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Detecting the seasonal agricultural crop pattern accurately is a vital part of the agricultural planning. In this extent, Cukurova Region that is located in Eastern Mediterranean Region of Turkey was evaluated on agricultural landscape pattern. This region is the most productive agricultural region of Turkey also crop variability and yield are higher than many parts of the world. The main agricultural part of the area is called Lower Seyhan Plane (LSP) and it has been formed by the Seyhan, Ceyhan and Berdan rivers. The purpose of the study was to define the wheat, corn and cotton crop pattern using multi-temporal Landsat satellite images and object based classification approach for 2007 and 2013 cropping years. Three main crop’s areal difference were evaluated and changes were monitored between 2007 and 2013. The accuracy of the classifications were obtained by the spatial kappa statistics. Overall kappa accuracy was derived to be 0.9. Classification results were shown that wheat areas were decreased 35% and corn and cotton areas were increased 49% and 69% respectively. Particularly, government subventions and market demands were impacted cropping pattern in the region significantly. In addition, multi-temporal Landsat images and object based classification were a great combination to define regional agricultural crop pattern with very good accuracy (>90%)

the international archives of the photogrammetry, remote sensing and spatial information sciences/international archives of the photogrammetry, remote sensing and spatial information sciences

MONITORING THE WHEAT, CORN AND COTTON AREAS IN AN EASTERN MEDITERRANEAN AGRICULTURAL BASIN BETWEEN 2007 AND 2013