Data Visualization in the Geological Sciences
Author: James R. Carr
Publisher:
Published: 2002
Total Pages: 292
ISBN-13:
DOWNLOAD EBOOKCD-ROM contains: Visual_Data -- Data files used in text -- Digital images used in text.
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Earth Systems Data Processing and Visualization Using MATLAB
Author: Zekâi Şen
Publisher:
Published: 2020
Total Pages: 277
ISBN-13: 9783030015435
DOWNLOAD EBOOKThis book is designed to provide easy means of problem solving based on the science philosophical and logical rules that lead to effective and reliable software at the service of professional earth system scientists through numerical scientific computation techniques. Through careful examination of software illuminated by brief scientific explanations given in the book the reader may develop his/her skills of computer program writing. Science aspects that are concerned with earth systems need numerical computation procedures and algorithms of data collected from the field measurements or laboratory records. The same is also valid for data processing in social sciences and economics. Some of the data assessment and processing procedures are at the large scales and complex, and therefore, require effective and efficient computer programs. Data reduction and graphical display in addition to probabilistic and statistical calculations are among the general purposes of the book. Not only students works but also projects of researchers at universities and tasks of experts in different companies depend on reliable software. Especially, potential users of MATLAB in earth systems need a guidance book that covers a variety of practically applicable software solutions.
Introduction to Python in Earth Science Data Analysis
Author: Maurizio Petrelli
Publisher: Springer Nature
Published: 2021-09-16
Total Pages: 229
ISBN-13: 3030780554
DOWNLOAD EBOOKThis textbook introduces the use of Python programming for exploring and modelling data in the field of Earth Sciences. It drives the reader from his very first steps with Python, like setting up the environment and starting writing the first lines of codes, to proficient use in visualizing, analyzing, and modelling data in the field of Earth Science. Each chapter contains explicative examples of code, and each script is commented in detail. The book is minded for very beginners in Python programming, and it can be used in teaching courses at master or PhD levels. Also, Early careers and experienced researchers who would like to start learning Python programming for the solution of geological problems will benefit the reading of the book.
Collecting, Processing and Presenting Geoscientific Information
Author: Martin H. Trauth
Publisher: Springer
Published: 2018-03-26
Total Pages: 286
ISBN-13: 3662562030
DOWNLOAD EBOOKThis second edition is an intensively revised and updated version of the book MATLAB® 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.
Planet Earth
Author: Chiara Piroddi
Publisher: White Star Kids
Published: 2018-03-15
Total Pages: 0
ISBN-13: 9788854412460
DOWNLOAD EBOOKKids can explore Earth's secrets with this guide featuring cool infographics, colorful illustrations, and scientific data. Sixteen different plates illuminate everything from the atmosphere to the ocean depths, icy tundra to hot deserts, and tiny bugs to gigantic elephants. Full color.
R for Data Science
Author: Hadley Wickham
Publisher: "O'Reilly Media, Inc."
Published: 2016-12-12
Total Pages: 521
ISBN-13: 1491910364
DOWNLOAD EBOOKLearn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you've learned along the way. You'll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results
Big Data for Remote Sensing: Visualization, Analysis and Interpretation
Author: Nilanjan Dey
Publisher: Springer
Published: 2018-05-23
Total Pages: 163
ISBN-13: 3319899236
DOWNLOAD EBOOKThis book thoroughly covers the remote sensing visualization and analysis techniques based on computational imaging and vision in Earth science. Remote sensing is considered a significant information source for monitoring and mapping natural and man-made land through the development of sensor resolutions that committed different Earth observation platforms. The book includes related topics for the different systems, models, and approaches used in the visualization of remote sensing images. It offers flexible and sophisticated solutions for removing uncertainty from the satellite data. It introduces real time big data analytics to derive intelligence systems in enterprise earth science applications. Furthermore, the book integrates statistical concepts with computer-based geographic information systems (GIS). It focuses on image processing techniques for observing data together with uncertainty information raised by spectral, spatial, and positional accuracy of GPS data. The book addresses several advanced improvement models to guide the engineers in developing different remote sensing visualization and analysis schemes. Highlights on the advanced improvement models of the supervised/unsupervised classification algorithms, support vector machines, artificial neural networks, fuzzy logic, decision-making algorithms, and Time Series Model and Forecasting are addressed. This book guides engineers, designers, and researchers to exploit the intrinsic design remote sensing systems. The book gathers remarkable material from an international experts' panel to guide the readers during the development of earth big data analytics and their challenges.
