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首页> 外文期刊>Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of >Validation of GPS-IR Soil Moisture Retrievals: Comparison of Different Algorithms to Remove Vegetation Effects
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Validation of GPS-IR Soil Moisture Retrievals: Comparison of Different Algorithms to Remove Vegetation Effects

机译:GPS-IR土壤水分反演的验证:去除植被影响的不同算法的比较

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摘要

The GPS interferometric reflectometry (GPS-IR) technique can be used to estimate near-surface soil moisture from signal-to-noise ratio (SNR) data collected with standard geodetic instrumentation. However, the effects of vegetation on GPS-IR soil moisture retrievals must be considered in some environments. In situ soil moisture observations from 11 GPS sites are used to compare the performance of three different retrieval algorithms that represent vegetation effects with different degrees of complexity. A bare-soil retrieval algorithm does not perform well, even at sites where seasonal variations in vegetation water content (VWC) are less than 1 kg m-2. The range of volumetric soil moisture (VSM) is too large due to the effects of vegetation on phase of the SNR interferogram, yielding an RMSE between in situ and GPS-IR VSM of 0.055 cm3 cm-3. Errors are reduced by an algorithm that adjusts for vegetation effects using variations in the amplitude of the SNR interferogram. RMSE is 0.038 cm3 cm-3 using this algorithm, below the typical limit required for validation of satellite data. This simple vegetation algorithm performs poorly at sites where seasonal variations in VWC are 1 kg m-2 or greater. A more complex algorithm, that uses amplitude in conjunction with frequency analysis of the SNR interferogeram to predict vegetation effects, provides acceptable performance at these sites ( RMSE = 0.039 cm3 cm-3). The additional complexity of this algorithm is only warranted at sites where the simple vegetation algorithm cannot adequately represent the effects of the vegetation fluctuations.
机译:GPS干涉反射法(GPS-IR)技术可用于根据标准大地测量仪器收集的信噪比(SNR)数据估算近地土壤湿度。但是,在某些环境中必须考虑植被对GPS-IR土壤水分获取的影响。使用来自11个GPS站点的原位土壤湿度观测结果来比较三种不同的检索算法的性能,这些算法代表了不同程度的植被效应。即使在植被含水量(VWC)的季节变化小于1 kg m-2的站点上,裸土检索算法也无法很好地执行。由于植被对SNR干涉图相位的影响,土壤体积水分(VSM)的范围太大,导致原位和GPS-IR VSM之间的RMSE为0.055 cm3 cm-3。通过使用SNR干涉图幅值的变化来调整植被效应的算法,可以减少误差。使用此算法,RMSE为0.038 cm3 cm-3,低于验证卫星数据所需的典型限值。这种简单的植被算法在VWC的季节变化为1 kg m-2或更大的站点上效果较差。一种更复杂的算法,结合使用振幅和SNR干扰素的频率分析来预测植被影响,可以在这些位置提供可接受的性能(RMSE = 0.039 cm3 cm-3)。仅在简单植被算法无法充分代表植被波动影响的地点,才需要保证该算法的额外复杂性。

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