首页> 外文会议>24th International Symposium on Atmospheric and Ocean Optics: Atmospheric Physics >Classification of cloudiness from MODIS satellite data using regional statistical models for image texture and physical parameters of cloudiness during periods with snow cover
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Classification of cloudiness from MODIS satellite data using regional statistical models for image texture and physical parameters of cloudiness during periods with snow cover

机译:使用区域统计模型从MODIS卫星数据中对云量进行分类,以获取积雪期间云量的图像纹理和物理参数

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Statistical models are presented of the image texture and cloudiness physical characteristics over various natural zones of the Russian Federation during periods of snow cover. These models are based on the determination of the distribution laws and estimation of their parameters, which describe the fluctuations in the values of the cloud characteristics. The results are discussed of a comparative analysis of statistical cloud models for various natural zones, as well as cloud models, averaged over them, over snow-covered territories and a snow-free underlying surface. A description is presented of the cloud classification algorithm based on the application of artificial neural network technology and fuzzy logic methods. The results are presented of recognition of 12 cloud types from MODIS satellite data for various natural zones during seasons with snow cover.
机译:统计模型给出了各种自然区域的图像纹理和浊度物理特征。 俄罗斯联邦在积雪期间。这些模型基于确定的分布 定律及其参数的估计,它们描述了云特征值的波动。这 讨论了对各种自然区以及云的统计云模型进行比较分析的结果 在冰雪覆盖的领土和无雪的下层表面上对它们进行平均的模型。描述是 人工神经网络技术和模糊算法的云分类算法研究 逻辑方法。提出了从MODIS卫星数据中识别12种云类型的各种自然结果 积雪季节的区域。

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