Classification of agricultural crops from middle-resolution satellite images using Gaussian processes based method

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Agricultural applications of the Gaussian process (GP) based techniques is considered. A method of classifying crops from multi-temporal Landsat 8 satellite imagery is proposed. The method uses the model of spectral features based on GP regression with constant expectation and square exponential covariance functions. Main steps of the classification procedure and examples of recognition of culture species are represented. The ground based data are used for quantitative validation of the proposed classification method. The highest overall classification accuracy in three classes of crops is 77.78%.

Gaussian processes, classification, regression, agricultural crops, landsat images, remote sensing, ndvi, снимки landsat

Короткий адрес: https://sciup.org/146279558

IDR: 146279558   |   DOI: 10.17516/1999-494X-0113

Список литературы Classification of agricultural crops from middle-resolution satellite images using Gaussian processes based method

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