images. The trained neural network model has an accuracy of 90%.