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E-raamat: Signal and Noise in Geosciences: MATLAB(R) Recipes for Data Acquisition in Earth Sciences

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Signal and Noise in Geosciences: MATLAB(R) Recipes for Data Acquisition in Earth SciencesSuurem pilt
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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.

1 Data Acquisition in Earth Sciences
1(14)
1.1 Introduction
1(3)
1.2 Methods of Data Acquisition
4(5)
1.3 Classroom-Sized Earth Science Experiments
9(4)
Recommended Reading
13(2)
2 Introduction to MATLAB
15(32)
2.1 MATLAB in Earth Sciences
15(1)
2.2 Getting Started
16(2)
2.3 The Syntax
18(5)
2.4 Array Manipulation
23(5)
2.5 Basic Visualization Tools
28(3)
2.6 Generating Code to Recreate Graphics
31(2)
2.7 Publishing and Sharing MATLAB Code
33(3)
2.8 Exercises
36(9)
2.8.1 Getting Started with MATLAB
36(1)
2.8.2 Using MATLAB Help and Docs
37(1)
2.8.3 Creating a Simple MATLAB Script
38(2)
2.8.4 Creating Graphics with MATLAB
40(2)
2.8.5 Collaborative Coding with MATLAB
42(3)
Recommended Reading
45(2)
3 MATLAB Programming
47(60)
3.1 Introduction to Programming
47(1)
3.2 Data Types in MATLAB
48(14)
3.3 Data Storage and Handling
62(10)
3.4 Control Flow
72(4)
3.5 Scripts and Functions
76(4)
3.6 Creating Graphical User Interfaces
80(6)
3.7 Exercises
86(19)
3.7.1 Communicating with the LEGO MINDSTORMS EV3 Brick
86(3)
3.7.2 Controlling EV3 Motors Using an Ultrasonic Sensor
89(6)
3.7.3 Reading Complex Text Files with MATLAB
95(3)
3.7.4 Smartphone Sensors with MATLAB Mobile
98(4)
3.7.5 Smartphone GPS Tracking with MATLAB Mobile
102(3)
Recommended Reading
105(2)
4 Geometric Properties
107(46)
4.1 Introduction
107(1)
4.2 Position on the Earth's Surface
108(3)
4.3 Digital Elevation Models of the Earth's Surface
111(4)
4.4 Gridding and Contouring
115(6)
4.5 Exercises
121(31)
4.5.1 Dip and Dip Direction of Planar Features Using Smartphone Sensors
121(6)
4.5.2 Precision and Accuracy of Ultrasonic Distance Measurements
127(6)
4.5.3 Spatial Resolution of the LEGO EV3 Ultrasonic Sensor
133(7)
4.5.4 Object Scanning with the LEGO EV3 Ultrasonic Sensor
140(5)
4.5.5 Point Clouds from Multiple Smartphone Images
145(7)
Recommended Reading
152(1)
5 Visible Light Images
153(52)
5.1 Introduction
153(1)
5.2 Visible Electromagnetic Waves
154(1)
5.3 Acquiring Visible Digital Images
155(2)
5.4 Storing Images on a Computer
157(4)
5.5 Processing Images on a Computer
161(7)
5.6 Image Enhancement, Correction and Rectification
168(8)
5.7 Exercises
176(27)
5.7.1 Smartphone Camera/Webcam Images with MATLAB
176(4)
5.7.2 Enhancing, Rectifying and Referencing Images
180(4)
5.7.3 Stitching Multiple Smartphone Images
184(4)
5.7.4 Spatial Resolution of the LEGO EV3 Color Sensor
188(9)
5.7.5 Scanning Images Using the LEGO EV3 Color Sensor
197(6)
Recommended Reading
203(2)
6 Spectral Imaging
205(50)
6.1 Introduction
205(1)
6.2 Visible to Thermal Electromagnetic Radiation
206(1)
6.3 Acquiring Spectral Images
207(1)
6.4 Storing Spectral Images on a Computer
208(4)
6.5 Processing Spectral Images on a Computer
212(4)
6.6 Exercises
216(37)
6.6.1 Infrared Spectrometry of Landscapes
216(4)
6.6.2 Using Spectral Cameras in a Botanic Garden
220(10)
6.6.3 Using RGB Cameras to Classify Minerals in Rocks
230(6)
6.6.4 Using Spectral Cameras to Classify Minerals in Rocks
236(10)
6.6.5 Thermal Imaging in a Roof Garden
246(7)
Recommended Reading
253(2)
7 Acquisition of Elastic Signals
255(46)
7.1 Introduction
255(1)
7.2 Earth's Elastic Properties
256(2)
7.3 Acquiring Elastic Signals
258(1)
7.4 Storing and Processing Elastic Signals
259(6)
7.5 Exercises
265(35)
7.5.1 Smartphone Seismometer
266(3)
7.5.2 Smartphone Sonar for Distance Measurement
269(5)
7.5.3 Use of Stereo Microphones to Locate a Sound Source
274(8)
7.5.4 Sound in Time and Frequency Domains
282(10)
7.5.5 Distortion of a Harmonic Signal
292(8)
Recommended Reading
300(1)
8 Gravimetric, Magnetic and Weather Data
301
8.1 Introduction
301(1)
8.2 Earth's Gravity Field, Magnetic Field and Weather
302(2)
8.3 Acquiring Gravimetric, Magnetic and Weather Data
304(2)
8.4 Storing Gravimetric, Magnetic and Weather Data
306(2)
8.5 Exercises
308(31)
8.5.1 Measuring the Density of Minerals
309(4)
8.5.2 Gravitational Acceleration
313(3)
8.5.3 Position, Velocity and Acceleration
316(6)
8.5.4 LEGO-Smartphone Magnetic Survey
322(7)
8.5.5 ThingSpeak Weather Station
329(10)
Recommended Reading
339
Martin H. Trauth studied geophysics and geology at the University of Karlsruhe. He obtained a doctoral degree from the University of Kiel in 1995 and then became a permanent member of the scientific staff at the University of Potsdam. Following his habilitation in 2003 he became a lecturer, and then in 2011 a titular professor at the University of Potsdam. Since 1990 he has worked on various aspects of past changes in the climates of East Africa and South America. His projects have aimed to understand the role of the tropics in terminating ice ages, the relationship between climatic changes and human evolution, and the influence that climate anomalies had on mass movements in the central Andes. Each of these projects has involved the use of MATLAB to apply numerical and statistical methods (such as time-series analysis and signal processing) to paleoclimate time series, lake-balance modeling, stochastic modeling of bioturbation, age-depth modeling of sedimentary sequences, and the processing of satellite and microscope images. Martin H. Trauth has been teaching a variety of courses on data analysis in earth sciences with MATLAB for more than 25 years, both at the University of Potsdam and other universities around the world.
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