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| Titel |
Integration of potential and quasipotential geophysical fields and GPR data for delineation of buried karst terranes in complex environments |
| VerfasserIn |
L. V. Eppelbaum, L. S. Alperovich, V. Zheludev, M. Ezersky, A. Al-Zoubi, E. Levi |
| Konferenz |
EGU General Assembly 2012
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 14 (2012) |
| Datensatznummer |
250061391
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| Zusammenfassung |
| Karst is found on particularly soluble rocks, especially limestone, marble, and dolomite
(carbonate rocks), but is also developed on gypsum and rock salt. Subsurface carbonate rocks
involved in karst groundwater circulation considerably extend the active karst realm, to
perhaps 14% of the world’s land area (Price, 2009). The phenomenon of the solution
weathering of limestone is the most widely known in the world. Active sinkholes growth
appears under different industrial constructions, roads, railways, bridges, airports,
buildings, etc. Regions with arid and semi-arid climate occupy about 30% of the Earth’s
land.
Subsurface in arid regions is characterized by high variability of physical properties both on
lateral and vertical that complicates geophysical survey analysis. Therefore for localization
and monitoring of karst terranes effective and reliable geophysical methodologies should be
applied. Such advanced methods were developed in microgravity (Eppelbaum et al., 2008;
Eppelbaum, 2011b), magnetic (Khesin et al., 1996; Eppelbaum et al., 2000, 2004;
Eppelbaum, 2011a), induced polarization (Khesin et al., 1997; Eppelbaum and Khesin,
2002), VLF (Eppelbaum and Khesin, 1992; Eppelbaum and Mishne, 2012), near-surface
temperature (Eppelbaum, 2009), self-potential (Khesin et al., 1996; Eppelbaum and
Khesin, 2002), and resistivity (Eppelbaum, 1999, 2007a) surveys. Application of some
of these methodologies in the western and eastern shores of the Dead Sea area
(e.g., Eppelbaum et al., 2008; Ezersky et al., 2010; Al-Zoubi et al., 2011) and in
other regions of the world (Eppelbaum, 2007a) has shown their effectiveness. The
common procedures for ring structure identification against the noise background and
probabilistic-deterministic methods for recognizing the desired targets in complex media are
presented in Khesin and Eppelbaum (1997), Eppelbaum et al. (2003), and Eppelbaum
(2007b).
For integrated analysis of different geophysical fields (including GPR images) intended for
delineation of karst terranes at a depth was proposed to use informational and wavelet
methodologies (Eppelbaum et al., 2011). Informational approach based on the classic
Shannon approach is propose to recognize weak geophysical effects observed against the
strong noise background. Unfortunately, this approach sometimes does not permit to reveal
the desired effects when the noise effects have a strong dispersion. At the same time, the
wavelet methodologies are highly powerful and thriving mathematical tool. Wavelet approach
is applied for derivation of enhanced (e.g., coherence portraits) and combined images of
geophysical indicators oriented to identification of karst signatures. The methodology based
on the matching pursuit with wavelet packet dictionaries is used to extract desired signals
even from strongly noised data developed (e.g., Averbuch et al., 2010). The recently
developed technique of diffusion clustering combined with the abovementioned wavelet
methods is utilized to integrate geophysical data and detect existing signals caused by
karst terranes developing a depth. The main goal of this approach is to detect the
geophysical signatures of karst developing at a noisy area with minimal number
of false alarms and miss-detections. It is achieved via analysis of some physical
parameters (these parameters may vary for different regions). For this aim various
robust algorithms might be employed. The geophysical signals are characterized
by the distribution of their energies among blocks of wavelet packet coefficients. |
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