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Impact of Data Processing and Antenna Frequency on Spatial Structure Modelling of GPR Data

机译:数据处理和天线频率对GPR数据空间结构建模的影响

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Over the last few years high-resolution geophysical techniques, in particular ground-penetrating radar (GPR), have been used in agricultural applications for assessing soil water content variation in a non-invasive way. However, the wide use of GPR is greatly limited by the data processing complexity. In this paper, a quantitative analysis of GPR data is proposed. The data were collected with 250, 600 and 1600 MHz antennas in a gravelly soil located in south-eastern Italy. The objectives were: (1) to investigate the impact of data processing on radar signals; (2) to select a quick, efficient and error-effective data processing for detecting subsurface features; (3) to examine the response of GPR as a function of operating frequency, by using statistical and geostatistical techniques. Six data processing sequences with an increasing level of complexity were applied. The results showed that the type and range of spatial structures of GPR data did not depend on data processing at a given frequency. It was also evident that the noise tended to decrease with the complexity of processing, then the most error-effective procedure was selected. The results highlight the critical importance of the antenna frequency and of the spatial scale of soil/subsoil processes being investigated.
机译:在过去的几年中,高分辨率地球物理技术,特别是探地雷达(GPR),已在农业应用中用于以无创方式评估土壤含水量的变化。但是,GPR的广泛使用受到数据处理复杂性的极大限制。本文提出了对GPR数据的定量分析。数据是通过位于意大利东南部的砾石土壤中的250、600和1600 MHz天线收集的。目标是:(1)研究数据处理对雷达信号的影响; (2)选择一种快速,高效和具有错误效果的数据处理来检测地下特征; (3)通过使用统计和地统计技术来检验GPR作为工作频率的函数的响应。六个数据处理序列的复杂程度不断提高。结果表明,GPR数据空间结构的类型和范围不取决于给定频率下的数据处理。同样明显的是,噪声会随着处理的复杂性而降低,因此选择了最有效的错误处理程序。结果突出了天线频率和土壤/地下土壤过程空间尺度的至关重要性。

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