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

De Benedetto D, Quarto R, Castrignanò A, Palumbo DA - Sensors (Basel) (2015)

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Dipartimento di Scienze della Terra e Geoambientali, University of Bari, Aldo Moro, Bari 70125, Italy. daniela.debenedetto@entecra.it.

ABSTRACT
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.

No MeSH data available.


Maps of estimated amplitude for 250 MHz antenna frequency using the third processing procedure corresponding to 4 ns (a); 10 ns (b) and 20 ns (c). (Colour scale uses iso-frequency classes).
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sensors-15-16430-f007: Maps of estimated amplitude for 250 MHz antenna frequency using the third processing procedure corresponding to 4 ns (a); 10 ns (b) and 20 ns (c). (Colour scale uses iso-frequency classes).

Mentions: For the second processing, the maps at 250 MHz frequency and corresponding to the longer time slices (16–18 ns) appeared well structured and more associated with the ones observed in the shallower depths. Therefore, the addition of a further step in the GPR processing improved the signal, recovering more information from the deeper depths. This characteristic was not valid for the other frequencies, suggesting that no improvement was obtained with the addition of dewow, as expected for the higher sampling frequencies used. As for the third procedure, all the maps of the estimated amplitude at different times (Figure 7) displayed some consistency up to the deeper depth. A tendency for higher values of amplitude was detectable along the north-eastern and south-western sides of the plot.


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

De Benedetto D, Quarto R, Castrignanò A, Palumbo DA - Sensors (Basel) (2015)

Maps of estimated amplitude for 250 MHz antenna frequency using the third processing procedure corresponding to 4 ns (a); 10 ns (b) and 20 ns (c). (Colour scale uses iso-frequency classes).
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4541886&req=5

sensors-15-16430-f007: Maps of estimated amplitude for 250 MHz antenna frequency using the third processing procedure corresponding to 4 ns (a); 10 ns (b) and 20 ns (c). (Colour scale uses iso-frequency classes).
Mentions: For the second processing, the maps at 250 MHz frequency and corresponding to the longer time slices (16–18 ns) appeared well structured and more associated with the ones observed in the shallower depths. Therefore, the addition of a further step in the GPR processing improved the signal, recovering more information from the deeper depths. This characteristic was not valid for the other frequencies, suggesting that no improvement was obtained with the addition of dewow, as expected for the higher sampling frequencies used. As for the third procedure, all the maps of the estimated amplitude at different times (Figure 7) displayed some consistency up to the deeper depth. A tendency for higher values of amplitude was detectable along the north-eastern and south-western sides of the plot.

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Dipartimento di Scienze della Terra e Geoambientali, University of Bari, Aldo Moro, Bari 70125, Italy. daniela.debenedetto@entecra.it.

ABSTRACT
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.

No MeSH data available.