In this paper, we focus on the application of satellite synthetic-aperture radar (SAR) images for discriminating summer crops in Ukraine within the JECAM project. Both optical (EO-1/ALI) and SAR (RADARSAT-2) images are used in order to assess impact adding SAR images for classification purposes. Three different classifiers, in particular neural networks, support vector machine and decision trees, are applied with neural networks giving the best overall accuracy. It is found that major impact of using SAR images is for sunflower and sugar beet classes while there was no gain for other crops (maize and soybeans).
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Kussul et al. (2014) studied this question.