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How can we draw reliable conclusions from limited and imperfect data? This textbook offers a clear and accessible guide to the principles behind scientific inference, showing how a unifying framework connects fields as diverse as Earth science, medical imaging, non-destructive testing, meteorology, climate research, and machine learning. It presents both classical and modern methods for solving real-world inference problems, with practical guidance on evaluating the reliability of results and understanding their uncertainties. Designed as both a learning resource and a long-term reference, the book balances depth with clarity. Hands-on computational exercises throughout help readers translate ideas into practice, strengthen their intuition and build confidence in tackling their own data challenges. It is ideal for advanced undergraduate and postgraduate students, as well as researchers and professionals, across many disciplines, from environmental science and medical imaging to climate research, machine learning, and economics.

The seismic ambient field allows us to study interactions between the atmosphere, the oceans and the solid Earth. The theoretical understanding of seismic ambient noise has improved substantially in the last decades, and the number of its applications has increased dramatically. With chapters written by eminent scientists from the field, this book covers a range of topics including ambient noise observations, generation models of their physical origins, numerical modelling and processing methods. The later chapters focus on applications in imaging and monitoring the internal structure of the Earth, including interferometry for time-dependant imaging and tomography. This volume thus provides a comprehensive overview of this cutting-edge discipline for graduate students studying geophysics and for scientists working in seismology and other imaging sciences.

This enduringly popular undergraduate textbook has been thoroughly reworked and updated, and now comprises twelve chapters covering the same breadth of topics as earlier editions, but in a substantially modernized fashion to facilitate classroom teaching. Covering both theoretical and applied aspects of geophysics, clear explanations of the physical principles are blended with step-by-step derivations of the key equations and over 400 explanatory figures to explain the internal structure and properties of the planet, including its petroleum and mineral resources. New topics include the latest data acquisition technologies, such as satellite geophysics, planetary landers, ocean bottom seismometers, and fibre optic methods, as well as recent research developments in ambient noise interferometry, seismic hazard analysis, rheology, and numerical modelling - all illustrated with examples from the scientific literature. Student-friendly features include separate text boxes with auxiliary explanations and advanced topics of interest; reading lists of foundational, alternative, or more detailed resources; end-of-chapter review questions and an increased number of quantitative exercises. Completely new to this edition is the addition of computational exercises in Python, designed to help students acquire important programming skills and develop a more profound understanding of geophysics.

This enduringly popular undergraduate textbook has been thoroughly reworked and updated, and now comprises twelve chapters covering the same breadth of topics as earlier editions, but in a substantially modernized fashion to facilitate classroom teaching. Covering both theoretical and applied aspects of geophysics, clear explanations of the physical principles are blended with step-by-step derivations of the key equations and over 400 explanatory figures to explain the internal structure and properties of the planet, including its petroleum and mineral resources. New topics include the latest data acquisition technologies, such as satellite geophysics, planetary landers, ocean bottom seismometers, and fibre optic methods, as well as recent research developments in ambient noise interferometry, seismic hazard analysis, rheology, and numerical modelling - all illustrated with examples from the scientific literature. Student-friendly features include separate text boxes with auxiliary explanations and advanced topics of interest; reading lists of foundational, alternative, or more detailed resources; end-of-chapter review questions and an increased number of quantitative exercises. Completely new to this edition is the addition of computational exercises in Python, designed to help students acquire important programming skills and develop a more profound understanding of geophysics.

Exploiting Seismic Waveforms introduces a range of recent developments in seismology including the application of correlation techniques, understanding of multi-scale heterogeneity and the extraction of structure and source information by seismic waveform inversion. It provides a full treatment of correlation methods for seismic noise and event signals, and develops inverse methods for both sources and structure. Higher frequency components of seismograms are frequently neglected, or removed by filtering, but they contain information about seismic structure on scales that cannot be revealed by seismic tomography. Sufficient computational resources are now available for waveform inversion for 3-D structure to be a practical procedure and this book describes suitable algorithms and examples reflecting current best practice. Intended for students and researchers in seismology, this book provides a physical understanding of seismic waveforms and the way that different aspects of the seismic wavefield are revealed by the way that seismic data are handled.

This book develops and describes state of the art methodologies covering all aspects of full waveform tomography including methods for the numerical solution of the elastic wave equation, the adjoint method, the design of objective functionals and optimisation schemes.