Collecting, Processing and Presenting Geoscientific Information
Collecting, Processing and Presenting Geoscientific Information

Author: Martin H. Trauth

Publisher: Springer

Published: 2018-03-26

Total Pages: 286

ISBN-13: 3662562030

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This second edition is an intensively revised and updated version of the book MATLAB® and Design Recipes for Earth Sciences. It aims to introduce students to the typical course followed by a data analysis project in earth sciences. A project usually involves searching relevant literature, reviewing and ranking published books and journal articles, extracting relevant information from the literature in the form of text, data, or graphs, searching and processing the relevant original data using MATLAB, and compiling and presenting the results as posters, abstracts, and oral presentations using graphics design software. The text of this book includes numerous examples on the use of internet resources, on the visualization of data with MATLAB, and on preparing scientific presentations. As with the book MATLAB Recipes for Earth Sciences–4rd Edition (2015), which demonstrates the use of statistical and numerical methods on earth science data, this book uses state-of-the art software packages, including MATLAB and the Adobe Creative Suite, to process and present geoscientific information collected during the course of an earth science project. The book's supplementary electronic material (available online through the publisher's website) includes color versions of all figures, recipes with all the MATLAB commands featured in the book, the example data, exported MATLAB graphics, and screenshots of the most important steps involved in processing the graphics.

MATLAB® and Design Recipes for Earth Sciences
MATLAB® and Design Recipes for Earth Sciences

Author: Martin H. Trauth

Publisher: Springer Science & Business Media

Published: 2012-09-14

Total Pages: 301

ISBN-13: 3642325432

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The overall aim of the book is to introduce students to the typical course followed by a data analysis project in earth sciences. A project usually involves searching relevant literature, reviewing and ranking published books and journal articles, extracting relevant information from the literature in the form of text, data, or graphs, searching and processing the relevant original data using MATLAB, and compiling and presenting the results as posters, abstracts, and oral presentations using graphics design software. The text of this book includes numerous examples on the use of internet resources, on the visualization of data with MATLAB, and on preparing scientific presentations. As with its sister book MATLAB Recipes for Earth Sciences–3rd Edition (2010), which demonstrates the use of statistical and numerical methods on earth science data, this book uses state-of-the art software packages, including MATLAB and the Adobe Creative Suite, to process and present geoscientific information collected during the course of an earth science project. The book's supplementary electronic material (available online through the publisher's website) includes color versions of all figures, recipes with all the MATLAB commands featured in the book, the example data, exported MATLAB graphics, and screenshots of the most important steps involved in processing the graphics.

MATLAB® Recipes for Earth Sciences
MATLAB® Recipes for Earth Sciences

Author: Martin H. Trauth

Publisher: Springer Science & Business Media

Published: 2007

Total Pages: 294

ISBN-13: 3540727485

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Introduces methods of data analysis in geosciences using MATLAB such as basic statistics for univariate, bivariate and multivariate datasets, jackknife and bootstrap resampling schemes, processing of digital elevation models, gridding and contouring, geostatistics and kriging, processing and georeferencing of satellite images, digitizing from the screen, linear and nonlinear time-series analysis and the application of linear time-invariant and adaptive filters. Includes a brief description of each method and numerous examples demonstrating how MATLAB can be used on data sets from earth sciences.

Python Recipes for Earth Sciences
Python Recipes for Earth Sciences

Author: Martin H. Trauth

Publisher: Springer Nature

Published: 2022-09-28

Total Pages: 463

ISBN-13: 3031077199

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Python is used in a wide range of geoscientific applications, such as in processing images for remote sensing, in generating and processing digital elevation models, and in analyzing time series. This book introduces methods of data analysis in the geosciences using Python that include basic statistics for univariate, bivariate, and multivariate data sets, time series analysis, and signal processing; the analysis of spatial and directional data; and image analysis. The text includes numerous examples that demonstrate how Python can be used on data sets from the earth sciences. The supplementary electronic material (available online through Springer Link) contains the example data as well as recipes that include all the Python commands featured in the book.

