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Time Series Modelling In Earth Sciences

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Time Series Modelling In Earth Sciences

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Author : B.K. Sahu
language : en
Publisher: CRC Press
Release Date : 2021-07-01

Time Series Modelling In Earth Sciences written by B.K. Sahu and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-01 with Technology & Engineering categories.

Including the latest theories and applications of time series modelling, this book is intended for students, faculties and professionals with a background in multivariate statistics. Highlighting linear methods to yield ARIMA, SARIMA models and their multivariate (vector) extensions, the text also draws attention to non-linear methods, as well as state-space, dynamic linear, wavelet, volatility and long memory models. Also included are several solved case studies and exercises from the fields of mining, ore genesis, earthquakes, and climatology.

Geodetic Time Series Analysis In Earth Sciences

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Author : Jean-Philippe Montillet
language : en
Publisher: Springer
Release Date : 2019-08-16

Geodetic Time Series Analysis In Earth Sciences written by Jean-Philippe Montillet and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-08-16 with Science categories.

This book provides an essential appraisal of the recent advances in technologies, mathematical models and computational software used by those working with geodetic data. It explains the latest methods in processing and analyzing geodetic time series data from various space missions (i.e. GNSS, GRACE) and other technologies (i.e. tide gauges), using the most recent mathematical models. The book provides practical examples of how to apply these models to estimate seal level rise as well as rapid and evolving land motion changes due to gravity (ice sheet loss) and earthquakes respectively. It also provides a necessary overview of geodetic software and where to obtain them.

Advanced Time Series Analysis In Geosciences

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Author : Flavio Cannavo’
language : en
Publisher: Frontiers Media SA
Release Date : 2021-05-12

Advanced Time Series Analysis In Geosciences written by Flavio Cannavo’ and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-12 with Science categories.

Time Series Modelling In Earth Sciences

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Author : B.K. Sahu
language : en
Publisher: CRC Press
Release Date : 2003-01-01

Matlab Recipes For Earth Sciences

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Author : Martin H. Trauth
language : en
Publisher: Springer
Release Date : 2015-02-17

Matlab Recipes For Earth Sciences written by Martin H. Trauth and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-02-17 with Science categories.

MATLAB® 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.

Spatial Modeling Principles In Earth Sciences

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Author : Zekai Sen
language : en
Publisher: Springer
Release Date : 2016-10-04

Spatial Modeling Principles In Earth Sciences written by Zekai Sen and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-10-04 with Science categories.

This is a revised and updated second edition, including new chapters on temporal and point uncertainty model, as well as on sampling and deterministic modeling. It is a comprehensive presentation of spatial modeling techniques used in the earth sciences, outlining original techniques developed by the author. Data collection in the earth sciences is difficult and expensive, but simple, rational and logical approaches help the reader to appreciate the fundamentals of advanced methodologies. It requires special care to gather accurate geological, hydrogeological, meteorological and hydrological information all with risk assessments. Spatial simulation methodologies in the earth sciences are essential, then, if we want to understand the variability in features such as fracture frequencies, rock quality, and grain size distribution in rock and porous media. This book outlines in a detailed yet accessible way the main spatial modeling techniques, in particular the Kriging methodology. It also presents many unique physical approaches, field cases, and sample interpretations. Since Kriging’s origin in the 1960s it has been developed into a number of new methods such as cumulative SV (CSV), point CSV (PCSV), and spatial dependence function, which have been applied in different aspects of the earth sciences. Each one of these techniques is explained in this book, as well as how they are used to model earth science phenomena such as geology, earthquakes, meteorology, and hydrology. In addition to Kriging and its variants, several alternatives to Kriging methodology are presented and the necessary steps in their applications are clearly explained. Simple spatial variation prediction methodologies are also revised with up-to-date literature, and the ways in which they relate to more advanced spatial modeling methodologies are explained. The book is a valuable resource for students, researchers and professionals of a broad range of disciplines including geology, geography, hydrology, meteorology, environment, image processing, spatial modeling and related topics. Keywords »Data mining - Geo-statistics - Kriging - Regional uncertainty - Spatial dependence - Spatial modeling - geographic data - geoscience - hydrology - image processing

Random Field Models In Earth Sciences

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Author : George Christakos
language : en
Publisher: Elsevier
Release Date : 2013-10-22

Random Field Models In Earth Sciences written by George Christakos and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-10-22 with Science categories.