Earth Observation Using Python
Author: Rebekah B. Esmaili
Publisher: John Wiley & Sons
Published: 2021-08-24
Total Pages: 308
ISBN-13: 1119606888
DOWNLOAD EBOOKLearn basic Python programming to create functional and effective visualizations from earth observation satellite data sets Thousands of satellite datasets are freely available online, but scientists need the right tools to efficiently analyze data and share results. Python has easy-to-learn syntax and thousands of libraries to perform common Earth science programming tasks. Earth Observation Using Python: A Practical Programming Guide presents an example-driven collection of basic methods, applications, and visualizations to process satellite data sets for Earth science research. Gain Python fluency using real data and case studies Read and write common scientific data formats, like netCDF, HDF, and GRIB2 Create 3-dimensional maps of dust, fire, vegetation indices and more Learn to adjust satellite imagery resolution, apply quality control, and handle big files Develop useful workflows and learn to share code using version control Acquire skills using online interactive code available for all examples in the book The American Geophysical Union promotes discovery in Earth and space science for the benefit of humanity. Its publications disseminate scientific knowledge and provide resources for researchers, students, and professionals. Find out more about this book from this Q&A with the Author
Data Visualization
Author: Kieran Healy
Publisher: Princeton University Press
Published: 2018-12-18
Total Pages: 292
ISBN-13: 0691181624
DOWNLOAD EBOOKAn accessible primer on how to create effective graphics from data This book provides students and researchers a hands-on introduction to the principles and practice of data visualization. It explains what makes some graphs succeed while others fail, how to make high-quality figures from data using powerful and reproducible methods, and how to think about data visualization in an honest and effective way. Data Visualization builds the reader’s expertise in ggplot2, a versatile visualization library for the R programming language. Through a series of worked examples, this accessible primer then demonstrates how to create plots piece by piece, beginning with summaries of single variables and moving on to more complex graphics. Topics include plotting continuous and categorical variables; layering information on graphics; producing effective “small multiple” plots; grouping, summarizing, and transforming data for plotting; creating maps; working with the output of statistical models; and refining plots to make them more comprehensible. Effective graphics are essential to communicating ideas and a great way to better understand data. This book provides the practical skills students and practitioners need to visualize quantitative data and get the most out of their research findings. Provides hands-on instruction using R and ggplot2 Shows how the “tidyverse” of data analysis tools makes working with R easier and more consistent Includes a library of data sets, code, and functions
Foundations of Data Visualization
Author: Min Chen
Publisher: Springer Nature
Published: 2020-08-11
Total Pages: 395
ISBN-13: 3030344444
DOWNLOAD EBOOKThis is the first book that focuses entirely on the fundamental questions in visualization. Unlike other existing books in the field, it contains discussions that go far beyond individual visual representations and individual visualization algorithms. It offers a collection of investigative discourses that probe these questions from different perspectives, including concepts that help frame these questions and their potential answers, mathematical methods that underpin the scientific reasoning of these questions, empirical methods that facilitate the validation and falsification of potential answers, and case studies that stimulate hypotheses about potential answers while providing practical evidence for such hypotheses. Readers are not instructed to follow a specific theory, but their attention is brought to a broad range of schools of thoughts and different ways of investigating fundamental questions. As such, the book represents the by now most significant collective effort for gathering a large collection of discourses on the foundation of data visualization. Data visualization is a relatively young scientific discipline. Over the last three decades, a large collection of computer-supported visualization techniques have been developed, and the merits and benefits of using these techniques have been evidenced by numerous applications in practice. These technical advancements have given rise to the scientific curiosity about some fundamental questions such as why and how visualization works, when it is useful or effective and when it is not, what are the primary factors affecting its usefulness and effectiveness, and so on. This book signifies timely and exciting opportunities to answer such fundamental questions by building on the wealth of knowledge and experience accumulated in developing and deploying visualization technology in practice.
