Enhancing Lithological Mapping with Spatially Constrained Bayesian Network (SCB-Net): An Approach for Field Data-Constrained Predictions with Uncertainty Evaluation

arXiv:2403.20195v1 Announce Type: cross
Abstract: Geological maps are an extremely valuable source of information for the Earth sciences. They provide insights into mineral exploration, vulnerability to natural hazards, and many other applications. These maps are created using numerical or conceptual models that use geological observations to extrapolate data. Geostatistical techniques have traditionally been used to generate reliable predictions that take into account the spatial patterns inherent in the data. However, as the number of auxiliary variables increases, these methods become …

abstract applications arxiv bayesian cs.cv cs.lg data earth earth sciences eess.iv evaluation exploration hazards information insights mapping maps natural network numerical predictions type uncertainty vulnerability