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This second edition is an intensively revised and updated version
of the book MATLAB (R) 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.
This second edition is an intensively revised and updated version
of the book MATLAB (R) 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 (R) is used for a wide range of applications in geosciences,
such as image processing in remote sensing, the generation and
processing of digital elevation models and the analysis of time
series. This book introduces methods of data analysis in
geosciences using MATLAB, such as 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 Fourth Edition includes sixteen
new sections and most chapters have greatly been expanded so that
they now include a step by step discussion of all methods before
demonstrating the methods with MATLAB functions. New sections
include: Array Manipulation; Control Flow; Creating Graphical User
Interfaces; Hypothesis Testing; Kolmogorov-Smirnov Test;
Mann-Whitney Test; Ansari-Bradley Test; Detecting Abrupt
Transitions in Time Series; Exporting 3D Graphics to Create
Interactive Documents; Importing, Processing and Exporting LANDSAT
Images; Importing and Georeferencing TERRA ASTER Images; Processing
and Exporting EO-1 Hyperion Images; Image Enhancement; Correction
and Rectification; Shape-Based Object Detection in Images;
Discriminant Analysis; and Multiple Linear Regression. The text
includes numerous examples demonstrating how MATLAB can be used on
data sets from earth sciences. The book's supplementary electronic
material (available online through Springer Link) includes recipes
that include all the MATLAB commands featured in the book and the
example data.
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.
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.
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