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Basic geological mapping / Richard J. Lisle, Peter J. Brabham, and John W. Barnes
\"Basic Geological Mapping, 5th Edition is an essential basic guide to field techniques in mapping geology\"-- Provided by publisher.
Book
Geology of the Northern Apennines nappe stack on eastern Elba (Italy): new insights on the Neogene orogenic evolution of the Northern Tyrrhenian Sea
We document the tectonic and metamorphic evolution of thrust nappes of the eastern island of Elba. The area exposes a natural cross section of the Northern Apennines hinterland, from the metamorphic basement units to the overlying continent- and ocean-derived nappes. We integrated mapping, analysis of structures and microstructures, and the interpretation of drill core logs with lithostratigraphic, metamorphic, and geochronological constraints, producing a novel geological map of eastern Elba (1:5'000 scale). We show that the area experienced polyphase Oligocene - Pliocene contractional tectonics marked by in-sequence and out-of-sequence thrusting accompanied by folding and overprinted by faulting in the Pliocene. Magmatism occurred during contraction with post-magmatic thrusting ultimately coupling HP-LT and LP-HT units. Drill core logs allow for the first time the reconstruction of the N-dipping character of the Zuccale Fault, which represents the youngest (late Miocene - early Pliocene) large-scale structure in the area.
Journal Article
Landslide monitoring techniques in the Geological Surveys of Europe
Landslide monitoring is a mandatory step in landslide risk assessment. It requires collecting data on landslide conditions (e.g., areal extent, landslide kinematics, surface topography, hydrogeometeorological parameters, and failure surfaces) from different time periods and at different scales, from site-specific to local, regional, and national, to assess landslide activity. In this analysis, we collected information on landslide monitoring techniques from 17 members of the Earth Observation and Geohazards Expert Group (from EuroGeoSurveys) deployed between 2005 and 2021. We examined the types of the 75 recorded landslides, the landslide techniques, spatial resolution, temporal resolution, status of the technique (operational, non-operational), time of using (before the event, during the event, after the event), and the applicability of the technique in early warning systems. The research does not indicate the accuracy of each technique but, rather, the extent to which Geological Surveys conduct landslide monitoring and the predominant techniques used. Among the types of landslides, earth slides predominate and are mostly monitored by geological and engineering geological mapping. The results showed that Geological Surveys mostly utilized more traditional monitoring techniques since they have a broad mandate to collect geological data. In addition, this paper provides new insights into the role of the Geological Surveys on landslide monitoring in Europe and contributes to landslide risk reduction initiatives and commitments (e.g., the Kyoto Landslide Commitment 2020).
Journal Article
Hyperspectral Reconnaissance: Joint Characterization of the Spectral Mixture Residual Delineates Geologic Unit Boundaries in the White Mountains, CA
We use a classic locale for geology education in the White Mountains, CA, to demonstrate a novel approach for using imaging spectroscopy (hyperspectral imaging) to generate base maps for the purpose of geologic mapping. The base maps produced in this fashion are complementary to, but distinct from, maps of mineral abundance. The approach synthesizes two concepts in imaging spectroscopy data analysis: the spectral mixture residual and joint characterization. First, the mixture residual uses a linear, generalizable, and physically based continuum removal model to mitigate the confounding effects of terrain and vegetation. Then, joint characterization distinguishes spectrally distinct geologic units by isolating residual, absorption-driven spectral features as nonlinear manifolds. Compared to most traditional classifiers, important strengths of this approach include physical basis, transparency, and near-uniqueness of result. Field validation confirms that this approach can identify regions of interest that contribute significant complementary information to PCA alone when attempting to accurately map spatial boundaries between lithologic units. For a geologist, this new type of base map can complement existing algorithms in exploiting the coming availability of global hyperspectral data for pre-field reconnaissance and geologic unit delineation.
Journal Article
Engineering Geological Mapping for the Preservation of Ancient Underground Quarries via a VR Application
Underground monument preservation is tightly linked to geological risk. The geological risk management of underground structures typically relies on a preliminary site investigation phase. Engineering geological mapping—as a key site investigation element—is largely based on manual in situ work, often in harsh and dangerous environments. However, although new technologies can, in many cases, decrease the on-field time as well as eliminate inaccessibility issues, the example presented in this study demonstrates a special challenge that had to be addressed. The ancient underground marble quarries of Paros Island in Greece constitute a gallery complex of a total length of 7 km and only two portals, resulting in total darkness throughout almost the full length of the unsurveyed galleries. As such, the entire survey and engineering geological mapping solely relied on a virtual reality application that was developed based on a digital replica of the quarries using laser scanning. The study identifies several critical locations with potentially unstable geologic structures and computes their geometrical properties. Further numerical analyses based on data extracted directly from the digital replica of the rock mass led to the definition of appropriate risk mitigation measures along the underground marble quarries.
Journal Article
Landslide susceptibility assessment in complex geological settings: sensitivity to geological information and insights on its parameterization
The literature about landslide susceptibility mapping is rich of works focusing on improving or comparing the algorithms used for the modeling, but to our knowledge, a sensitivity analysis on the use of geological information has never been performed, and a standard method to input geological maps into susceptibility assessments has never been established. This point is crucial, especially when working on wide and complex areas, in which a detailed geological map needs to be reclassified according to more general criteria. In a study area in Italy, we tested different configurations of a random forest–based landslide susceptibility model, accounting for geological information with the use of lithologic, chronologic, structural, paleogeographic, and genetic units. Different susceptibility maps were obtained, and a validation procedure based on AUC (area under receiver-operator characteristic curve) and OOBE (out of bag error) allowed us to get to some conclusions that could be of help for in future landslide susceptibility assessments. Different parameters can be derived from a detailed geological map by aggregating the mapped elements into broader units, and the results of the susceptibility assessment are very sensitive to these geology-derived parameters; thus, it is of paramount importance to understand properly the nature and the meaning of the information provided by geology-related maps before using them in susceptibility assessment. Regarding the model configurations making use of only one parameter, the best results were obtained using the genetic approach, while lithology, which is commonly used in the current literature, was ranked only second. However, in our case study, the best prediction was obtained when all the geological parameters were used together. Geological maps provide a very complex and multifaceted information; in wide and complex area, this information cannot be represented by a single parameter: more geology-based parameters can perform better than one, because each of them can account for specific features connected to landslide predisposition.
Journal Article