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Data Treatment In Environmental Sciences

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Data Treatment in Environmental Sciences

Data Treatment in Environmental Sciences Book
Author : Valérie David
Publisher : Elsevier
Release : 2017-05-25
ISBN : 0081023464
Language : En, Es, Fr & De

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Book Description :

Data Treatment in Environmental Sciences presents the various methods used in the analysis of databases—obtained in the field or in a laboratory—by focusing on the most commonly used multivariate analyses in different disciplines of environmental sciences, from geochemistry to ecology. The book examines the principles, application conditions and implementation (in R software) of various analyses before interpreting them. The wide variety of analyses presented allows users to treat datasets, both large and small, which are often limited in terms of available processing techniques. The approach taken by the author details (i) the preparation of a dataset prior to analysis, in relation to the scientific strategy and objectives of the study, (ii) the preliminary treatment of datasets, (iii) the establishment of a structure of objects (stations/dates) or relevant variables (e.g. physicochemical, biological), and (iv) how to highlight the explanatory parameters of these structures (e.g. how the physico-chemistry influences the biological structure obtained). Proposes tools that can be used to deal with environmental data Insists on the adequacy between the scientific objectives and the types of analyses Present mathematical principles without going into detail Offers a wide range of important analyses

Introduction to Environmental Data Analysis and Modeling

Introduction to Environmental Data Analysis and Modeling Book
Author : Moses Eterigho Emetere,Esther Titilayo Akinlabi
Publisher : Springer Nature
Release : 2020-01-03
ISBN : 3030362078
Language : En, Es, Fr & De

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Book Description :

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.

Machine Learning Methods in the Environmental Sciences

Machine Learning Methods in the Environmental Sciences Book
Author : William W. Hsieh
Publisher : Cambridge University Press
Release : 2009-07-30
ISBN : 0521791928
Language : En, Es, Fr & De

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Book Description :

A graduate textbook that provides a unified treatment of machine learning methods and their applications in the environmental sciences.

Spatial Data Analysis in the Social and Environmental Sciences

Spatial Data Analysis in the Social and Environmental Sciences Book
Author : Robert Haining
Publisher : Cambridge University Press
Release : 1993-08-26
ISBN : 9780521448666
Language : En, Es, Fr & De

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Book Description :

A spatial data set is a data set in which each observation is referenced to a site or area. 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, therefore, is to describe to students and research workers in the social and environmental sciences the current methods available for the analyses of spatial data. Methods described include data description, map interpolation, exploratory and explanatory analyses. The book also examines how spatial referencing raises a distinctive set of issues for the data analyst and recognizes the need to test underlying statistical assumptions. Further, methods for detecting problems, assessing their seriousness and taking appropriate action are discussed.

Numerical Methods in Environmental Data Analysis

Numerical Methods in Environmental Data Analysis Book
Author : Moses Emetere
Publisher : Elsevier
Release : 2021-11-15
ISBN : 9780128189719
Language : En, Es, Fr & De

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Book Description :

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

From Experimental Network to Meta analysis

From Experimental Network to Meta analysis Book
Author : David Makowski,François Piraux,François Brun
Publisher : Springer
Release : 2019-05-07
ISBN : 940241696X
Language : En, Es, Fr & De

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Book Description :

This book has been designed as a methodological guide and shows the interests and limitations of different statistical methods to analyze data from experimental networks and to perform meta-analyses. It is intended for engineers, students and researchers involved in data analysis in agronomy and environmental science.

