Pixelwise remote sensing image classification has benefited from temporal contextual information encoded in time series. In this paper, we investigate the use of data-driven features extracted from time series representations based on recurrence plots, with the goal of improving the effectiveness of classification systems. Performed experiments considered the classification of eucalyptus plantations based on time series profiles. Achieved results demonstrate that the combination of recurrence plot representations with deep-learning features are a promising research venue for addressing pixelwise classification problems.