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Polar sea-ice classification using enhanced resolution NSCAT data

机译:北极海冰分类使用增强的分辨率NSCAT数据

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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)从1996年9月到1997年9月收集了KU-BAND散射计测量。这些数据通过使用滤波器(SIRF)算法的散射计图像重建来转换极性区域的高分辨率六天图像。 SiRF产生A和B的图像,其中A是/ SPL SIGMA // SUP 0 /在40 / SPL型/入射和B处是/ 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,其使用双偏振参数A / sum v /,a / sub h /,b / sub v / sub h / su / s。 K-Means聚类分类可用于将图像的像素分开,具有不同的散射机制。该方法还通过融合到局部最佳聚类质心来适应集群迁移的季节性特征。虽然在本写作时不可用验证数据,但该方法显示与NSIDC SSM / I导出的多年度冰地图具有高相关性。

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