Image Segmentation in the Geosciences

Image Segmentation in Geosciences: From Fundamentals to Frontiers is the definitive resource for researchers, practitioners, and students working with complex geological imagery. This volume addresses the increasing need for precise, quantitative interpretation of diverse datasets, from micro-CT scans to satellite imagery, by consolidating classical and modern computational methodologies. As the volume of geoscience data expands, the book emphasizes the necessity of advanced segmentation techniques, including machine learning and deep learning, to transform raw data into actionable insights. It systematically covers core principles, innovative AI-driven approaches, and applications across reservoir characterization, geophysics, remote sensing, and environmental monitoring, supported by detailed case studies. The content spans methods, fractal and multifractal analysis, and cutting-edge AI architectures like CNNs, GANs, and transformers. It guides readers through practical workflows, visualization tools, and evaluation metrics, enabling them to bridge the gap between theoretical algorithms and real-world geoscience problems. This book empowers geoscientists, data scientists, and engineers to leverage the latest computational advances for more accurate resource assessment, hazard detection, and environmental management, fostering a new era of data-driven Earth sciences.