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Preliminary Results of a GNSS-R Simulation to Sense Canopy Parameters

机译:感测冠层参数的GNSS-R仿真的初步结果

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Soil moisture (SM) plays a significant role on the Earth's water, energy, and carbon transfers. Thus, global sensing of SM is vital. Conventional active and passive monostatic instruments have been used for SM retrieval for decades. For the sake of increasing spatiotemporal resolutions and decreasing costs, Global Navigation Satellite System Reflectometry (GNSS-R) have been examined recently. However, the high number of dynamic factors that affect GNSS-R observables in land applications make the use of this technique challenging. In this paper, we aim to present our preliminary observations about simulated GNSS-R signatures through a vegetated terrain in order to unveil GNSS-R sensitivity to dynamic land parameters. We exploited our recently developed coherent bistatic vegetation scattering model (SCoBi-Veg) for these simulations. We modelled a full growing season of corn field by using in situ measurement data. We observed received power variations as a function of observation angle and corn growth stage. First findings indicate the dominance of the coherent contribution over incoherent one. Results also demonstrate the effect of the growth stages on the received power.
机译:土壤水分(SM)在地球的水,能量和碳转移中起着重要作用。因此,对SM的整体感知至关重要。常规的主动和被动单静态仪器已用于SM检索数十年。为了提高时空分辨率和降低成本,最近已经对全球导航卫星系统反射法(GNSS-R)进行了研究。但是,在土地应用中会影响GNSS-R观测值的大量动态因素使该技术的使用具有挑战性。在本文中,我们旨在通过植被植被介绍有关模拟GNSS-R信号的初步观测结果,以揭示GNSS-R对动态土地参数的敏感性。我们利用我们最近开发的相干双基地植被散射模型(SCoBi-Veg)进行这些模拟。我们通过使用原位测量数据对玉米田的整个生长季节进行了建模。我们观察到接收功率随观察角和玉米生长阶段的变化而变化。最初的发现表明,相干贡献比不相干贡献更重要。结果还证明了生长阶段对接收功率的影响。

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