Geophysical Data Analysis and Inverse Theory with MATLAB® and Python
Author: William Menke (Author)
Edition 版次: 5th
Publication Date 出版日期: 2024-03-12
Language 语言: English
Print Length 页数: 342 pages
ISBN-10: 0443137943
ISBN-13: 9780443137945
Book Description
By finelybook
Geophysical Data Analysis and Inverse Theory with MATLAB or Python, Fifth Edition is a revised and expanded introduction to inverse theory and tomography as it is practiced by geophysicists. The book demonstrates the methods needed to analyze a broad spectrum of geophysical datasets, with special attention given to those methods that generate images of the earth. Data analysis can be a mathematically complex activity, but the treatment in this volume is carefully designed to emphasize those mathematical techniques that readers will find the most familiar and to systematically introduce less-familiar ones. A series of “crib sheets” offer step-by-step summaries of methods presented. Utilizing problems and case studies, along with MATLAB and Python computer code and summaries of methods, the book provides professional geophysicists, students, data scientists and engineers in geophysics with the tools necessary to understand and apply mathematical techniques and inverse theory.
Includes material on probability, including Bayesian influence, probability density function, and metropolis algorithm
Offers detailed discussions of the application of inverse theory to seismological, gravitational, and tectonic studies
Provides numerous examples, color figures, and end-of-chapter problems to help readers explore and further understand the presented ideas
Includes both MATLAB and Python examples and problem sets
Review
An in-depth review of inverse theory and tomography as it is practiced by geophysicists that features Python and MATLAB problem sets
From the Back Cover
Geophysical Data Analysis and Inverse Theory with MATLAB® and Python Geophysical Data Analysis and Inverse Theory with MATLAB® and Python, fifth edition, is a revised and expanded introduction to inverse theory and tomography as it is practiced by geophysicists. It demonstrates the methods needed to analyze a broad spectrum of geophysical datasets, with special attention to those methods that generate images of the earth. Data analysis can be a mathematically complex activity, but the treatment in this volume is carefully designed to emphasize those mathematical techniques that readers will find most familiar and to systematically introduce less familiar ones. A series of “crib sheets” offer step-by-step summaries of the methods presented. Utilizing problems and case studies along with MATLAB and Python computer code and summaries of methods, the book provides professional geophysicists, students, data scientists, and engineers in geophysics with the tools necessary to understand and apply mathematical techniques and inverse theory. Key Features
Includes material on probability, including Bayesian inference, generalized least squares, Markov Chain Monte Carlo methods, and adjoint methods
Offers detailed discussion of the application of inverse theory to seismological, gravitational, and tectonic studies
Provides numerous examples, color figures, and end-of-chapter problems to help explore and further understand the presented ideas
Includes both MATLAB and Python examples and problem sets
About the Author William Menke, PhD, is a professor of earth and environmental sciences at Columbia University. His research focuses on the development of data analysis algorithms for time series analysis and imaging in the earth and environmental sciences and the application of these methods to volcanoes, earthquakes, and other natural hazards. He has 30 years of experience teaching data analysis methods to both undergraduate and graduate students. Relevant courses that he has taught include, at the undergraduate level, Computational Earth Science, Environmental Data Analysis, and The Earth System, and at the graduate level, Geophysical Inverse Theory, Quantitative Methods of Data Analysis, Geophysical Theory, and Practical Seismology. Cover: S-Wave arrival time anomalies (circles) from the magnitude 6.9 2014 Greece earthquake, relative to the prediction of the AK135 earth model, with the arrow depicting the direction of wave propagation. Late arrivals (up to 4s, red) in southern New England are due to the Northern Appalachian Anomaly, a region of unusually hot and upwelling mantle at about 200 km depth. Data like these are used to produce tomographic models of the Earth’s interior.
About the Author
William Menke is a Professor of Earth and Environmental Sciences at Columbia University. His research focuses on the development of data analysis algorithms for time series analysis and imaging in the earth and environmental sciences and the application of these methods to volcanoes, earthquakes, and other natural hazards. He has thirty years of experience teaching data analysis methods to both undergraduates and graduate students. Relevant courses that he has taught include, at the undergraduate level, Environmental Data Analysis and The Earth System, and at the graduate level, Geophysical Inverse Theory, Quantitative Methods of Data Analysis, Geophysical Theory and Practical Seismology.
