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  • 1
    Call number: 19/M 12.0303 ; M 12.0304
    Description / Table of Contents: 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.
    Type of Medium: Monograph available for loan
    Pages: XI, 292 S. , 100 schw.-w. Ill., 25 farb. Ill. , 235 mm x 155 mm
    ISBN: 9783642325434
    Classification:
    Mathematics
    Location: Reading room
    Location: Upper compact magazine
    Branch Library: GFZ Library
    Branch Library: GFZ Library
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  • 2
    Monograph available for loan
    Monograph available for loan
    Potsdam
    Call number: AWI A3-04-0109
    Type of Medium: Monograph available for loan
    Pages: 122 Bl.
    Branch Library: AWI Library
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  • 3
    Call number: PIK M 102-08-0153 ; PIK M 102-08-0257 ; 19/M 10.0047 ; AWI S1-10-0005
    Type of Medium: Monograph available for loan
    Pages: XII, 288 Seiten , Illustrationen, Diagramme, Karten , 1 CD-ROM (12 cm)
    Edition: Second edition
    ISBN: 3540727485 , 978-3-540-72748-4
    Language: English
    Note: Contents Preface 1 Data Analysis in Earth Sciences 1.1 Introduction 1.2 Collecting Data 1.3 Types of Data 1.4 Methods of Data Analysis Recommended Reading 2 Introduction to MATLAB 2.1 MATLAB in Earth Sciences 2.2 Getting Started 2.3 The Syntax 2.4 Data Storage 2.5 Data Handling 2.6 Scripts and Functions 2.7 Basic Visualization Tools Recommended Reading 3 Univariate Statistics 3.1 Introduction 3.2 Empirical Distributions Measures of Central Tendency Measures of Dispersion 3.3 Example of Empirical Distributions 3.4 Theoretical Distributions Uniform Distribution Binomial or Bernoulli Distribution Poisson Distribution Normal or Gaussian Distribution Logarithmic Normal or Log-Normal Distribution Student's t Distribution Fisher's F Distribution Χ2 or Chi-Squared Distribution 3.5 Example ofTheoretical Distributions 3.6 Thet-Test 3.7 TheF-Test 3.8 The Χ2-Test Recommended Reading 4 Bivariate Statistics 4.1 Introduction 4.2 Pearson's Correlation Coefficient 4.3 Classical Linear Regression Analysis and Prediction 4.4 Analyzing the Residuals 4.5 Bootstrap Estimates of the Regression Coefficients 4.6 Jackknife Estimates of the Regression Coefficients 4.7 Cross Validation 4.8 Reduced Major Axis Regression 4.9 Curvilinear Regression Recommended Reading 5 Time-Series Analysis 5.1 Introduction 5.2 Generating Signals 5.3 Blackman-Tukey Autospectral Analysis 5.4 Blackman-Tukey Crossspectral Analysis 5.5 Interpolating and Analyzing Unevenly-Spaced Data 5.6 Evolutionary Blackman-Tukey Powerspectrum 5.7 Lomb-Scargle Powerspectrum 5.8 Wavelet Powerspectrum 5.9 Nonlinear Time-Series Analysis (by N. Marwarn) Phase Space Portrait Recurrence Plots Recommended Reading 6 Signal Processing 6.1 Introduction 6.2 Generating Signals 6.3 Linear Time-Invariant Systems 6.4 Convolution and Filtering 6.5 Comparing Functions for Filtering Data Series 6.6 Recursive and Nonrecursive Filters 6.7 Impulse Response 6.8 Frequency Response 6.9 Filter Design 6.10 Adaptive Filtering Recommended Reading 7 Spatial Data 7.1 Types of Spatial Data 7.2 The GSHHS Shoreline Data Set 7.3 The 2-Minute Gridded Global Elevation Data ETOPO2 7.4 The 30-Arc Seconds Elevation Model GTOPO30 7.5 The Shuttle Radar Topography Mission SRTM 7.6 