Download or read book Introduction to Environmental Data Analysis and Modeling written by Moses Eterigho Emetere and published by Springer Nature. This book was released on 2020-01-03 with total page 239 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces numerical methods for processing datasets which may be of any form, illustrating adequately computational resolution of environmental alongside the use of open source libraries. This book solves the challenges of misrepresentation of datasets that are relevant directly or indirectly to the research. It illustrates new ways of screening datasets or images for maximum utilization. The adoption of various numerical methods in dataset treatment would certainly create a new scientific approach. The book enlightens researchers on how to analyse measurements to ensure 100% utilization. It introduces new ways of data treatment that are based on a sound mathematical and computational approach.

Download or read book Introduction to Environmental Data Science written by Jerry Davis and published by CRC Press. This book was released on 2023-03-13 with total page 492 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction to Environmental Data Science focuses on data science methods in the R language applied to environmental research, with sections on exploratory data analysis in R including data abstraction, transformation, and visualization; spatial data analysis in vector and raster models; statistics and modelling ranging from exploratory to modelling, considering confirmatory statistics and extending to machine learning models; time series analysis, focusing especially on carbon and micrometeorological flux; and communication. Introduction to Environmental Data Science is an ideal textbook to teach undergraduate to graduate level students in environmental science, environmental studies, geography, earth science, and biology, but can also serve as a reference for environmental professionals working in consulting, NGOs, and government agencies at the local, state, federal, and international levels. Features • Gives thorough consideration of the needs for environmental research in both spatial and temporal domains. • Features examples of applications involving field-collected data ranging from individual observations to data logging. • Includes examples also of applications involving government and NGO sources, ranging from satellite imagery to environmental data collected by regulators such as EPA. • Contains class-tested exercises in all chapters other than case studies. Solutions manual available for instructors. • All examples and exercises make use of a GitHub package for functions and especially data.

Download or read book Analyzing Environmental Data written by Walter W. Piegorsch and published by John Wiley & Sons. This book was released on 2005-06-10 with total page 512 pages. Available in PDF, EPUB and Kindle. Book excerpt: Environmental statistics is a rapidly growing field, supported by advances in digital computing power, automated data collection systems, and interactive, linkable Internet software. Concerns over public and ecological health and the continuing need to support environmental policy-making and regulation have driven a concurrent explosion in environmental data analysis. This textbook is designed to address the need for trained professionals in this area. The book is based on a course which the authors have taught for many years, and prepares students for careers in environmental analysis centered on statistics and allied quantitative methods of data evaluation. The text extends beyond the introductory level, allowing students and environmental science practitioners to develop the expertise to design and perform sophisticated environmental data analyses. In particular, it: Provides a coherent introduction to intermediate and advanced methods for modeling and analyzing environmental data. Takes a data-oriented approach to describing the various methods. Illustrates the methods with real-world examples Features extensive exercises, enabling use as a course text. Includes examples of SAS computer code for implementation of the statistical methods. Connects to a Web site featuring solutions to exercises, extra computer code, and additional material. Serves as an overview of methods for analyzing environmental data, enabling use as a reference text for environmental science professionals. Graduate students of statistics studying environmental data analysis will find this invaluable as will practicing data analysts and environmental scientists including specialists in atmospheric science, biology and biomedicine, chemistry, ecology, environmental health, geography, and geology.

Download or read book Modeling and Data Analysis An Introduction with Environmental Applications written by John B. Little and published by American Mathematical Soc.. This book was released on 2019-03-28 with total page 323 pages. Available in PDF, EPUB and Kindle. Book excerpt: Can we coexist with the other life forms that have evolved on this planet? Are there realistic alternatives to fossil fuels that would sustainably provide for human society's energy needs and have fewer harmful effects? How do we deal with threats such as emergent diseases? Mathematical models—equations of various sorts capturing relationships between variables involved in a complex situation—are fundamental for understanding the potential consequences of choices we make. Extracting insights from the vast amounts of data we are able to collect requires analysis methods and statistical reasoning. This book on elementary topics in mathematical modeling and data analysis is intended for an undergraduate “liberal arts mathematics”-type course but with a specific focus on environmental applications. It is suitable for introductory courses with no prerequisites beyond high school mathematics. A great variety of exercises extends the discussions of the main text to new situations and/or introduces new real-world examples. Every chapter ends with a section of problems, as well as with an extended chapter project which often involves substantial computing work either in spreadsheet software or in the R statistical package.

