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| Titel |
Delineation of karst terranes in complex environments: Application of modern developments in the wavelet theory and data mining |
| VerfasserIn |
Leonid Alperovich, Amir Averbuch, Lev Eppelbaum, Valery Zheludev |
| Konferenz |
EGU General Assembly 2013
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 15 (2013) |
| Datensatznummer |
250082068
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| Zusammenfassung |
| Karst areas occupy about 14% of the world land. Karst terranes of different origin have
caused difficult conditions for building, industrial activity and tourism, and are the source of
heightened danger for environment. Mapping of karst (sinkhole) hazards, obviously,
will be one of the most significant problems of engineering geophysics in the XXI
century.
Taking into account the complexity of geological media, some unfavourable environments
and known ambiguity of geophysical data analysis, a single geophysical method examination
might be insufficient. Wavelet methodology as whole has a significant impact on cardinal
problems of geophysical signal processing such as: denoising of signals, enhancement of
signals and distinguishing of signals with closely related characteristics and integrated
analysis of different geophysical fields (satellite, airborne, earth surface or underground
observed data).
We developed a three-phase approach to the integrated geophysical localization of
subsurface karsts (the same approach could be used for following monitoring of karst
dynamics). The first phase consists of modeling devoted to compute various geophysical
effects characterizing karst phenomena. The second phase determines development of the
signal processing approaches to analyzing of profile or areal geophysical observations.
Finally, at the third phase provides integration of these methods in order to create a new
method of the combined interpretation of different geophysical data. In the base of
our combine geophysical analysis we put modern developments in the wavelet
technique of the signal and image processing. The development of the integrated
methodology of geophysical field examination will enable to recognizing the karst
terranes even by a small ratio of “useful signal – noise” in complex geological
environments.
For analyzing the geophysical data, we used a technique based on the algorithm to
characterize a geophysical image by a limited number of parameters. This set of
parameters serves as a signature of the image and is to be utilized for discrimination
of images containing karst cavity (K) from the images non-containing karst (N).
The constructed algorithm consists of the following main phases: (a) collection of
the database, (b) characterization of geophysical images, (c) and dimensionality
reduction. Then, each image is characterized by the histogram of the coherency
directions. As a result of the previous steps we obtain two sets K and N of the signatures
vectors for images from sections containing karst cavity and non-karst subsurface,
respectively. |
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