Gridding and Contouring Background 7.7 Gridding Example 7.8 Comparison of Methods and Potential Artifacts 7.9 Statistics of Point Distributions Test for Uniform Distribution Test for Random Distribution Test for Clustering 7.10 Analysis of Digital Elevation Models (by R. Gebbers) 7.11 Geostatistics and Kriging (by R. Gebbers) Theorical Background Preceding Analysis Variography with the Classical Variogram Kriging Discussion of Kriging Recommended Reading 8 Image Processing 8.1 Introduction 8.2 Datastorage 8.3 Importing, Processing and Exporting Images 8.4 Importing, Processing and Exporting Satellite Images 8.5 Georeferencing Satellite Images 8.6 Digitizing from the Screen Recommended Reading 9 Multivariate Statistics 9.1 Introduction 9.2 Principal Component Analysis 9.3 Independent Component Analysis (by N. Marwan) 9.4 Cluster Analysis Recommended Reading 10 Statistics on Directional Data 10.1 Introduction 10.2 Graphical Representation 10.3 Empirical Distributions 10.4 Theoretical Distributions 10.5 Test for Randomness of Directional Data 10.6 Test for the Significance of a Mean Direction 10.7 Test for the Difference of Two Sets of Directions Recommended Reading General Index
    Location: A 18 - must be ordered
    Location: A 18 - must be ordered
    Location: Reading room
    Location: Reading room
    Branch Library: PIK Library
    Branch Library: PIK Library
    Branch Library: GFZ Library
    Branch Library: AWI Library
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  • 4
    Call number: 9783030749132 (e-book)
    Description / Table of Contents: 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.
    Type of Medium: 12
    Pages: 1 Online-Ressource (xi, 340 Seiten) , Illustrationen, Diagramme
    ISBN: 9783030749132 , 978-3-030-74913-2
    ISSN: 2510-1307 , 2510-1315
    Series Statement: Springer Textbooks in Earth Sciences, Geography and Environment
    Language: English
    Note: Contents 1 Data Acquisition in Earth Sciences 1.1 Introduction 1.2 Methods of Data Acquisition 1.3 Classroom-Sized Earth Science Experiments Recommended Reading 2 Introduction to MATLAB 2.1 MATLAB in Earth Sciences 2.2 Getting Started 2.3 The Syntax 2.4 Array Manipulation 2.5 Basic Visualization Tools 2.6 Generating Code to Recreate Graphics 2.7 Publishing and Sharing MATLAB Code 2.8 Exercises 2.8.1 Getting Started with MATLAB 2.8.2 Using MATLAB Help and Docs 2.8.3 Creating a Simple MATLAB Script 2.8.4 Creating Graphics with MATLAB 2.8.5 Collaborative Coding with MATLAB Recommended Reading 3 MATLAB Programming 3.1 Introduction to Programming 3.2 Data Types in MATLAB 3.3 Data Storage and Handling 3.4 Control Flow 3.5 Scripts and Functions 3.6 Creating Graphical User Interfaces 3.7 Exercises . 3.7.1 Communicating with the LEGO MINDSTORMS EV3 Brick 3.7.2 Controlling EV3 Motors Using an Ultrasonic Sensor 3.7.3 Reading Complex Text Files with MATLAB 3.7.4 Smartphone Sensors with MATLAB Mobile 3.7.5 Smartphone GPS Tracking with MATLAB Mobile Recommended Reading 4 Geometric Properties 4.1 Introduction 4.2 Position on the Earth’s Surface 4.3 Digital Elevation Models of the Earth’s Surface 4.4 Gridding and Contouring 4.5 Exercises 4.5.1 Dip and Dip Direction of Planar Features Using Smartphone Sensors 4.5.2 Precision and Accuracy of Ultrasonic Distance Measurements 4.5.3 Spatial Resolution of the LEGO EV3 Ultrasonic Sensor 