Statistics for Earth and Environmental Scientists

Statistics for Earth and Environmental Scientists Book
Author : John H. Schuenemeyer,Lawrence J. Drew
Publisher : John Wiley & Sons
Release : 2011-04-12
ISBN : 1118102215
Language : En, Es, Fr & De

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Book Description :

A comprehensive treatment of statistical applications for solvingreal-world environmental problems A host of complex problems face today's earth science community,such as evaluating the supply of remaining non-renewable energyresources, assessing the impact of people on the environment,understanding climate change, and managing the use of water. Propercollection and analysis of data using statistical techniquescontributes significantly toward the solution of these problems.Statistics for Earth and Environmental Scientists presentsimportant statistical concepts through data analytic tools andshows readers how to apply them to real-world problems. The authors present several different statistical approaches tothe environmental sciences, including Bayesian and nonparametricmethodologies. The book begins with an introduction to types ofdata, evaluation of data, modeling and estimation, randomvariation, and sampling—all of which are explored throughcase studies that use real data from earth science applications.Subsequent chapters focus on principles of modeling and the keymethods and techniques for analyzing scientific data,including: Interval estimation and Methods for analyzinghypothesis testingof means time series data Spatial statistics Multivariate analysis Discrete distributions Experimental design Most statistical models are introduced by concept andapplication, given as equations, and then accompanied by heuristicjustification rather than a formal proof. Data analysis, modelbuilding, and statistical inference are stressed throughout, andreaders are encouraged to collect their own data to incorporateinto the exercises at the end of each chapter. Most data sets,graphs, and analyses are computed using R, but can be worked withusing any statistical computing software. A related websitefeatures additional data sets, answers to selected exercises, and Rcode for the book's examples. Statistics for Earth and Environmental Scientists is anexcellent book for courses on quantitative methods in geology,geography, natural resources, and environmental sciences at theupper-undergraduate and graduate levels. It is also a valuablereference for earth scientists, geologists, hydrologists, andenvironmental statisticians who collect and analyze data in theireveryday work.

Environmental Data Analysis

Environmental Data Analysis Book
Author : Carsten Dormann
Publisher : Springer Nature
Release : 2020-12-20
ISBN : 3030550206
Language : En, Es, Fr & De

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Book Description :

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.

Geophysical Data Analysis

Geophysical Data Analysis Book
Author : William Menke
Publisher : Academic Press
Release : 2018-04-10
ISBN : 0128135565
Language : En, Es, Fr & De

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Book Description :

Geophysical Data Analysis: Diverse Inverse Theory, Fourth Edition is a revised and expanded introduction to inverse theory and tomography as it is practiced by geophysicists. It demonstrates the methods needed to analyze a broad spectrum of geophysical datasets, with special attention to those methods that generate images of the earth. Data analysis can be a mathematically complex activity, but the treatment in this volume is carefully designed to emphasize those mathematical techniques that readers will find the most familiar and to systematically introduce less-familiar ones. Using problems and case studies, along with MATLAB computer code and summaries of methods, the book provides data scientists and engineers in geophysics with the tools necessary to understand and apply mathematical techniques and inverse theory. Includes material on probability, including Bayesian influence, probability density function and metropolis algorithm Offers detailed discussion of the application of inverse theory to tectonic, gravitational and geomagnetic studies Contains numerous examples, color figures and end-of-chapter homework problems to help readers explore and further understand presented ideas Includes MATLAB examples and problem sets Updated and refined throughout to bring the text in line with current understanding and improved examples and case studies Expanded sections to cover material, such as second-derivation smoothing and chi-squared tests not covered in the previous edition

Applied Multivariate Analysis in SAR and Environmental Studies

Applied Multivariate Analysis in SAR and Environmental Studies Book
Author : J. Devillers,W. Karcher
Publisher : Springer Science & Business Media
Release : 2013-03-07
ISBN : 9401131988
Language : En, Es, Fr & De

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Book Description :

Based on the Lectures given during the Eurocourse on `Applied Multivariate Analysis in SAR and Environmental Studies' held at the Joint Research Centre, Ispra, Italy, June 24-28, 1991

Data Science Applied to Sustainability Analysis

Data Science Applied to Sustainability Analysis Book
Author : Jennifer Dunn,Prasanna Balaprakash
Publisher : Elsevier
Release : 2021-05-28
ISBN : 0128179775
Language : En, Es, Fr & De

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Book Description :

