Analysis of GLORI GNSS-R airborne measurements for soil moisture estimation

crossref(2023)

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摘要
<p>Soil moisture plays an essential role in understanding the soil-vegetation-atmosphere interface and in managing water resources for irrigation. In recent years, the Global Navigation Satellite System Reflectometry (GNSS-R) technique has shown great potential in estimating and monitoring this parameter. In this context, various global operational products are already offered based on data from the CYGNSS satellites. In this study, we propose an analysis of an airborne campaign with measurements from the GLORI instrument at the Urgell agricultural site, in Spain. It is a polarimetric instrument allowing acquisitions in both LHCP (Left Hand Circular Polarized) and RHCP (Right Hand Circular Polarized) polarizations and L1 frequency band.</p> <p>In parallel with three flights carried out on the study site in July 2021, various in situ measurements are carried out on twenty reference plots (soil moisture, Leaf area index, soil roughness). An analysis of the incidence angle effect on the GNSS-R reflectivity measurements is proposed. It illustrates larger effects for RHCP polarization. A normalization of data for one incidence angle is proposed. A sensitivity analysis of GLORI measurements to soil moisture is then discussed. The effect of vegetation cover on the degradation of this sensitivity is highlighted. The LHCP polarization displays a higher sensitivity to soil moisture.</p> <p>An inversion model based on the two-omega approach is calibrated and validated with the in situ data acquired on the reference plots. Reflectivity is simulated as a function of soil moisture and the optical Normalized Difference Vegetation Index (NDVI) index which describes the dynamics of the plant cover. An RMSE close to 0.07m<sup>3</sup>/m<sup>3</sup> is retrieved for soil moisture validation.</p> <p>Soil moisture maps, based on the application of the inversion model, are proposed at a spatial resolution of 100 m for three realized flights. A correlation with precipitation events, as well as the presence or absence of irrigation is clearly observed.</p>
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