4.5.4 Object Scanning with the LEGO EV3 Ultrasonic Sensor 4.5.5 Point Clouds from Multiple Smartphone Images Recommended Reading 5 Visible Light Images 5.1 Introduction 5.2 Visible Electromagnetic Waves 5.3 Acquiring Visible Digital Images 5.4 Storing Images on a Computer 5.5 Processing Images on a Computer 5.6 Image Enhancement, Correction and Rectification 5.7 Exercises 5.7.1 Smartphone Camera/Webcam Images with MATLAB 5.7.2 Enhancing, Rectifying and Referencing Images 5.7.3 Stitching Multiple Smartphone Images 5.7.4 Spatial Resolution of the LEGO EV3 Color Sensor 5.7.5 Scanning Images Using the LEGO EV3 Color Sensor Recommended Reading 6 Spectral Imaging 6.1 Introduction 6.2 Visible to Thermal Electromagnetic Radiation 6.3 Acquiring Spectral Images 6.4 Storing Spectral Images on a Computer 6.5 Processing Spectral Images on a Computer 6.6 Exercises 6.6.1 Infrared Spectrometry of Landscapes 6.6.2 Using Spectral Cameras in a Botanic Garden 6.6.3 Using RGB Cameras to Classify Minerals in Rocks 6.6.4 Using Spectral Cameras to Classify Minerals in Rocks 6.6.5 Thermal Imaging in a Roof Garden Recommended Reading 7 Acquisition of Elastic Signals 7.1 Introduction 7.2 Earth’s Elastic Properties 7.3 Acquiring Elastic Signals 7.4 Storing and Processing Elastic Signals 7.5 Exercises 7.5.1 Smartphone Seismometer 7.5.2 Smartphone Sonar for Distance Measurement 7.5.3 Use of Stereo Microphones to Locate a Sound Source 7.5.4 Sound in Time and Frequency Domains 7.5.5 Distortion of a Harmonic Signal Recommended Reading 8 Gravimetric, Magnetic and Weather Data 8.1 Introduction 8.2 Earth’s Gravity Field, Magnetic Field and Weather 8.3 Acquiring Gravimetric, Magnetic and Weather Data 8.4 Storing Gravimetric, Magnetic and Weather Data 8.5 Exercises 8.5.1 Measuring the Density of Minerals 8.5.2 Gravitational Acceleration 8.5.3 Position, Velocity and Acceleration 8.5.4 LEGO-Smartphone Magnetic Survey 8.5.5 ThingSpeak Weather Station Recommended Reading
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  • 5
    Call number: 9/M 05.0597
    Type of Medium: Monograph available for loan
    Pages: XI, 272 S. : zahlr. farb. Ill. und graph. Darst. + 1 CD-ROM
    ISBN: 354029144X
    Classification:
    Regional Geology
    Location: Reading room
    Branch Library: GFZ Library
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  • 6
    Monograph available for loan
    Monograph available for loan
    Cham : Springer
    Call number: M 23.95151
    Description / Table of Contents: 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.
    Type of Medium: Monograph available for loan
    Pages: XII, 453 Seiten , Illustrationen
    ISBN: 9783031077180
    Series Statement: Springer textbooks in earth sciences, geography and environment
    Language: English
    Note: Data Analysis in the Earth Sciences.- Introduction to Python.- Univariate Statistics.- Bivariate Statistics.- Time Series Analysis.- Signal Processing.- Spatial Data.- Image Processing.- Multivariate Statistics.- Directional Data.
    Location: Upper compact magazine
    Branch Library: GFZ Library
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  • 7
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    Cham : Springer Nature
    Call number: 9783030384418 (e-book)
    Description / Table of Contents: 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.
