Basic Environmental Data Analysis For Scientists And Engineers
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Data Analysis And Statistics For Geography Environmental Science And Engineering
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Author : Miguel F. Acevedo
language : en
Publisher: CRC Press
Release Date : 2012-12-07
Data Analysis And Statistics For Geography Environmental Science And Engineering written by Miguel F. Acevedo and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-07 with Mathematics categories.
Providing a solid foundation for twenty-first-century scientists and engineers, Data Analysis and Statistics for Geography, Environmental Science, and Engineering guides readers in learning quantitative methodology, including how to implement data analysis methods using open-source software. Given the importance of interdisciplinary work in sustain
Environmental Data Analysis
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Author : Zhihua Zhang
language : en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date : 2016-11-21
Environmental Data Analysis written by Zhihua Zhang and has been published by Walter de Gruyter GmbH & Co KG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-11-21 with Mathematics categories.
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
Basic Environmental Data Analysis For Scientists And Engineers
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Author : Ralph R.B. Von Frese
language : en
Publisher: CRC Press
Release Date : 2019-11-22
Basic Environmental Data Analysis For Scientists And Engineers written by Ralph R.B. Von Frese and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-22 with Mathematics categories.
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
Applied Statistics For Environmental Science With R
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Author : Abbas F. M. Al-Karkhi
language : en
Publisher: Elsevier
Release Date : 2019-09-13
Applied Statistics For Environmental Science With R written by Abbas F. M. Al-Karkhi and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-13 with Computers categories.
Applied Statistics for Environmental Science with R presents the theory and application of statistical techniques in environmental science and aids researchers in choosing the appropriate statistical technique for analyzing their data. Focusing on the use of univariate and multivariate statistical methods, this book acts as a step-by-step resource to facilitate understanding in the use of R statistical software for interpreting data in the field of environmental science. Researchers utilizing statistical analysis in environmental science and engineering will find this book to be essential in solving their day-to-day research problems.
Environmental Statistics And Data Analysis
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Author : Wayne R. Ott
language : en
Publisher: Routledge
Release Date : 2018-12-13
Environmental Statistics And Data Analysis written by Wayne R. Ott and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-13 with Mathematics categories.
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
Spatial Data Analysis In The Social And Environmental Sciences
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Author : Robert P. Haining
language : en
Publisher: Cambridge University Press
Release Date : 1993-08-26
Spatial Data Analysis In The Social And Environmental Sciences written by Robert P. Haining and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1993-08-26 with Mathematics categories.
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.
Introduction To Environmental Data Science
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Author : William W. Hsieh
language : en
Publisher: Cambridge University Press
Release Date : 2023-03-23
Introduction To Environmental Data Science written by William W. Hsieh and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-23 with Computers categories.
A comprehensive guide to machine learning and statistics for students and researchers of environmental data science.
Marine Environmental Characterization
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Author : C. Reid Nichols
language : en
Publisher: Springer Nature
Release Date : 2022-06-01
Marine Environmental Characterization written by C. Reid Nichols and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-01 with Technology & Engineering categories.
The use of environmental data to support science, technology, and marine operations has evolved dramatically owing to long-term ocean observatories, unmanned platforms, satellite and coastal remote sensing, data assimilative numerical models, and high-speed communications. Actionable environmental information is regularly produced and communicated from quality-controlled measurements and skillful forecasts. The characterization of complex oceanographic processes is more difficult compared to inland features because of the difficulty in obtaining observations from often remote and hazardous locations. Regardless, coastal and ocean engineering projects and operations require the collection and analysis of meteorological and oceanographic data to fill information gaps and the running of numerical models to characterize regions of interest. Data analytics are also essential to integrate disparate marine data from national archives, in situ sensors, imagery, and numerical models to meet project requirements. Holistic marine environmental characterization is essential for data-driven decision making across the science and engineering lifecycle (e.g., research, production, operations, end-of-life). Many marine science and technology projects require the employment of an array of instruments and models to characterize spatially and temporally variable processes that may impact operations. Since certain environmental conditions will contribute to structural damage or operational disturbances, they are described using statistical parameters that have been standardized for engineering purposes. The statistical description should describe extreme conditions as well as long- and short-term variability. These data may also be used to verify and validate models and simulations. Environmental characterization covers the region where engineering projects or maritime operations take place. For vessels that operate across a variety of seaways, marine databases and models are essential to describe environmental conditions. Data, which are used for design and operations, must cover a sufficiently long time period to describe seasonal to sub-seasonal variations, multi-year, decadal, multi-decadal, and even climatological factors such as sea level rise, coastal winds, waves, and global ocean temperatures. Combined data types are essential for the computation of environmental loads for the region of interest. Typical factors include winds, waves, currents, and tides. Some regions may require consideration of biofouling, earthquakes, ice, salinity, soil conditions, temperature, tsunami, and visibility. Observations are also used for numerical forecasts, but errors may exist due to inexact physical assumptions and/or inaccurate initial data, which can cause errors to grow to unacceptable levels with increased forecasting times. Overall, marine environmental characterization tools, from observational data to numerical modeling, are critical to today's science, engineering, and marine operational disciplines.
Statistics For Environmental Engineers Second Edition
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Author : Linfield C. Brown
language : en
Publisher: CRC Press
Release Date : 2002-01-29
Statistics For Environmental Engineers Second Edition written by Linfield C. Brown and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002-01-29 with Mathematics categories.
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.
Data Driven Modeling Using Matlab In Water Resources And Environmental Engineering
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Author : Shahab Araghinejad
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-11-26
Data Driven Modeling Using Matlab In Water Resources And Environmental Engineering written by Shahab Araghinejad 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 2013-11-26 with Science categories.
“Data-Driven Modeling: Using MATLAB® in Water Resources and Environmental Engineering” provides a systematic account of major concepts and methodologies for data-driven models and presents a unified framework that makes the subject more accessible to and applicable for researchers and practitioners. It integrates important theories and applications of data-driven models and uses them to deal with a wide range of problems in the field of water resources and environmental engineering such as hydrological forecasting, flood analysis, water quality monitoring, regionalizing climatic data, and general function approximation. The book presents the statistical-based models including basic statistical analysis, nonparametric and logistic regression methods, time series analysis and modeling, and support vector machines. It also deals with the analysis and modeling based on artificial intelligence techniques including static and dynamic neural networks, statistical neural networks, fuzzy inference systems, and fuzzy regression. The book also discusses hybrid models as well as multi-model data fusion to wrap up the covered models and techniques. The source files of relatively simple and advanced programs demonstrating how to use the models are presented together with practical advice on how to best apply them. The programs, which have been developed using the MATLAB® unified platform, can be found on extras.springer.com. The main audience of this book includes graduate students in water resources engineering, environmental engineering, agricultural engineering, and natural resources engineering. This book may be adapted for use as a senior undergraduate and graduate textbook by focusing on selected topics. Alternatively, it may also be used as a valuable resource book for practicing engineers, consulting engineers, scientists and others involved in water resources and environmental engineering.