Data Science Applied to Sustainability Analysis focuses on the methodological considerations associated with applying this tool in analysis techniques such as lifecycle assessment and materials flow analysis. As sustainability analysts need examples of applications of big data techniques that are defensible and practical in sustainability analyses and that yield actionable results that can inform policy development, corporate supply chain management strategy, or non-governmental organization positions, this book helps answer underlying questions. In addition, it addresses the need of data science experts looking for routes to apply their skills and knowledge to domain areas. Presents data sources that are available for application in sustainability analyses, such as market information, environmental monitoring data, social media data and satellite imagery Includes considerations sustainability analysts must evaluate when applying big data Features case studies illustrating the application of data science in sustainability analyses

Ecological Data

Ecological Data Book
Author : William K. Michener,James W. Brunt
Publisher : John Wiley & Sons
Release : 2009-04-01
ISBN : 1444311395
Language : En, Es, Fr & De

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Book Description :

Ecologists are increasingly tackling difficult issues like global change, loss of biodiversity and sustainability of ecosystem services. These and related topics are enormously challenging, requiring unprecedented multidisciplinary collaboration and rapid synthesis of large amounts of diverse data into information and ultimately knowledge. New sensors, computers, data collection and storage devices and analytical and statistical methods provide a powerful tool kit to support analyses, graphics and visualizations that were unthinkable even a few years ago. New and increased emphasis on accessibility, management, processing and sharing of high-quality, well-maintained and understandable data represents a significant change in how scientists view and treat data. These issues are complex and despite their importance, are typically not addressed in database, ecological and statistical textbooks. This book addresses these issues, providing a much needed resource for those involved in designing and implementing ecological research, as well as students who are entering the environmental sciences. Chapters focus on the design of ecological studies, data management principles, scientific databases, data quality assurance, data documentation, archiving ecological data and information and processing data into information and knowledge. The book stops short of a detailed treatment of data analysis, but does provide pointers to the relevant literature in graphics, statistics and knowledge discovery. The central thesis of the book is that high quality data management systems are critical for addressing future environmental challenges. This requires a new approach to how we conduct ecological research, that views data as a resource and promotes stewardship, recycling and sharing of data. Ecological Data will be particularly useful to those ecologists and information specialists that actively design, manage and analyze environmental databases. However, it will also benefit a wider audience of scientists and students in the ecological and environmental sciences.

Statistical Methods for Trend Detection and Analysis in the Environmental Sciences

Statistical Methods for Trend Detection and Analysis in the Environmental Sciences Book
Author : Richard Chandler,Marian Scott
Publisher : John Wiley & Sons
Release : 2011-03-25
ISBN : 111999196X
Language : En, Es, Fr & De

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Book Description :

The need to understand and quantify change is fundamental throughout the environmental sciences. This might involve describing past variation, understanding the mechanisms underlying observed changes, making projections of possible future change, or monitoring the effect of intervening in some environmental system. This book provides an overview of modern statistical techniques that may be relevant in problems of this nature. Practitioners studying environmental change will be familiar with many classical statistical procedures for the detection and estimation of trends. However, the ever increasing capacity to collect and process vast amounts of environmental information has led to growing awareness that such procedures are limited in the insights that they can deliver. At the same time, significant developments in statistical methodology have often been widely dispersed in the statistical literature and have therefore received limited exposure in the environmental science community. This book aims to provide a thorough but accessible review of these developments. It is split into two parts: the first provides an introduction to this area and the second part presents a collection of case studies illustrating the practical application of modern statistical approaches to the analysis of trends in real studies. Key Features: Presents a thorough introduction to the practical application and methodology of trend analysis in environmental science. Explores non-parametric estimation and testing as well as parametric techniques. Methods are illustrated using case studies from a variety of environmental application areas. Looks at trends in all aspects of a process including mean, percentiles and extremes. Supported by an accompanying website featuring datasets and R code. The book is designed to be accessible to readers with some basic statistical training, but also contains sufficient detail to serve as a reference for practising statisticians. It will therefore be of use to postgraduate students and researchers both in the environmental sciences and in statistics.

