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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 (a); 600 MHz (b) and 1600 MHz (c) frequencies using the sixth processing procedure. (Colour scale uses iso-frequency classes).
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sensors-15-16430-f010: Maps of estimated amplitude for 250 MHz (a); 600 MHz (b) and 1600 MHz (c) frequencies using the sixth processing procedure. (Colour scale uses iso-frequency classes).

Mentions: No significant improvement was observed in the maps obtained with the application of running average (fourth and fifth processing) even if the maps looked slightly more smoothed. Finally, the maps obtained with the sixth procedure were quite similar to the previous maps, though the quality has worsened for some of them, in particular for the deeper maps (Figure 10), because of the presence of quite evident artifacts. This was probably due to the assumption of a subsoil model with horizontal stratification and the use of an average velocity for all radar sections of a given frequency. In a complex environment, as the one studied, this assumption is probably violated, therefore the migration can cause errors and does not improve the quality of maps.


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 (a); 600 MHz (b) and 1600 MHz (c) frequencies using the sixth processing procedure. (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-f010: Maps of estimated amplitude for 250 MHz (a); 600 MHz (b) and 1600 MHz (c) frequencies using the sixth processing procedure. (Colour scale uses iso-frequency classes).
Mentions: No significant improvement was observed in the maps obtained with the application of running average (fourth and fifth processing) even if the maps looked slightly more smoothed. Finally, the maps obtained with the sixth procedure were quite similar to the previous maps, though the quality has worsened for some of them, in particular for the deeper maps (Figure 10), because of the presence of quite evident artifacts. This was probably due to the assumption of a subsoil model with horizontal stratification and the use of an average velocity for all radar sections of a given frequency. In a complex environment, as the one studied, this assumption is probably violated, therefore the migration can cause errors and does not improve the quality of maps.

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.