Glacially Induced Fault Identification with LiDAR, Based on Examples from Finland

doi:10.1017/9781108779906.008

5 - Glacially Induced Fault Identification with LiDAR, Based on Examples from Finland

from Part II - Methods and Techniques for Fault Identification and Dating

Published online by Cambridge University Press: 02 December 2021

Jukka-Pekka Palmu ,

Antti E. K. Ojala ,

Jussi Mattila ,

Mira Markovaara-Koivisto ,

Tobias Bauer and

Edited by

Odleiv Olesen and

Holger Steffen: Affiliation:
Lantmäteriet, Sweden
Odleiv Olesen: Affiliation:
Geological Survey of Norway
Raimo Sutinen: Affiliation:
Geological Survey of Finland

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Summary

Using information from airborne light detection and ranging (LiDAR) data has produced a breakthrough in identification of postglacial faults and earthquake-deformed Quaternary deposits. LiDAR digital elevation models (DEMs) also improve the collection of detailed information on their spatial distribution, characteristics and geometry, and provides guidance for the more costly and time-consuming field studies. In areas of weak glacial erosion, younger and older (i.e. Pre-Late Weichselian) ruptures have been discovered superimposed on the same or adjacent postglacial fault segments, as has been identified when combining the DEM information and test pit sedimentological studies. We discuss Finnish examples and identify advantages, disadvantages and limitations. Advantages include verification of previously known fault scarps, detection of new postglacial fault segments, systems and entire complexes and the ability to measure the dimensions (lengths and offset) of the fault scarps from the LiDAR DEM data. Disadvantages include that inventory of the sub- and postglacial fault scarps is only possible when linear scarps cross-cut glacial and postglacial sediments.

Keywords

LiDAR Digital Elevation Model Fault Scarp Postglacial Fault Landslide Hillshading Delineation Masking Effect

Information

Type: Chapter
Information: Glacially-Triggered Faulting , pp. 89 - 99

DOI: https://doi.org/10.1017/9781108779906.008 [Opens in a new window]

Publisher: Cambridge University Press

Print publication year: 2021

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