Statistics in Genetics and in the Environmental Sciences

Statistics in Genetics and in the Environmental Sciences Book
Author : Luisa T. Fernholz,Stephan Morgenthaler,Werner Stahel
Publisher : Birkhäuser
Release : 2012-12-06
ISBN : 3034883269
Language : En, Es, Fr & De

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Book Description :

Statistics is strongly tied to applications in different scientific disciplines, and the most challenging statistical problems arise from problems in the sciences. In fact, the most innovative statistical research flows from the needs of applications in diverse settings. This volume is a testimony to the crucial role that statistics plays in scientific disciplines such as genetics and environmental sciences, among others. The articles in this volume range from human and agricultural genetic DNA research to carcinogens and chemical concentrations in the environment and to space debris and atmospheric chemistry. Also included are some articles on statistical methods which are sufficiently general and flexible to be applied to many practical situations. The papers were refereed by a panel of experts and the editors of the volume. The contributions are based on the talks presented at the Workshop on Statistics and the Sciences, held at the Centro Stefano Franscini in Ascona, Switzerland, during the week of May 23 to 28, 1999. The meeting was jointly organized by the Swiss Federal Institutes of Technology in Lausanne and Zurich, with the financial support of the Minerva Research Foundation. As the presentations at the workshop helped the participants recognize the po tential role that statistics can play in the sciences, we hope that this volume will help the reader to focus on the central role of statistics in the specific areas presented here and to extrapolate the results to further applications.

Hierarchical Modelling for the Environmental Sciences

Hierarchical Modelling for the Environmental Sciences Book
Author : James S. Clark,Alan E. Gelfand
Publisher : OUP Oxford
Release : 2006-05-04
ISBN : 9780191513848
Language : En, Es, Fr & De

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Book Description :

New statistical tools are changing the ways in which scientists analyze and interpret data and models. Many of these are emerging as a result of the wide availability of inexpensive, high speed computational power. In particular, hierarchical Bayes and Markov Chain Monte Carlo methods for analysis provide consistent framework for inference and prediction where information is heterogeneous and uncertain, processes are complex, and responses depend on scale. Nowhere are these methods more promising than in the environmental sciences. Models have developed rapidly, and there is now a requirement for a clear exposition of the methodology through to application for a range of environmental challenges.

Compositional Data Analysis

Compositional Data Analysis Book
Author : John Bacon-Shone
Publisher : CRC Press
Release : 2018-07-30
ISBN : 9781498729482
Language : En, Es, Fr & De

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Book Description :

Compositional Data Analysis (CoDA) refers to the analysis of all those vectors representing parts of a whole which only carry relative information. This type of data is ubiquitous in most applications, especially in geology, chemistry, genetics, and environmental sciences. The last comprehensive treatment was written by John Aitchison in 1986, and this book represents an update of that classic book.

International Symposium on Earth and Environmental Sciences for Future Generations

International Symposium on Earth and Environmental Sciences for Future Generations Book
Author : Jeffrey T. Freymueller,Laura Sánchez
Publisher : Springer
Release : 2017-11-27
ISBN : 3319691708
Language : En, Es, Fr & De

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Book Description :

This book series is composed of peer-reviewed proceedings of selected symposia organized by the International Association of Geodesy. It deals primarily with topics related to Geodesy Earth Sciences : terrestrial reference frame, Earth gravity field, Geodynamics and Earth rotation, Positioning and engineering applications.

