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Effects of noise on optimal deconvolution accuracy in microwave observations

机译：噪声对微波观测中最佳反褶积精度的影响

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摘要

Due to large footprints of remotely sensed microwave brightness temperatures, accuracy of microwave observations in areas of large surface heterogeneity has always been a technological challenge. Microwave observations in areas dominated by waterbod-ies typically exhibit observed brightness temperature several tens of kelvins lower than areas having no surface water. The non-linearity between brightness temperature and other geophysical quantities such as soil moisture makes the accuracy of microwave observations a critical element for accurate estimation of these quantities. In retrieving soil moisture estimates, an error of 1 K in remotely sensed microwave brightness temperatures results in about 0.5-1% error in volumetric soil moisture. Large uncertainties in the observed brightness temperatures make such observations unusable in areas of large brightness temperature contrast. In this article, we discuss a deconvolution method to improve accuracy using the overlap in the adjacent microwave observations. We have shown that the method results in improved accuracy of 40% in brightness temperature estimation in regions of high brightness temperature contrast.
机译：由于遥感微波亮度温度占用的空间较大，因此在大表面异质性区域中进行微波观测的准确性一直是一项技术挑战。在以水体为主的区域中的微波观测通常显示出的亮度温度比没有地表水的区域低几十个开尔文。亮度温度与其他地球物理量（例如土壤湿度）之间的非线性使得微波观测的准确性成为准确估算这些量的关键因素。在获取土壤湿度估算值时，遥感微波亮度温度的1 K误差导致土壤体积水分的误差约为0.5-1％。所观察到的亮度温度的较大不确定性使得这种观察无法在大亮度温度对比度的区域中使用。在本文中，我们讨论了一种反卷积方法，以利用相邻微波观测中的重叠来提高精度。我们已经表明，该方法在高亮度温度对比度的区域中提高了亮度温度估计的40％精度。

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  • 来源
    《International journal of remote sensing》 |2013年第22期|7811-7820|共10页
  • 作者

    Ashutosh S. Limaye; William L. Crosson; Charles A. Laymon;

  • 作者单位

    NASA Marshall Space Flight Center / ZP 11, Huntsville, AL 35805, USA;

    Universities Space Research Association, Huntsville, AL 35805, USA;

    Universities Space Research Association, Huntsville, AL 35805, USA;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
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