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ground truth
Probabilistic Programming for Transportable Source Characterization and Uncertainty Quantification of the North Korean Nuclear Tests 2006–2017
Single‐Station Back‐Azimuth Determination with the Receiver Function Rotation Technique Validated by the Locations of Earthquakes, Impacts, and Explosions
Applications of Nonergodic Site Response Models to ShakeAlert Case Studies in the Los Angeles Area
Influence of Sensor Density on Seismic Damage Assessment: A Case Study for Istanbul
THE IMPORTANCE OF THE MUSEUM IN ANTEBELLUM U.S. WESTERN TERRITORIAL EXPLORATION: PART 2. THE ROLES OF HAYDEN AND MEEK IN A PARADIGM SHIFT IN GEOLOGIC AND PALEONTOLOGIC STUDIES
Localization of deep voids through geophysical signatures of secondary dewatering features
Seismic detection and characterization of a man-made karst analog — A feasibility study
Ground-truth uncertainty-aware metrics for machine learning applications on seismic image interpretation: Application to faults and horizon extraction
Automated gamma-ray log pattern alignment and depth matching by machine learning
Reassessment of source parameters of ‘major’ southern African earthquakes
Iterative deblending for simultaneous source data using the deep neural network
SaltSeg: Automatic 3D salt segmentation using a deep convolutional neural network
New Perspectives On the Geomorphic, Sedimentologic, and Stratigraphic Signatures of Former Wave-dominated Tidal Inlets: Assateague Island, Maryland, U.S.A.
Generation of ground truth images to validate micro-CT image-processing pipelines
A3Mark: Seismic attribute benchmarking
Building Damage Assessment in the 2015 Gorkha, Nepal, Earthquake Using Only Post-Event Dual Polarization Synthetic Aperture Radar Imagery
Inversion of airborne geophysics over the DO-27/DO-18 kimberlites — Part 3: Induced polarization
Translating tomographic ambiguity into the probabilistic inference of hydrologic and engineering target parameters
Characterizing Earthquake Location Uncertainty in North America Using Source–Receiver Reciprocity and USArray
Application of a new method for rapid quality assessment of renewable aggregate resources in alpine regions
Abstract Alluvial fans, valley fills and debris cones represent economically significant, natural aggregate resources in the alpine regions of Austria. Due to continual erosion they constitute renewable sources of sand and gravel. However, knowledge of their petrographic properties and resulting aggregate quality is scant. An automated evaluation method was developed to estimate petrographic characteristics and predict resource suitability. This method makes use of the fact that the properties of a gravel deposit depend on the morphology and geology of the provenance area. Area percentages of geological units in the source area were expected to mirror the litho-spectrum of the gravel resource. Petrographic analysis of 13 field samples shows that this is indeed the case. Discrepancies amount to 0–10%; larger deviations occur for grain size fractions <2 mm in the presence of soft rock types such as mica-schist or paragneiss. Forecasts of aggregate quality on the basis of lithological composition and grain size characteristics were compared to operational data of five gravel pits. The actual usage of the material agrees with predictions in four out of the five cases.