用近端伽玛射线能谱鉴别灌溉和降雨

2020 IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor) Pub Date : 2020-11-04 DOI:10.1109/MetroAgriFor50201.2020.9277556

A. Serafini, M. Albéri, Enrico Chiarelli, M. Montuschi, Kassandra Giulia Cristina Raptis, V. Strati, F. Mantovani

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引用次数: 1

摘要

我们提出了一项基于7个月连续采集的近端伽马射线地面站的性能研究，包括42次降雨和16次灌溉。特别地，我们证明了该站通过其特有的伽马信号指纹识别灌溉和降雨的可靠性。这个概念验证实验表明，近端伽玛射线光谱可以潜在地填补准时和卫星土壤含水量测量之间的空间差距，并为制作综合灌溉地图提供一种无偏的方法。

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Discriminating irrigation and rainfall with proximal gamma-ray spectroscopy

We present a study of the performances of a proximal gamma-ray ground station based on a 7 months continuous acquisition, including 42 rain episodes and 16 irrigations. In particular, we demonstrate the reliability of the station in discriminating irrigations and rains through their peculiar gamma signals fingerprint. This proof of concept experiment shows that proximal gamma-ray spectroscopy can potentially fill the spatial gap between punctual and satellite soil water content measurements, as well as provide an unbiased approach for producing comprehensive irrigations maps.

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来源期刊

2020 IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor)

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