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| Titel |
How segmented is your fault? Deciphering fault relationships from low resolution data |
| VerfasserIn |
Emma Bramham, Douglas Paton, Tim Wright |
| Konferenz |
EGU General Assembly 2017
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| Medientyp |
Artikel
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| Sprache |
en
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 19 (2017) |
| Datensatznummer |
250150716
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| Publikation (Nr.) |
 EGU/EGU2017-15205.pdf |
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| Zusammenfassung |
| Current understanding of the maximum displacement/length (Dmax/L) relationship of faults
results from the consolidation of numerous published studies. Many of these studies attempt
to constrain the power law exponent, n, where Dmax ∝ Ln, and provide rationale to the
spread in results in the cumulative published data. Variations in n across studies are widely
acknowledged as being due to differences in rock type, tectonic environment and
limitations on fault size range and sample size, both of which can be affected by the
acquisition resolution. The extent of the contribution of data resolution to the spread
in Dmax/L results is not currently constrained. This study examines the effect of
varying data resolution on the length-displacement relationship to determine this
contribution. We have created a 0.5 m resolution digital elevation model (DEM) of
the Krafla fissure swarm, NE Iceland, using airborne LiDAR and measured the
displacement/length profiles of 775 faults, with lengths ranging from 10s to 1000s of metres.
The LiDAR data was additionally downsampled to create 10 m and 30 m resolution
DEMs from which we measured the displacement/length profiles of 90 and 40 faults
respectively. Additionally we selected three major fault systems, measured as single
faults at 30 m resolution, measuring all the component faults observed at 10 m
and 0.5 m resolution. We suggest that the variation in resolution can account for a
substantial amount of the spread observed in the published dataset. Additionally we
propose that it is possible to establish whether a measured fault is likely to be a
single fault, without segmentation, regardless of the resolution it has been measured
at, based on its location within the distribution of the published Dmax/L dataset. |
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