    Type of Medium: 12
    Pages: 1 Online-Ressource (xii, 517 Seiten) , Illustrationen
    Edition: Fifth edition
    ISBN: 9783030384418 , 978-3-030-38441-8
    ISSN: 2510-1307 , 2510-1315
    Series Statement: Springer Textbooks in Earth Sciences, Geography and Environment
    Language: English
    Note: Contents 1 Data Analysis in Earth Sciences 1.1 Introduction 1.2 Data Collection 1.3 Types of Data 1.4 Methods of Data Analysis Recommended Reading 2 Introduction to MATLAB 2.1 MATLAB in Earth Sciences 2.2 Getting Started 2.3 The Syntax 2.4 Array Manipulation 2.5 Data Types in MATLAB 2.6 Data Storage and Handling 2.7 Control Flow 2.8 Scripts and Functions 2.9 Basic Visualization Tools 2.10 Generating Code to Recreate Graphics 2.11 Publishing and Sharing MATLAB Code 2.12 Creating Graphical User Interfaces Recommended Reading 3 Univariate Statistics 3.1 Introduction 3.2 Empirical Distributions 3.3 Examples of Empirical Distributions 3.4 Theoretical Distributions 3.5 Examples of Theoretical Distributions 3.6 Hypothesis Testing 3.7 The t-Test 3.8 The F-Test 3.9 The v2-Test 3.10 The Kolmogorov-Smirnov Test 3.11 Mann-Whitney Test 3.12 The Ansari-Bradley Test 3.13 Distribution Fitting 3.14 Error Analysis Recommended Reading 4 Bivariate Statistics 4.1 Introduction 4.2 Correlation Coefficients 4.3 Classical Linear Regression Analysis 4.4 Analyzing the Residuals 4.5 Bootstrap Estimates of the Regression Coefficients 4.6 Jackknife Estimates of the Regression Coefficients 4.7 Cross Validation 4.8 Reduced Major Axis Regression 4.9 Curvilinear Regression 4.10 Nonlinear and Weighted Regression 4.11 Classical Linear Regression of Log-Transformed Data Recommended Reading 5 Time-Series Analysis 5.1 Introduction 5.2 Generating Signals 5.3 Auto-Spectral and Cross-Spectral Analysis 5.4 Examples of Auto-Spectral and Cross-Spectral Analysis 5.5 Interpolating and Analyzing Unevenly-Spaced Data 5.6 Evolutionary Power Spectrum 5.7 Lomb-Scargle Power Spectrum 5.8 Wavelet Power Spectrum 5.9 Detecting Abrupt Transitions in Time Series 5.10 Aligning Stratigraphic Sequences 5.11 Nonlinear Time-Series Analysis (by N. Marwan) Recommended Reading 6 Signal Processing 6.1 Introduction 6.2 Generating Signals 6.3 Linear Time-Invariant Systems 6.4 Convolution, Deconvolution and Filtering 6.5 Comparing Functions for Filtering Data Series 6.6 Recursive and Nonrecursive Filters 6.7 Impulse Response 6.8 Frequency Response 6.9 Filter Design 6.10 Adaptive Filtering Recommended Reading 7 Spatial Data 7.1 Types of Spatial Data 7.2 The Global Geography Database GSHHG 7.3 The 1 Arc-Minute Gridded Global Relief Data ETOPO1 7.4 The 30 Arc-Seconds Elevation Model GTOPO30 7.5 The Shuttle Radar Topography Mission SRTM 7.6 Exporting 3D Graphics to Create Interactive Documents 7.7 Gridding and Contouring 7.8 Comparison of Methods and Potential Artifacts 7.9 Statistics of Point Distributions 7.10 Analysis of Digital Elevation Models (by R. Gebbers) 7.11 Geostatistics and Kriging (by R. Gebbers) Recommended Reading 8 Image Processing 8.1 Introduction 8.2 Data Storage 8.3 Importing, Processing and Exporting Images 8.4 Importing, Processing and Exporting LANDSAT Images 8.5 Importing and Georeferencing TERRA ASTER Images 8.6 Processing and Exporting EO-1 Hyperion Images 8.7 Digitizing from the Screen 8.8 Image Enhancement, Correction and Rectification 8.9 Color-Intensity Transects Across Varved Sediments 8.10 Grain Size Analysis from Microscope Images 8.11 Quantifying Charcoal in Microscope Images 8.12 Shape-Based Object Detection in Images 8.13 The Normalized Difference Vegetation Index Recommended Reading 9 Multivariate Statistics 9.1 Introduction 9.2 Principal Component Analysis 9.3 Independent Component Analysis (by N. Marwan) 9.4 Discriminant Analysis 9.5 Cluster Analysis 9.6 Multiple Linear Regression 9.7 Aitchison’s Log-Ratio Transformation Recommended Reading 10 Directional Data 10.1 Introduction 10.2 Graphical Representation of Circular Data 10.3 Empirical Distributions of Circular Data 10.4 Theoretical Distributions of Circular Data 10.5 Test for Randomness of Circular Data 10.6 Test for the Significance of a Mean Direction 10.7 Test for the Difference between Two Sets of Directions 10.8 Graphical Representation of Spherical Data 10.9 Statistics of Spherical Data Recommended Reading