Download or read book Environmental Data Analysis written by Carsten Dormann and published by Springer Nature. This book was released on 2020-12-20 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: Environmental Data Analysis is an introductory statistics textbook for environmental science. It covers descriptive, inferential and predictive statistics, centred on the Generalized Linear Model. The key idea behind this book is to approach statistical analyses from the perspective of maximum likelihood, essentially treating most analyses as (multiple) regression problems. The reader will be introduced to statistical distributions early on, and will learn to deploy models suitable for the data at hand, which in environmental science are often not normally distributed. To make the initially steep learning curve more manageable, each statistical chapter is followed by a walk-through in a corresponding R-based how-to chapter, which reviews the theory and applies it to environmental data. In this way, a coherent and expandable foundation in parametric statistics is laid, which can be expanded in advanced courses.The content has been “field-tested” in several years of courses on statistics for Environmental Science, Geography and Forestry taught at the University of Freiburg.

Download or read book Environmental Data Analysis with MatLab written by William Menke and published by Elsevier. This book was released on 2011-09-02 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Environmental Data Analysis with MatLab" is for students and researchers working to analyze real data sets in the environmental sciences. One only has to consider the global warming debate to realize how critically important it is to be able to derive clear conclusions from often-noisy data drawn from a broad range of sources. This book teaches the basics of the underlying theory of data analysis, and then reinforces that knowledge with carefully chosen, realistic scenarios. MatLab, a commercial data processing environment, is used in these scenarios; significant content is devoted to teaching how it can be effectively used in an environmental data analysis setting. The book, though written in a self-contained way, is supplemented with data sets and MatLab scripts that can be used as a data analysis tutorial. It is well written and outlines a clear learning path for researchers and students. It uses real world environmental examples and case studies. It has MatLab software for application in a readily-available software environment. Homework problems help user follow up upon case studies with homework that expands them.

Download or read book Quantitative Analysis and Modeling of Earth and Environmental Data written by Jiaping Wu and published by Elsevier. This book was released on 2021-12-04 with total page 504 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Download or read book Introduction to Environmental Data Science written by Jerry D. Davis and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Introduction to Environmental Data Science focuses on data science methods in the R language applied to environmental research, with sections on exploratory data analysis in R including data abstraction, transformation, and visualization; spatial data analysis in vector and raster models; statistics & modelling ranging from exploratory to modelling, considering confirmatory statistics and extending to machine learning models; time series analysis, focusing especially on carbon and micrometeorological flux; and communication. Introduction to Environmental Data Science. It is an ideal textbook to teach undergraduate to graduate level students in environmental science, environmental studies, geography, earth science, and biology, but can also serve as a reference for environmental professionals working in consulting, NGOs, and government agencies at the local, state, federal, and international levels"--

Download or read book Environmental Data Analysis written by Zhihua Zhang and published by Walter de Gruyter GmbH & Co KG. This book was released on 2016-11-21 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: Most environmental data involve a large degree of complexity and uncertainty. Environmental Data Analysis is created to provide modern quantitative tools and techniques designed specifically to meet the needs of environmental sciences and related fields. This book has an impressive coverage of the scope. Main techniques described in this book are models for linear and nonlinear environmental systems, statistical & numerical methods, data envelopment analysis, risk assessments and life cycle assessments. These state-of-the-art techniques have attracted significant attention over the past decades in environmental monitoring, modeling and decision making. Environmental Data Analysis explains carefully various data analysis procedures and techniques in a clear, concise, and straightforward language and is written in a self-contained way that is accessible to researchers and advanced students in science and engineering. This is an excellent reference for scientists and engineers who wish to analyze, interpret and model data from various sources, and is also an ideal graduate-level textbook for courses in environmental sciences and related fields. Contents: Preface Time series analysis Chaos and dynamical systems Approximation Interpolation Statistical methods Numerical methods Optimization Data envelopment analysis Risk assessments Life cycle assessments Index