Applied Multiway Data Analysis

Applied Multiway Data Analysis Book
Author : Pieter M. Kroonenberg
Publisher : Wiley-Interscience
Release : 2008-01-28
ISBN : 9780470164976
Language : En, Es, Fr & De

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Book Description :

From a preeminent authority—a modern and applied treatment of multiway data analysis This groundbreaking book is the first of its kind to present methods for analyzing multiway data by applying multiway component techniques. Multiway analysis is a specialized branch of the larger field of multivariate statistics that extends the standard methods for two-way data, such as component analysis, factor analysis, cluster analysis, correspondence analysis, and multidimensional scaling to multiway data. Applied Multiway Data Analysis presents a unique, thorough, and authoritative treatment of this relatively new and emerging approach to data analysis that is applicable across a range of fields, from the social and behavioral sciences to agriculture, environmental sciences, and chemistry. General introductions to multiway data types, methods, and estimation procedures are provided in addition to detailed explanations and advice for readers who would like to learn more about applying multiway methods. Using carefully laid out examples and engaging applications, the book begins with an introductory chapter that serves as a general overview of multiway analysis, including the types of problems it can address. Next, the process of setting up, carrying out, and evaluating multiway analyses is discussed along with commonly encountered issues, such as preprocessing, missing data, model and dimensionality selection, postprocessing, and transformation, as well as robustness and stability issues. Extensive examples are presented within a unified framework consisting of a five-step structure: objectives; data description and design; model and dimensionality selection; results and their interpretation; and validation. Procedures featured in the book are conducted using 3WayPack, which is software developed by the author, and analyses can also be carried out within the R and MATLAB systems. Several data sets and 3WayPack can be downloaded via the book's related Web site. The author presents the material in a clear, accessible style without unnecessary or complex formalism, assuring a smooth transition from well-known standard two-analysis to multiway analysis for readers from a wide range of backgrounds. An understanding of linear algebra, statistics, and principal component analyses and related techniques is assumed, though the author makes an effort to keep the presentation at a conceptual, rather than mathematical, level wherever possible. Applied Multiway Data Analysis is an excellent supplement for component analysis and statistical multivariate analysis courses at the upper-undergraduate and beginning graduate levels. The book can also serve as a primary reference for statisticians, data analysts, methodologists, applied mathematicians, and social science researchers working in academia or industry. Visit the Related Website: http://three-mode.leidenuniv.nl/, to view data from the book.

Models for Ecological Data

Models for Ecological Data Book
Author : James S. Clark,James Samuel Clark
Publisher : Princeton University Press
Release : 2007-06-03
ISBN : 0691122628
Language : En, Es, Fr & De

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Book Description :

Laboratory manual for: Models for ecological data.

Statistics for Environmental Engineers Second Edition

Statistics for Environmental Engineers  Second Edition Book
Author : Linfield C. Brown,Paul Mac Berthouex
Publisher : CRC Press
Release : 2002-01-29
ISBN : 9781420056631
Language : En, Es, Fr & De

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Book Description :

Two critical questions arise when one is confronted with a new problem that involves the collection and analysis of data. How will the use of statistics help solve this problem? Which techniques should be used? Statistics for Environmental Engineers, Second Edition helps environmental science and engineering students answer these questions when the goal is to understand and design systems for environmental protection. The second edition of this bestseller is a solutions-oriented text that encourages students to view statistics as a problem-solving tool. Written in an easy-to-understand style, Statistics for Environmental Engineers, Second Edition consists of 54 short, "stand-alone" chapters. All chapters address a particular environmental problem or statistical technique and are written in a manner that permits each chapter to be studied independently and in any order. Chapters are organized around specific case studies, beginning with brief discussions of the appropriate methodologies, followed by analysis of the case study examples, and ending with comments on the strengths and weaknesses of the approaches. New to this edition: Thirteen new chapters dealing with topics such as experimental design, sizing experiments, tolerance and prediction intervals, time-series modeling and forecasting, transfer function models, weighted least squares, laboratory quality assurance, and specialized control charts Exercises for classroom use or self-study in each chapter Improved graphics Revisions to all chapters Whether the topic is displaying data, t-tests, mechanistic model building, nonlinear least squares, confidence intervals, regression, or experimental design, the context is always familiar to environmental scientists and engineers. Case studies are drawn from censored data, detection limits, regulatory standards, treatment plant performance, sampling and measurement errors, hazardous waste, and much more. This revision of a classic text serves as an ideal textbook for students and a valuable reference for any environmental professional working with numbers.