Synergy of very high resolution optical and radar data for object based olive grove mapping

This study investigates the potential of very high resolution (VHR) optical and radar data for olive grove landscape mapping. VHR data were fed into a four-step processing chain performing an object-based land-use classification. The four steps included (i) image segmentation, (ii) object feature calculation, (iii) object-based classification and (iv) land-use map evaluation. First, the optical (ADS40) and radar (RAMSES SAR and TerraSAR-X) data were applied to the processing chain separately. As supported by two segmentation evaluation measures, the stand purity index (PI) and the potential mapping accuracy (PMA), the optical data thereby led to a significantly better segmentation and a more accurate olive cover map (Kruskal–Wallis test, P