Crop Classification with Morphological Profiles derived from SAR and Electro-Optical Satellite Data

Increasing world population, global climate change and environmental deteriorations force food and agriculture sector to increase production under difficult conditions. Crop monitoring and precision agriculture are significant legs in this process and crop classification is usually the first step. Remote sensing provides a less costly and more practical way compared to conventional methods in crop classification. In this study, contribution of spatial information provided by morphological opening and closing profiles to crop classification performances of time series SAR and electro-optical satellite data are assessed separately. In both, significant improvements are observed in overall classification accuracies; however, SAR benefited more from it. In nine-class classification problem, overall classification performance reached around 90% for both sensors.