Download or read book Environmental Data Analysis with MatLab written by William Menke and published by Elsevier. This book was released on 2009-10-13 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: Environmental Data Analysis with MatLab is a reference work designed to teach students and researchers the basics of data analysis in the environmental sciences using MatLab, and more specifically how to analyze data sets in carefully chosen, realistic scenarios. Although written in a self-contained way, the text is supplemented with data sets and MatLab scripts that can be used as a data analysis tutorial, available at the author's website: http://www.ldeo.columbia.edu/users/menke/edawm/index.htm. This book is organized into 12 chapters. After introducing the reader to the basics of data analysis with MatLab, the discussion turns to the power of linear models; quantifying preconceptions; detecting periodicities; patterns suggested by data; detecting correlations among the data; filling in missing data; and determining whether your results are significant. Homework problems help users follow up upon case studies. This text will appeal to environmental scientists, specialists, researchers, analysts, and undergraduate and graduate students in Environmental Engineering, Environmental Biology and Earth Science courses, who are working to analyze data and communicate results. Well written and outlines a clear learning path for researchers and students Uses real world environmental examples and case studies MatLab software for application in a readily-available software environment Homework problems help user follow up upon case studies with homework that expands them

Download or read book Environmental Statistics and Data Analysis written by Wayne R. Ott and published by Routledge. This book was released on 2018-12-13 with total page 249 pages. Available in PDF, EPUB and Kindle. Book excerpt: This easy-to-understand introduction emphasizes the areas of probability theory and statistics that are important in environmental monitoring, data analysis, research, environmental field surveys, and environmental decision making. It communicates basic statistical theory with very little abstract mathematical notation, but without omitting importa

Download or read book Models for Ecological Data written by James S. Clark and published by Princeton University Press. This book was released on 2020-10-06 with total page 634 pages. Available in PDF, EPUB and Kindle. Book excerpt: The environmental sciences are undergoing a revolution in the use of models and data. Facing ecological data sets of unprecedented size and complexity, environmental scientists are struggling to understand and exploit powerful new statistical tools for making sense of ecological processes. In Models for Ecological Data, James Clark introduces ecologists to these modern methods in modeling and computation. Assuming only basic courses in calculus and statistics, the text introduces readers to basic maximum likelihood and then works up to more advanced topics in Bayesian modeling and computation. Clark covers both classical statistical approaches and powerful new computational tools and describes how complexity can motivate a shift from classical to Bayesian methods. Through an available lab manual, the book introduces readers to the practical work of data modeling and computation in the language R. Based on a successful course at Duke University and National Science Foundation-funded institutes on hierarchical modeling, Models for Ecological Data will enable ecologists and other environmental scientists to develop useful models that make sense of ecological data. Consistent treatment from classical to modern Bayes Underlying distribution theory to algorithm development Many examples and applications Does not assume statistical background Extensive supporting appendixes Lab manual in R is available separately

Download or read book Introduction to Environmental Modeling written by William G. Gray and published by Cambridge University Press. This book was released on 2017 with total page 449 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook presents the timeless basic physical and mathematical principles and philosophy of environmental modeling to students who need to be taught how to think in a different way than they would for more narrowly-defined engineering or physics problems. Examples come from a range of hydrologic, atmospheric, and geophysical problems.

Download or read book Spatial Data Analysis in the Social and Environmental Sciences written by Robert P. Haining and published by Cambridge University Press. This book was released on 1993-08-26 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt: Within both the social and environmental sciences, much of the data collected is within a spatial context and requires statistical analysis for interpretation. The purpose of this book is to describe current methods for the analysis of spatial data. Methods described include data description, map interpolation, and exploratory and explanatory analyses. The book also examines spatial referencing, and methods for detecting problems, assessing their seriousness and taking appropriate action are discussed. This is an important text for any discipline requiring a broad overview of current theoretical and applied work for the analysis of spatial data sets. It will be of particular use to research workers and final year undergraduates in the fields of geography, environmental sciences and social sciences.

