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Study of wind speed retrievals from Sentinel-1 images using physical models

机译:使用物理模型研究Sentinel-1图像中的风速检索

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Sea surface wind plays an important role for many applications such as meteorological forecasting, oil slick observation and ship detection. From the Sentinel-1 SAR images, we propose in this paper the methods which permit to retrieve rapidly wind fields. Wind directions can be directly extracted from the SAR images by the Local Gradient method with high resolution. Wind speed is estimated by the physical (SPM) and empirical (CMOD.5) models. Compared to the empirical models, the physical ones can give the estimations of wind speed in different frequencies and for both co-polarizations. They are thus more general and more interesting. Surface wave roughness spectrum is the most important parameter in the physical models to retrieve accurately wind speed. We study two approaches in this paper: semi-empirical model proposed by Elfouhaily and al., and empirical model studied by Hwang. To evaluate, the wind speed estimated by the SPM with two models of wave spectrum and the CMOD.5 is compared for the different cases of incident angle.
机译:海面风在许多应用中起着重要作用,例如气象预报,浮油观测和船舶探测。从Sentinel-1 SAR图像中,我们提出了允许快速检索风场的方法。可以通过局部梯度法以高分辨率直接从SAR图像中提取风向。风速由物理模型(SPM)和经验模型(CMOD.5)估算。与经验模型相比,物理模型可以给出不同频率和两种共极化下的风速估计。因此,它们更通用,更有趣。表面波粗糙度谱是物理模型中准确获取风速的最重要参数。本文研究了两种方法:Elfouhaily等人提出的半经验模型和Hwang研究的经验模型。为了进行评估,比较了SPM用两种波谱模型和CMOD.5估算的风速,以用于不同入射角的情况。

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