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Airborne multi-frequency microwave radiometric measurements in synergy with SAR data for the retrieval of soil moisture

机译:SAR数据中的空气传播多频微波辐射测量,用于树脂水分检索

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In the framework of a project funded by the Italian Space Agency (Algoritmi-METEMW), experimental activities based on airborne multi-frequency microwave radiometric measurements and simultaneous ground-truth data collection have been carried out in Central Italy, in an agricultural area close to Florence. The aim of the project was the development of innovative algorithms for the estimate of hydrological parameters integrating active and passive microwave data. The retrieval algorithms are based on Artificial Neural Networks (ANN). IFAC multi-frequency microwave radiometers (at L, C, and X bands) have been installed on ultralight helicopters, which overflew the area in concomitance with SMAP and Sentinel-1 (S-1) image acquisitions. Comparisons of new data with past results confirmed the already stated relationships between microwave indices and soil and vegetation parameters. Soil moisture content (SMC) values estimated from L-band radiometric data are very close to those retrieved using the ANN algorithm. This result confirms the possibility of validating satellite algorithms with airborne microwave radiometers.
机译:在由意大利航天局(Algoritmi-METEMW)资助的一个项目的框架,基于机载多频率的微波辐射测量和同时地面实况数据采集实验活动已经在意大利中部进行,在一个农业区,靠近佛罗伦萨。该项目的目的是具有革新算法水文参数集成有源和无源微波数据的估计的发展。检索算法是基于人工神经网络(ANN)。 IFAC多频微波辐射计(在L,C,和X波段)已被安装在直升机超轻,其飞越区域与SMAP和Sentinel-1(S-1)的图像采集concomitance。与过去的结果的新数据的比较证实微波指数和土壤和植被参数之间已经说明的关系。从L波段估计土壤水分含量(SMC)值辐射测量数据非常接近那些使用ANN算法检索。该结果证实验证卫星算法与空气传播的微波辐射计的可能性。

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