Data acquisition by digitizing 2-D fracture networks and topographic lineaments in geographic information systems: further development and applications
Palamakumbura, Romesh; Krabbendam, Maarten; Whitbread, Katie; Arnhardt, Christian. 2020 Data acquisition by digitizing 2-D fracture networks and topographic lineaments in geographic information systems: further development and applications. Solid Earth, 11 (5). 1731-1746. https://doi.org/10.5194/se-11-1731-2020
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Abstract/Summary
Understanding the impact of fracture networks on rock mass properties is an essential part of a wide range of applications in geosciences from understanding permeability of groundwater aquifers and hydrocarbon reservoirs to erodibility properties and slope stability of rock masses for geotechnical engineering. However, gathering high-quality, oriented-fracture datasets in the field can be difficult and time-consuming, for example, due to constraints on field work time or access (e.g. cliffs). Therefore, a method for obtaining accurate, quantitative fracture data from photographs is a significant benefit. In this paper we describe a method for generating a series of digital fracture traces in a geographic information system (GIS) environment, in which spatial analysis of a fracture network can be carried out. The method is not meant to replace the gathering of data in the field but to be used in conjunction with it, and it is well suited when field work time is limited or when the section cannot be accessed directly. The basis of the method is the generation of the vector dataset (shapefile) of a fracture network from a georeferenced photograph of an outcrop in a GIS environment. From that shapefile, key parameters such as fracture density and orientation can be calculated. Furthermore, in the GIS environment more complex spatial calculations and graphical plots can be carried out such as heat maps of fracture density. Advantages and limitations compared to other fracture network capture methods are discussed.
Item Type: | Publication - Article |
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Digital Object Identifier (DOI): | https://doi.org/10.5194/se-11-1731-2020 |
ISSN: | 1869-9529 |
Date made live: | 06 Oct 2020 08:38 +0 (UTC) |
URI: | https://nora.nerc.ac.uk/id/eprint/528634 |
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