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Lineaments, linear structures on the surface of the Earth, often represent the surface expressions of brittle structures, e.g., fault zones and fracture zones, or ductile shear zones. In addition, they may also represent other geological features such as lithological contacts, tectonic boundaries and Quaternary structures, or potentially a superposition of any of these. A lineament interpretation is usually the first step in the structural assessment of a crystalline bedrock setting, and the lineaments can further be used as basis for scientific research to more accurately determine the location of the previously mentioned various geological features. In this study, a multi-source lineament interpretation was performed within ArcGIS for the whole of Finland, based on light detecting and ranging (LiDAR), aerogeophysical and bathymetric raster data. The lineament database enhances the capability to produce more accurate geological maps for various geological purposes in Finland. [ABSTRACT FROM AUTHOR]

Fracture studies commonly lack data for the length range between 10 m to 1 km. For this reason, scaling laws are required to extrapolate fracture properties, for example in discrete fracture network models. This study focused on analysis and correlation of topology, orientation and length distribution of multiscale fracture datasets to assess their scalability. The used datasets comprise UAV-derived photogrammetric models from natural outcrops and lineaments mapped using airborne LiDAR, bathymetry and aerogeophysical data, in several contrasting scales and resolutions. This study highlights challenges in acquiring uncensored and coherent brittle structural datasets from source data characterized by a large span of resolutions between the remote sensing datasets and models of the fractured outcrop. In specific, collected data was found to be potentially biased and affected by uncertainties related to both the censoring by sedimentary cover and the scale of observation. Our results revealed differences between lineament and outcrop fracture orientations, as well as difficulties in assessing topological parameters from lineament datasets. The 1:200 000 resolution was found best suited to the mapping of lineament length and resulted in a length distribution power law exponent of -1.92. For outcrop fractures that are less than 2 m long, the lognormal length distribution provided the only good fit to our data, while the longer outcrop fractures fitted relatively well with a power law exponent of -2.26. [ABSTRACT FROM AUTHOR]

Using multiple scales of observation in studying the fractures of the bedrock increases the reliability and representativeness of the respective studies. This is because the discontinuities, i.e., the fractures, in the bedrock lack any characteristic length and instead occur within a large range of scales of approximately 10 orders of magnitude. Consequently, fracture models need to be constructed based on representative multi-scale datasets to enable valid interpolation and extrapolation of common scaling laws to all fracture sizes. In this paper, we combine a detailed bedrock fracture study from an extensive bedrock outcrop area with lineament interpretation using Light Detection And Ranging (LiDAR) and geophysical data. Our study offers lineament data in an intermediary length range missing from Discrete Fracture Network -modelling conducted at Olkiluoto, a nuclear spent fuel facility in Finland. In addition, this study also provides a robust multi-scale fracture and lineament dataset which has been thoroughly analysed for the purposes of understanding the uncertainties and differences in the different datasets. Our analysis further covers the topological, scale-independent, fracture network characteristics. Results of our study include the discovery of three distinct azimuth sets, N-S, NE-SW and WNW-ESE, both single scale and multi-scale power-law models for fracture and lineaments and further insight into a trend of decreasing apparent connectivity of fracture networks as the scale of observation increases. Specifically, a multi-scale power-law exponent of -1.13 is fitted to fracture and lineament lengths although we found that individually the fractures and lineaments might follow distinct powerlaws rather than a common one. [ABSTRACT FROM AUTHOR]

Using multiple scales of observation in studying the fractures of the bedrock increases the reliability and representativeness of the respective studies. This is because the discontinuities, i.e., the fractures, in the bedrock lack any characteristic length and instead occur within a large range of scales of approximately 10 orders of magnitude. Consequently, fracture models need to be constructed based on representative multi-scale datasets to enable valid interpolation and extrapolation of common scaling laws to all fracture sizes. In this paper, we combine a detailed bedrock fracture study from an extensive bedrock outcrop area with lineament interpretation using Light Detection And Ranging (LiDAR) and geophysical data. Our study offers lineament data in an intermediary length range missing from Discrete Fracture Network -modelling conducted at Olkiluoto, a nuclear spent fuel facility in Finland. In addition, this study also provides a robust multi-scale fracture and lineament dataset which has been thoroughly analysed for the purposes of understanding the uncertainties and differences in the different datasets. Our analysis further covers the topological, scale-independent, fracture network characteristics. Results of our study include the discovery of three distinct azimuth sets, N-S, NE-SW and WNW-ESE, both single scale and multi-scale power-law models for fracture and lineaments and further insight into a trend of decreasing apparent connectivity of fracture networks as the scale of observation increases. Specifically, a multi-scale power-law exponent of -1.13 is fitted to fracture and lineament lengths although we found that individually the fractures and lineaments might follow distinct power-laws rather than a common one. [ABSTRACT FROM AUTHOR]