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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.


Variance proportion explained by nugget component for each used processing procedure and for each antenna.
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sensors-15-16430-f011: Variance proportion explained by nugget component for each used processing procedure and for each antenna.

Mentions: Since the best processing should be selected on its capability of filtering spatially uncorrelated error (white noise of GPR signal, nugget effect in geostatistics), the proportion of the total variance associated with nugget component was calculated (Figure 11).


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)

Variance proportion explained by nugget component for each used processing procedure and for each antenna.
© Copyright Policy
Related In: Results  -  Collection

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

sensors-15-16430-f011: Variance proportion explained by nugget component for each used processing procedure and for each antenna.
Mentions: Since the best processing should be selected on its capability of filtering spatially uncorrelated error (white noise of GPR signal, nugget effect in geostatistics), the proportion of the total variance associated with nugget component was calculated (Figure 11).

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.