TY - JOUR
T1 - Landmine and UXO detection using EMI and GPR -limitations due to the influence of the soil
AU - Igel, Jan
AU - Preetz, Holger
AU - Takahashi, Kazunori
AU - Loewer, Markus
PY - 2013/8/1
Y1 - 2013/8/1
N2 - Magnetic susceptibility and its frequency dependence have the dominant influences on EMI sensors. By analysing a large dataset of the magnetic properties of tropical soils, a classification system has been developed. With this system, it is possible to transform information from geological and soil maps into a prognosis of the performance of EMI sensors, which is valuable information to demining organisations for planning mine-clearing campaigns and selecting suitable equipment. The influence of the soil on GPR stand-alone and dual sensors is a more complicated issue, as it depends on the interaction between the properties of the soil and targets, as well as the construction of the individual sensor model. Therefore, there are no simple thresholds that can be used to rate the impact of soil properties on GPR sensor performance. In addition, the soil properties may change over time due to the influence of weather and vegetation on the water distribution in the soil. The sensor performance can be qualitatively predicted by investigating the in situ electrical properties of soil, including their values and spatial variability, which requires the knowledge of experts in the field. This semi-quantitative approach must be developed further in order to properly deduce the pertinent soil properties from geological maps and additional information, without requiring an extensive field survey. Doolittle et al. (2007) made the first attempt at generating a GPR soil suitability map, although their approach is based on classifying the DC conductivity and does not include dielectric losses, which govern the attenuation for high-frequency GPR applications. Furthermore, spatial variability and the seasonal variation of the moisture distribution of soil must also to be considered.
AB - Magnetic susceptibility and its frequency dependence have the dominant influences on EMI sensors. By analysing a large dataset of the magnetic properties of tropical soils, a classification system has been developed. With this system, it is possible to transform information from geological and soil maps into a prognosis of the performance of EMI sensors, which is valuable information to demining organisations for planning mine-clearing campaigns and selecting suitable equipment. The influence of the soil on GPR stand-alone and dual sensors is a more complicated issue, as it depends on the interaction between the properties of the soil and targets, as well as the construction of the individual sensor model. Therefore, there are no simple thresholds that can be used to rate the impact of soil properties on GPR sensor performance. In addition, the soil properties may change over time due to the influence of weather and vegetation on the water distribution in the soil. The sensor performance can be qualitatively predicted by investigating the in situ electrical properties of soil, including their values and spatial variability, which requires the knowledge of experts in the field. This semi-quantitative approach must be developed further in order to properly deduce the pertinent soil properties from geological maps and additional information, without requiring an extensive field survey. Doolittle et al. (2007) made the first attempt at generating a GPR soil suitability map, although their approach is based on classifying the DC conductivity and does not include dielectric losses, which govern the attenuation for high-frequency GPR applications. Furthermore, spatial variability and the seasonal variation of the moisture distribution of soil must also to be considered.
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M3 - Article
AN - SCOPUS:84884568321
VL - 31
SP - 43
EP - 51
JO - First Break
JF - First Break
SN - 0263-5046
IS - 8
ER -