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. The stochastic generation of discrete fracture networks (DFN) is a method formodelling fracture patterns used to assess the in situ fragmentation in avolume of rock. The DFN modelling approach is based on theassumption that the natural fragmentation of rocks is a function of the length andconnectivity of the fractures within the considered volume of rock. Thus, in order to generate a site-specific DFN, theprimary geometric properties of the fracture surfaces within therock volume (especially orientation, size and fracture intensity as well asthe local spatial variability) must be defined as distribution functions (Elmoet al., 2014). The required base statistics are usually obtained from fractureanalysis on boreholes, exposed rock surfaces or (to a limited extent) 3Dseismics (e.g. Bisdom et al., 2014; Bemis et al., 2014). We adopted a terrestrial close-range photogrammetry approach to captureseveral outcrops and analyse fracture traces on the exposed rock surfaces, the chosenworkflow is based around the use of free and open-source software. Images wereacquired from several quarries in the Weschnitzpluton, agranodioritic to quartz monzodioritic pluton in the Bergstrasse Odenwald(e.g. Altherr et al., 1999) using a consumer-grade Nikon D5300DSLR with fixed focal length instead of a drone or Lidar-system for legalreasons, partially tree-lined outcrops and cost efficiency. Since point cloudsobtained from photogrammetry are inherently dimensionless, we used a sphericaltarget with compass and bubble level for scale and proper spatial orientation(Froideval et al., 2019). The exact geolocation is not particularly importantfor the task, so the use of GPS, total station or georeferenced ground controlpoints is not necessary. Dense point clouds were computed using the opensource SfM photogrammetry suite Meshroom (AliceVision, 2021), which can beused for manual or semi-automatic detection of fracture surfaces and their orientation(Schnabel et al., 2007) and to generate orthorectified images of the rock surfaceto trace fracture lengths and nodes in a GIS (Nyberg et al., 2018). Ourinvestigations proved terrestrial photogrammetry to be a valuable and easily accessible tool in thedocumentation of natural fracture patterns and a robust base for thegeneration of DFN networks.

Terrestrial photogrammetry: a method to gather data on fractures for DFN modelling from exposed rock surfaces