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Polar sea-ice classification using enhanced resolution NSCAT data

机译:使用增强分辨率的NSCAT数据进行极地海冰分类

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The NASA scatterometer (NSCAT) collected Ku-band scatterometer measurements from September 1996 to June 1997. These data are converted high resolution six day images of the polar regions through the use of the scatterometer image reconstruction with filter (SIRF) algorithm. SIRF produces images of A and B where A is /spl sigma//sup 0/ at 40/spl deg/ incidence and B is the incidence angle dependence of /spl sigma//sup 0/. A simple four-dimensional classification technique is proposed which uses the dual polarization parameters A/sub v/, A/sub h/, B/sub v/, and B/sub h/. A k-means clustering classification can be used to separate pixels of the images with differing scattering mechanisms. This method also adapts to the seasonal characteristics of cluster migration by converging to the locally optimal cluster centroids. While validation data was not available at the time of this writing, the method is shown to have high correlation with the NSIDC SSM/I derived multiyear ice maps.
机译:NASA散射仪(NSCAT)收集了1996年9月至1997年6月的Ku波段散射仪测量结果。这些数据通过使用带滤波器的散射仪图像重建(SIRF)算法转换为极区的高分辨率六天图像。 SIRF生成A和B的图像,其中A是40 / spl deg /入射角的/ spl sigma // sup 0 /,而B是/ spl sigma // sup 0 /的入射角依赖性。提出了一种简单的四维分类技术,该技术使用了双极化参数A / sub v /,A / sub h /,B / sub v /和B / sub h /。 k均值聚类分类可用于使用不同的散射机制来分离图像的像素。该方法还通过收敛到局部最优的聚类质心来适应聚类迁移的季节特征。虽然在撰写本文时尚无验证数据,但该方法与NSIDC SSM / I得出的多年冰图高度相关。

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