Random Forest classification of Mediterranean land cover using multi-seasonal imagery and multi-seasonal texture

► We assess the increase in accuracy that can be achieved by incorporating geostatistical texture in Random Forest classifiers. ► The proposed method is based on the analysis of mono- and multi-seasonal textural features. ► Pseudo-cross and cross variograms were used to incorporate the seasonal/temporal dimension. ► Our approach outperforms GLCM-based approaches. ► Random Forest classification system was utilised to determine and select the most important textural features.