This book is about modeling as a prinicipal component of scientific investigations. In general terms, modeling is the funamental process of combining intellectual creativity with physical knowledge and mathematical techniques in order to learn the properties of the mechanisms underlying a physical phenomenon and make predictions. The book focuses on a specific class of models, namely, random field models and certain of their physical applications in the context of a stochastic data analysis and processing research program. The term application is considered here in the sense wherein the mathematical random field model is shaping, but is also being shaped by, its objects.This book explores the application of random field models and stochastic data processing to problems in hydrogeology, geostatistics, climate modeling, and oil reservoir engineering, among others Researchers in the geosciences who work with models of natural processes will find discussion of; - Spatiotemporal random fields - Space transformation - Multidimensional estimation - Simulation - Sampling design - Stochastic partial differential equations

Matlab Recipes For Earth Sciences

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Author : Martin Trauth
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-06-26

Matlab Recipes For Earth Sciences written by Martin Trauth and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-06-26 with Science categories.

MATLAB® 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, 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. The revised and updated Third Edition includes ten new sections and has greatly expanded on most chapters from the previous edition, including a step by step discussion of all methods before demonstrating the methods with MATLAB functions. New sections include: Data Storage and Handling, Data Structures and Classes of Objects, Generating M-Files to Regenerate Graphs, Publishing M-Files, Distribution Fitting, Nonlinear and Weighted Regression, Color-Intensity Transects of Varved Sediments, and Grain Size Analysis from Microscope Images. The text includes numerous examples demonstrating how MATLAB can be used on data sets from earth sciences. All MATLAB recipes can be easily modified in order to analyse the reader's own data sets.

Quantitative Analysis And Modeling Of Earth And Environmental Data

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Author : Jiaping Wu
language : en
Publisher: Elsevier
Release Date : 2021-12-04

Quantitative Analysis And Modeling Of Earth And Environmental Data written by Jiaping Wu and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-04 with Science categories.

Quantitative Analysis and Modeling of Earth and Environmental Data: Space-Time and Spacetime Data Considerations introduces the notion of chronotopologic data analysis that offers a systematic, quantitative analysis of multi-sourced data and provides information about the spatial distribution and temporal dynamics of natural attributes (physical, biological, health, social). It includes models and techniques for handling data that may vary by space and/or time, and aims to improve understanding of the physical laws of change underlying the available numerical datasets, while taking into consideration the in-situ uncertainties and relevant measurement errors (conceptual, technical, computational). It considers the synthesis of scientific theory-based methods (stochastic modeling, modern geostatistics) and data-driven techniques (machine learning, artificial neural networks) so that their individual strengths are combined by acting symbiotically and complementing each other. The notions and methods presented in Quantitative Analysis and Modeling of Earth and Environmental Data: Space-Time and Spacetime Data Considerations cover a wide range of data in various forms and sources, including hard measurements, soft observations, secondary information and auxiliary variables (ground-level measurements, satellite observations, scientific instruments and records, protocols and surveys, empirical models and charts). Including real-world practical applications as well as practice exercises, this book is a comprehensive step-by-step tutorial of theory-based and data-driven techniques that will help students and researchers master data analysis and modeling in earth and environmental sciences (including environmental health and human exposure applications). - Explores the analysis and processing of chronotopologic (i.e., space-time and spacetime) data that varies spatially and/or temporally, which is the case with the majority of data in scientific and engineering disciplines - Studies the synthesis of scientific theory and empirical evidence (in its various forms) that offers a mathematically rigorous and physically meaningful assessment of real-world phenomena - Covers a wide range of data describing a variety of attributes characterizing physical phenomena and systems including earth, ocean and atmospheric variables, environmental and ecological parameters, population health states, disease indicators, and social and economic characteristics - Includes case studies and practice exercises at the end of each chapter for both real-world applications and deeper understanding of the concepts presented

Geostatistics With Applications In Earth Sciences

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Author : D.D. Sarma
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-09-30

Geostatistics With Applications In Earth Sciences written by D.D. Sarma and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-09-30 with Science categories.

Geostatistics is expanding very fast: concept- and technique-wise. Keeping in view the importance of the subject, it was thought appropriate to bring out the second edition of this book. In this process, Chapter I has been expanded In Chapter 2, incorporating more details on sampling and sampling designs. a section on simulation has been introduced with emphasis on Monte-Carlo simulation with worked out examples. In Chapter 5, a procedure to compute variogram in the case of irregular grid has been outlined. Minor modifications have been made in all other chapters. A new chapter on Introduction to Advanced Geostatistics has been introduced with discussions on universal kriging, disjunctive kriging, conditional simulation and median polish kriging. Review Questions are given at the end of each chapter to facilitate a better understanding of the subject by the student/practitioner. The software codes are put in a CD for convenience of the students/practitoner of geostatistics. A few additions have been made in the bibliography making it more exhaustive. This contains references to the concepts and methods presented, in-depth treatment of related topics and possible extensions. My grateful thanks are due to Dr. B.S. Saini, Principal, Guru Nanak Engg. College, Hyderabad for very helpful support. I hope that this edition will be a welcome one.

Time Series Modelling In Earth Sciences

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