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首页> 外文期刊>Geoscience and Remote Sensing Letters, IEEE >Stochastic Approach in Wet Snow Detection Using Multitemporal SAR Data
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Stochastic Approach in Wet Snow Detection Using Multitemporal SAR Data

机译：多时相SAR数据在湿雪探测中的随机方法

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摘要

This letter introduces an alternative strategy for wet snow detection using multitemporal synthetic aperture radar (SAR) data. The proposed change detection method is primarily based on the comparison between two X-band SAR images acquired during the accumulation (winter) and melting (spring) seasons, in the French Alps. The new decision criterion relies on the local intensity statistics of the SAR images by considering the backscattering ratio as a stochastic process: the probability that “the intensity ratio fits into the predetermined range of values” is larger than a defined confidence level. Both the conducted snow backscattering simulations and the state-of-the-art measurements indicate more complex relation between the backscattering properties of the two snow types, with respect to the conventional assumption of the augmented electromagnetic absorption associated to the wet snow. Therefore, rather than adopting the standard hypothesis, we analyze the wet/dry snow backscattering ratio as a function of the local incidence angle (LIA). After employing the multilayer snow backscattering simulator, calibrated with scatterometer measurements in C-band, we modify, to some extent, the range of ratio values indicating the presence of the wet snow, by including positive ratio values for lower LIA. By simultaneously accounting for the speckle noise, the proposed stochastic approach derives the refined wet snow probability map. The performance analyses are carried out both through the comparison with the ground air temperature map and by comparing two copolarized channels processed separately.
机译：这封信介绍了使用多时相合成孔径雷达（SAR）数据进行湿雪探测的另一种策略。所提出的变化检测方法主要基于法国阿尔卑斯山在积累（冬季）和融化（春季）季节获取的两个X波段SAR图像之间的比较。通过将后向散射比视为随机过程，新的决策标准依赖于SAR图像的局部强度统计：“强度比符合预定值范围”的概率大于定义的置信度。进行的雪反向散射模拟和最新技术测量都表明，相对于传统的假设，两种雪的反向散射特性之间存在更复杂的关系。湿的雪。因此，我们没有采用标准假设，而是将湿/干雪后向散射比作为局部入射角（LIA）的函数进行了分析。在使用多层雪反向散射模拟器（通过C波段的散射仪测量进行了校准）之后，我们在一定程度上修改了指示存在湿雪的比率值的范围，方法是包括较低LIA的正比率值。通过同时考虑斑点噪声，所提出的随机方法可以得出精炼的湿雪概率图。通过与地面空气温度图的比较以及通过比较分别处理的两个同极化通道来进行性能分析。

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