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  • 8
    Electronic Resource
    Electronic Resource
    Springer
    Mathematical geology 30 (1998), S. 557-574 
    ISSN: 1573-8868
    Keywords: least-mean-squares algorithm ; recursive least-squares algorithm ; signal-to-noise ratio ; inverse modeling
    Source: Springer Online Journal Archives 1860-2000
    Topics: Geosciences , Mathematics
    Notes: Abstract This study demonstrates that adaptive filters can be used successfully to remove noise from duplicate paleoceanographic time-series. Conventional methods for noise canceling such as fixed filters cannot be applied to paleoceanographic time-series if optimal filtering is to be achieved, because the signal-to-noise ratio is unknown and varies with time. In contrast, an adaptive filter automatically extracts information without any prior initialization of the filter parameters. Two basic adaptive filtering methods, the gradient-based stochastic least-mean-squares (LMS) algorithm and the recursive least-squares (RLS) algorithm have been modified for paleoceanographic applications. The RLS algorithm can be used for noise removal from duplicate records corrupted by stationary noise, for example, carbonate measurements, species counts, or density data. The RLS filter performance is characterized by high accuracy and fast rate of convergence. The modified LMS algorithm out-performs the RLS procedure in a nonstationary environment (e.g., stable isotope records) but at the price of a slower rate of convergence and a reduced accuracy in the final estimate. The application of both algorithms is demonstrated by means of carbonate and stable isotope data.
    Type of Medium: Electronic Resource
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  • 9
    Publication Date: 2011-10-13
    Description: High topography in the realm of the rifted East African Plateau is commonly explained by two different mechanisms: (1) rift-flank uplift resulting from mechanical and/or isostatic relaxation and (2) lithospheric uplift due to the impingement of a mantle plume. High topography in East Africa has far-reaching effects on atmospheric circulation systems and the amount and distribution of rainfall in this region. While the climatic and palaeoenvironmental influences of high topography in East Africa are widely accepted, the timing, the magnitude and this spatiotemporal characteristic of changes in topography have remained unclear. This dilemma stems from the lack of datable, geomorphically meaningful reference horizons that could unambiguously record surface uplift. Here, we report on the formation of high topography in East Africa prior to Cenozoic rifting. We infer topographic uplift of the East African Plateau based on the emplacement characteristics of the c. 300 km long and 13.5 Ma Yatta phonolitic lava flow along a former river valley that drained high topography, centred at the present-day rift. The lava flow followed an old riverbed that once routed runoff away from the eastern flank of the plateau. Using a compositional and temperature-dependent viscosity model with subsequent cooling and adjusting for the Yatta lava-flow dimensions and the covered palaeotopography (slope angle), we use the flow as a ‘palaeo-tiltmeter’. Based on these observations and our modelling results, we determine a palaeoslope of the Kenya dome of at least 0.2° prior to rifting and deduce a minimum plateau elevation of 1400 m. We propose that this high topography was caused by thermal expansion of the lithosphere interacting with a heat source generated by a mantle plume. Interestingly, the inferred Mid-Miocene uplift coincides with fundamental palaeoecological changes including the two-step expansion of grasslands in East Africa as well as important radiation and speciation events in tropical Africa.
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  • 10
    Publication Date: 2000-01-01
    Print ISSN: 0022-1376
    Electronic ISSN: 1537-5269
    Topics: Geosciences
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