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Modal decomposition of magnetic maps: the case of Cape Roberts aeromagnetic survey, Antarctica
Language
English
Obiettivo Specifico
3.4. Geomagnetismo
Status
Published
JCR Journal
JCR Journal
Peer review journal
Yes
Title of the book
Issue/vol(year)
2/52 (2009)
Pages (printed)
67-74
Issued date
2009
Abstract
This paper proposes a digital enhancement tool for magnetic anomaly maps. The magnetic anomaly map is decomposed
by means of Eigenvalue Decomposition into a number of orthogonal bases. The dataset is then filtered
accordingly to a specific variance pattern. The dataset is decomposed and the eigenvalues population is inspected
so that the variance is evaluated yielding the definition of two thresholds. Subsequently, the dataset is
reconstructed into three subsets which hold different features respectively. The proposed filtering procedure is
first tested with a synthetic signal and then applied to the data of Cape Roberts (Antarctica) aeromagnetic survey,
flown over an off-shore rift basin. The proposed method appears to be efficient in noise removal and acts as
a digital enhancement tool which provides TMI anomaly maps revealing hidden lineaments, otherwise not visible.
The methodology effectiveness as a hidden lineaments detection tool has been checked against independent
data.
by means of Eigenvalue Decomposition into a number of orthogonal bases. The dataset is then filtered
accordingly to a specific variance pattern. The dataset is decomposed and the eigenvalues population is inspected
so that the variance is evaluated yielding the definition of two thresholds. Subsequently, the dataset is
reconstructed into three subsets which hold different features respectively. The proposed filtering procedure is
first tested with a synthetic signal and then applied to the data of Cape Roberts (Antarctica) aeromagnetic survey,
flown over an off-shore rift basin. The proposed method appears to be efficient in noise removal and acts as
a digital enhancement tool which provides TMI anomaly maps revealing hidden lineaments, otherwise not visible.
The methodology effectiveness as a hidden lineaments detection tool has been checked against independent
data.
Type
article
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