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Signal and noise in geosciences = MA...

Trauth, Martin H.

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Signal and noise in geosciences = MATLAB recipes for data acquisition in earth sciences /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Signal and noise in geosciences/ by Martin H. Trauth.
Reminder of title:	MATLAB recipes for data acquisition in earth sciences /
Author:	Trauth, Martin H.
Published:	Cham :Springer International Publishing : : 2021.,
Description:	xi, 340 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:	Data Acquisition in Earth Sciences -- Introduction to MATLAB -- MATLAB Programming -- Geometric Properties -- Visible Light Images -- Spectral Imaging -- Acquisition of Elastic Signals -- Gravimetric, Magnetic and Weather Data.
Contained By:	Springer Nature eBook
Subject:	Earth sciences - Data processing. -
Online resource:	https://doi.org/10.1007/978-3-030-74913-2
ISBN:	9783030749132

Signal and noise in geosciences = MATLAB recipes for data acquisition in earth sciences /
Trauth, Martin H.

Signal and noise in geosciencesMATLAB recipes for data acquisition in earth sciences /[electronic resource] :by Martin H. Trauth. - Cham :Springer International Publishing :2021. - xi, 340 p. :ill. (some col.), digital ;24 cm. - Springer textbooks in earth sciences, geography and environment,2510-1315. - Springer textbooks in earth sciences, geography and environment..

Data Acquisition in Earth Sciences -- Introduction to MATLAB -- MATLAB Programming -- Geometric Properties -- Visible Light Images -- Spectral Imaging -- Acquisition of Elastic Signals -- Gravimetric, Magnetic and Weather Data.

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.

ISBN: 9783030749132

Standard No.: 10.1007/978-3-030-74913-2doiSubjects--Uniform Titles:

MATLAB.
Subjects--Topical Terms:

544097
Earth sciences
--Data processing.

LC Class. No.: QE48.8 / .T73 2021

Dewey Class. No.: 550.285

Signal and noise in geosciences = MATLAB recipes for data acquisition in earth sciences /
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505 0 $a Data Acquisition in Earth Sciences -- Introduction to MATLAB -- MATLAB Programming -- Geometric Properties -- Visible Light Images -- Spectral Imaging -- Acquisition of Elastic Signals -- Gravimetric, Magnetic and Weather Data.
520 $a 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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