MATLAB® and Design Recipes for Earth Sciences
MATLAB® and Design Recipes for Earth Sciences

Author: Martin Trauth

Publisher: Springer Science & Business Media

Published: 2012-09-14

Total Pages: 301

ISBN-13: 3642325440

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The overall aim of the book is to introduce students to the typical course followed by a data analysis project in earth sciences. A project usually involves searching relevant literature, reviewing and ranking published books and journal articles, extracting relevant information from the literature in the form of text, data, or graphs, searching and processing the relevant original data using MATLAB, and compiling and presenting the results as posters, abstracts, and oral presentations using graphics design software. The text of this book includes numerous examples on the use of internet resources, on the visualization of data with MATLAB, and on preparing scientific presentations. As with its sister book MATLAB Recipes for Earth Sciences–3rd Edition (2010), which demonstrates the use of statistical and numerical methods on earth science data, this book uses state-of-the art software packages, including MATLAB and the Adobe Creative Suite, to process and present geoscientific information collected during the course of an earth science project. The book's supplementary electronic material (available online through the publisher's website) includes color versions of all figures, recipes with all the MATLAB commands featured in the book, the example data, exported MATLAB graphics, and screenshots of the most important steps involved in processing the graphics.

Signal and Noise in Geosciences
Signal and Noise in Geosciences

Author: Martin H. Trauth

Publisher: Springer Nature

Published: 2021-11-06

Total Pages: 349

ISBN-13: 3030749134

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This textbook introduces methods of geoscientific data acquisition using MATLAB in combination with inexpensive data acquisition hardware such as sensors in smartphones, sensors that come with the LEGO MINDSTORMS set, webcams with stereo microphones, and affordable spectral and thermal cameras. The text includes 35 exercises in data acquisition, such as using a smartphone to acquire stereo images of rock specimens from which to calculate point clouds, using visible and near-infrared spectral cameras to classify the minerals in rocks, using thermal cameras to differentiate between different types of surface such as between soil and vegetation, localizing a sound source using travel time differences between pairs of microphones to localize a sound source, quantifying the total harmonic distortion and signal-to-noise ratio of acoustic and elastic signals, acquiring and streaming meteorological data using application programming interfaces, wireless networks, and internet of things platforms, determining the spatial resolution of ultrasonic and optical sensors, and detecting magnetic anomalies using a smartphone magnetometer mounted on a LEGO MINDSTORMS scanner. The book’s electronic supplementary material (available online through Springer Link) contains recipes that include all the MATLAB commands featured in the book, the example data, the LEGO construction plans, photos and videos of the measurement procedures.

Geoscience Data and Collections
Geoscience Data and Collections

Author: National Research Council

Publisher: National Academies Press

Published: 2002-09-23

Total Pages: 124

ISBN-13: 0309169666

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Geoscience data and collections (such as, rock and sediment cores, geophysical data, engineering records, and fossils) are necessary for industries to discover and develop domestic natural resources to fulfill the nation's energy and mineral requirements and to improve the prediction of immediate and long term hazards, such as land slides, volcanic eruptions and global climate change. While the nation has assembled a wealth of geoscience data and collections, their utility remains incompletely tapped. Many could act as invaluable resources in the future but immediate action is needed if they are to remain available. Housing of and access to geoscience data and collections have become critical issues for industry, federal and state agencies, museums, and universities. Many resources are in imminent danger of being lost through mismanagement, neglect, or disposal. A striking 46 percent of the state geological surveys polled by the committee reported that there is no space available or they have refused to accept new material. In order to address these challenges, Geoscience Data and Collections offers a comprehensive strategy for managing geoscience data and collections in the United States.

MATLAB® Recipes for Earth Sciences
MATLAB® Recipes for Earth Sciences

Author: Martin H. Trauth

Publisher: Springer Nature

Published: 2020-12-02

Total Pages: 526

ISBN-13: 3030384411

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MATLAB® is used in a wide range of geoscientific applications, e.g. for image processing in remote sensing, for creating and processing digital elevation models, and for analyzing time series. This book introduces readers to MATLAB-based data analysis methods used in the geosciences, including basic statistics for univariate, bivariate and multivariate datasets, time-series analysis, signal processing, the analysis of spatial and directional data, and image analysis. The revised and updated Fifth Edition includes seven new sections, and the majority of the chapters have been rewritten and significantly expanded. New sections include error analysis, the problem of classical linear regression of log-transformed data, aligning stratigraphic sequences, the Normalized Difference Vegetation Index, Aitchison’s log-ratio transformation, graphical representation of spherical data, and statistics of spherical data. The book also includes numerous examples demonstrating how MATLAB can be used on datasets from the earth sciences. The supplementary electronic material (available online through SpringerLink) contains recipes that include all the MATLAB commands featured in the book and the sample data.