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首页> 外文期刊>Hydrology and Earth System Sciences >Use of reflected GNSS SNR data to retrieve either soil moisture or vegetation height from a wheat crop
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Use of reflected GNSS SNR data to retrieve either soil moisture or vegetation height from a wheat crop

机译:使用反射的GNSS SNR数据检索小麦作物的土壤湿度或植被高度

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This work aims to estimate soil moisture and vegetation height from Global Navigation Satellite System?(GNSS) Signal to Noise Ratio?(SNR) data using direct and reflected signals by the land surface surrounding a ground-based antenna. Observations are collected from a rainfed wheat field in southwestern France. Surface soil moisture is retrieved based on SNR phases estimated by the Least Square Estimation method, assuming the relative antenna height is constant. It is found that vegetation growth breaks up the constant relative antenna height assumption. A vegetation-height retrieval algorithm is proposed using the SNR-dominant period (the peak period in the average power spectrum derived from a wavelet analysis of SNR). Soil moisture and vegetation height are retrieved at different time periods (before and after vegetation's significant growth in March). The retrievals are compared with two independent reference data sets: in?situ observations of soil moisture and vegetation height, and numerical simulations of soil moisture, vegetation height and above-ground dry biomass from the ISBA (interactions between soil, biosphere and atmosphere) land surface model. Results show that changes in soil moisture mainly affect the multipath phase of the SNR data (assuming the relative antenna height is constant) with little change in the dominant period of the SNR data, whereas changes in vegetation height are more likely to modulate the SNR-dominant period. Surface volumetric soil moisture can be estimated (iR/isup2/sup??=??0.74, RMSE??=??0.009?msup3/sup?msup?3/sup) when the wheat is smaller than one wavelength (~ 19?cm). The quality of the estimates markedly decreases when the vegetation height increases. This is because the reflected GNSS signal is less affected by the soil. When vegetation replaces soil as the dominant reflecting surface, a wavelet analysis provides an accurate estimation of the wheat crop height (iR/isup2/sup??=??0.98, RMSE??=??6.2?cm). The latter correlates with modeled above-ground dry biomass of the wheat from stem elongation to ripening. It is found that the vegetation height retrievals are sensitive to changes in plant height of at least one wavelength. A simple smoothing of the retrieved plant height allows an excellent matching to in?situ observations, and to modeled above-ground dry biomass.
机译:这项工作旨在利用地面天线周围地面的直接和反射信号,根据全球导航卫星系统(GNSS)信噪比(SNR)数据估算土壤水分和植被高度。观测值是从法国西南部的一块雨养麦田中收集的。假设相对天线高度恒定,则基于最小二乘估计法估计的SNR相位来检索表层土壤水分。发现植被生长破坏了恒定的相对天线高度假设。提出了一种以SNR为主的周期(从SNR的小波分析得到的平均功率谱中的峰值周期)的植被高度检索算法。在不同的时间段(3月植被显着增长之前和之后)恢复土壤水分和植被高度。将检索结果与两个独立的参考数据集进行比较:土壤水分和植被高度的原位观测,以及来自ISBA(土壤,生物圈和大气之间的相互作用)土地的土壤水分,植被高度和地上干生物量的数值模拟表面模型。结果表明,土壤水分的变化主要影响SNR数据的多径相位(假设相对天线高度恒定),而SNR数据的主导周期变化不大,而植被高度的变化则更有可能调制SNR-主导时期。可以估计地表土壤水分( R 2 ?? =?0.74,RMSE ?? = ?? 0.009?m 3 ?m当小麦小于一个波长(〜19厘米)时,?3 )。当植被高度增加时,估算的质量明显下降。这是因为反射的GNSS信号受土壤的影响较小。当植被代替土壤作为主要反射面时,小波分析可以准确估算出小麦的作物高度( R 2 ?? =?0.98,RMSE ?? = ?? 6.2?cm)。后者与从茎伸长到成熟的小麦地上干生物量模型化相关。发现植被高度恢复对至少一个波长的植物高度的变化敏感。取回的植物高度的简单平滑处理可以很好地匹配原位观测值,并可以模拟地面上的干燥生物量。

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