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SUMMER CROPS CLASSIFICATION BY MULTI-TEMPORAL COSMO-SkyMed~? DATA

机译:夏季作物通过多时间彩色屠户进行分类〜?数据

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In this study, we propose a multi-temporal and multipolarization approach to discriminate different crop types in the Marchefel region, Austria. The sensitivity of X-band COSMO-SkyMed~? (CSK~?) data with respect to five crop classes, namely carrot, corn, potato, soybean and sugarbeet is investigated. In particular, the capabilities of dual-polarization (StripMap PingPong) HH/HV, and single-polarization (StripMap Himage), HH and VH, in distinguishing among the five crop types are evaluated. A total of twenty-one Himage and ten PingPong images were acquired in a seven-months period, from April to October 2014. Therefore, the backscattering coefficient was extracted for each dataset and the classification was performed using a pixel-based support vector machine (SVM) approach. The accuracy of the obtained crop classifications was assessed by comparing them with ground truth. The dual-polarization results are contrasted between the HH and HV polarization, and with single-polarization ones (HH and VH polarizations). The best accuracy is obtained by using time-series of StripMap Himage data, at VH polarization, covering the whole season period.
机译:在这项研究中,我们提出了一种多时间和多极化方法来区分奥地利马克森地区的不同作物类型。 X波段Cosmo-Skymed的敏感性〜? (CSK〜?)关于五种作物类别的数据,即胡萝卜,玉米,马铃薯,大豆和甘油。特别地,评估了双极化(Tirmap Pingpongpong)HH / HV和单极化(TILLMAP Hemage),HH和VH的能力,在区分五种作物类型中。从2014年4月到10月,在七个月期间获得了二十一度成熟和十个Pingpong图像。因此,针对每个数据集提取了反向散射系数,并使用基于像素的支持向量机进行分类( SVM)方法。通过将它们与地面真理进行比较来评估所获得的作物分类的准确性。双极化结果与HH和HV偏振之间形成对比,并具有单极化(HH和VH偏振)。通过使用vh极化的时间系列的Tiblemap Memage数据,涵盖整个季节期间,获得最佳精度。

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