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Winter wheat is an important crop for many countries, and monitoring of its planted area is considered important. Optical sensors have been used to monitor agricultural land, and have shown good classification and monitoring capabilities. However, observations using optical sensors sometimes suffer from interference due to cloud cover or rain. In contrast, synthetic aperture radars (SAR) can be used for Earth observation even under rainy, cloudy or dark conditions, hence SAR is expected to be effective in monitoring agricultural fields and identifying winter wheat fields. The objective of this study is to analyze the potential of TerraSAR-X dual images, in the StripMap mode, for mapping winter wheat planted areas. Using the separability statistic (D), it emerged that the sigma naught acquired in mid-July possesses great potential. The method applied in this study has an overall accuracy exceeding 96% for HH and VV polarization data for identifying winter wheat fields.