Download or read book Analysis and Modelling of Spatial Environmental Data written by Mikhail Kanevski and published by EPFL Press. This book was released on 2004-03-30 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: Analysis and Modelling of Spatial Environmental Data presents traditional geostatistics methods for variography and spatial predictions, approaches to conditional stochastic simulation and local probability distribution function estimation, and select aspects of Geographical Information Systems. It includes real case studies using Geostat Office software tools under MS Windows and also provides tools and methods to solve problems in prediction, characterization, optimization, and density estimation. The author describes fundamental methodological aspects of the analysis and modelling of spatially distributed data and the application by way of a specific and user-friendly software, GSO Geostat Office. Presenting complete coverage of geostatistics and machine learning algorithms, the book explores the relationships and complementary nature of both approaches and illustrates them with environmental and pollution data. The book includes introductory chapters on machine learning, artificial neural networks of different architectures, and support vector machines algorithms. Several chapters cover monitoring network analysis, artificial neural networks, support vector machines, and simulations. The book demonstrates thepromising results of the application of SVM to environmental and pollution data.

Download or read book Basic Environmental Data Analysis for Scientists and Engineers written by Ralph R.B. Von Frese and published by CRC Press. This book was released on 2019-11-22 with total page 223 pages. Available in PDF, EPUB and Kindle. Book excerpt: Classroom tested and the result of over 30 years of teaching and research, this textbook is an invaluable tool for undergraduate and graduate data analysis courses in environmental sciences and engineering. It is also a useful reference on modern digital data analysis for the extensive and growing community of Earth scientists and engineers. Basic Environmental Data Analysis for Scientists and Engineers introduces practical concepts of modern digital data analysis and graphics, including numerical/graphical calculus, measurement units and dimensional analysis, error propagation and statistics, and least squares data modeling. It emphasizes array-based or matrix inversion and spectral analysis using the fast Fourier transform (FFT) that dominates modern data analysis. Divided into two parts, this comprehensive hands-on textbook is excellent for exploring data analysis principles and practice using MATLAB®, Mathematica, Mathcad, and other modern equation solving software. Part I, for beginning undergraduate students, introduces the basic approaches for quantifying data variations in terms of environmental parameters. These approaches emphasize uses of the data array or matrix, which is the fundamental data and mathematical processing format of modern electronic computing. Part II, for advanced undergraduate and beginning graduate students, extends the inverse problem to least squares solutions involving more than two unknowns. Features: Offers a uniquely practical guide for making students proficient in modern electronic data analysis and graphics Includes topics that are not explained in any existing textbook on environmental data analysis Data analysis topics are very well organized into a two-semester course that meets general education curriculum requirements in science and engineering Facilitates learning by beginning each chapter with an ‘Overview’ section highlighting the topics covered, and ending it with a ‘Key Concepts’ section summarizing the main technical details that the reader should have acquired Indexes many numerical examples for ready access in the classroom or other venues serviced by electronic equation solvers like MATLAB®, Mathematica, Mathcad, etc. Offers supplemental exercises and materials to enhance understanding the principles and practice of modern data analysis

Download or read book Numerical Methods in Environmental Data Analysis written by Moses Eterigho Emetere and published by Elsevier. This book was released on 2022-07-17 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt: Numerical Methods in Environmental Data Analysis introduces environmental scientists to the numerical methods available to help answer research questions through data analysis. One challenge in data analysis is misrepresentation of datasets that are relevant directly or indirectly to the research. This book illustrates new ways of screening dataset or images for maximum utilization, introducing environmental modeling, numerical methods, and computations techniques in data analysis. Throughout the book, the author includes case studies that provide guidance on how to translate research questions into appropriate models. Individuals working with data sets or images generated from environmental monitoring centers or satellites will find this book to be a concise guide for analyzing and interpreting their data. Bridges the theoretical underpinnings of modeling to research Illustrates the computational resolution of environmental issues alongside the use of open-source software Provides information on the use of analogue versus digital data treatment processes