Data Science Applied to Sustainability Analysis Book

Data Science Applied to Sustainability Analysis


  • Author : Jennifer Dunn
  • Publisher : Elsevier
  • Release Date : 2021-05-11
  • Genre: Science
  • Pages : 310
  • ISBN 10 : 9780128179772

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Data Science Applied to Sustainability Analysis Excerpt :

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

Computational Intelligent Data Analysis for Sustainable Development Book

Computational Intelligent Data Analysis for Sustainable Development


  • Author : Ting Yu
  • Publisher : CRC Press
  • Release Date : 2016-04-19
  • Genre: Business & Economics
  • Pages : 440
  • ISBN 10 : 9781439895955

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Computational Intelligent Data Analysis for Sustainable Development Excerpt :

Going beyond performing simple analyses, researchers involved in the highly dynamic field of computational intelligent data analysis design algorithms that solve increasingly complex data problems in changing environments, including economic, environmental, and social data. Computational Intelligent Data Analysis for Sustainable Development present

Data Science Applied to Sustainability Analysis Book

Data Science Applied to Sustainability Analysis


  • Author : Jennifer Dunn
  • Publisher : Elsevier
  • Release Date : 2021-05-17
  • Genre: Science
  • Pages : 310
  • ISBN 10 : 9780128179765

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Data Science Applied to Sustainability Analysis Excerpt :

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

Data driven Analytics for Sustainable Buildings and Cities Book

Data driven Analytics for Sustainable Buildings and Cities


  • Author : Xingxing Zhang
  • Publisher : Springer Nature
  • Release Date : 2021-09-11
  • Genre: Social Science
  • Pages : 450
  • ISBN 10 : 9789811627781

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Data driven Analytics for Sustainable Buildings and Cities Excerpt :

This book explores the interdisciplinary and transdisciplinary fields of energy systems, occupant behavior, thermal comfort, air quality and economic modelling across levels of building, communities and cities, through various data analytical approaches. It highlights the complex interplay of heating/cooling, ventilation and power systems in different processes, such as design, renovation and operation, for buildings, communities and cities. Methods from classical statistics, machine learning and artificial intelligence are applied into analyses for different building/urban components and systems. Knowledge from this book assists to accelerate sustainability of the society, which would contribute to a prospective improvement through data analysis in the liveability of both built and urban environment. This book targets a broad readership with specific experience and knowledge in data analysis, energy system, built environment and urban planning. As such, it appeals to researchers, graduate students, data scientists, engineers, consultants, urban scientists, investors and policymakers, with interests in energy flexibility, building/city resilience and climate neutrality.

Big Data Science and Analytics for Smart Sustainable Urbanism Book

Big Data Science and Analytics for Smart Sustainable Urbanism


  • Author : Simon Elias Bibri
  • Publisher : Springer
  • Release Date : 2019-05-30
  • Genre: Political Science
  • Pages : 337
  • ISBN 10 : 9783030173128

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Big Data Science and Analytics for Smart Sustainable Urbanism Excerpt :

We are living at the dawn of what has been termed ‘the fourth paradigm of science,’ a scientific revolution that is marked by both the emergence of big data science and analytics, and by the increasing adoption of the underlying technologies in scientific and scholarly research practices. Everything about science development or knowledge production is fundamentally changing thanks to the ever-increasing deluge of data. This is the primary fuel of the new age, which powerful computational processes or analytics algorithms are using to generate valuable knowledge for enhanced decision-making, and deep insights pertaining to a wide variety of practical uses and applications. This book addresses the complex interplay of the scientific, technological, and social dimensions of the city, and what it entails in terms of the systemic implications for smart sustainable urbanism. In concrete terms, it explores the interdisciplinary and transdisciplinary field of smart sustainable urbanism and the unprecedented paradigmatic shifts and practical advances it is undergoing in light of big data science and analytics. This new era of science and technology embodies an unprecedentedly transformative and constitutive power—manifested not only in the form of revolutionizing science and transforming knowledge, but also in advancing social practices, producing new discourses, catalyzing major shifts, and fostering societal transitions. Of particular relevance, it is instigating a massive change in the way both smart cities and sustainable cities are studied and understood, and in how they are planned, designed, operated, managed, and governed in the face of urbanization. This relates to what has been dubbed data-driven smart sustainable urbanism, an emerging approach based on a computational understanding of city systems and processes that reduces urban life to logical and algorithmic rules and procedures, while also harnessing urban big data to provide a more holistic and integrat

Environmental Data Analysis with MatLab Book

Environmental Data Analysis with MatLab


  • Author : William Menke
  • Publisher : Elsevier
  • Release Date : 2011-09-02
  • Genre: Mathematics
  • Pages : 282
  • ISBN 10 : 9780123918864

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Environmental Data Analysis with MatLab 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.

Basic Environmental Data Analysis for Scientists and Engineers Book

Basic Environmental Data Analysis for Scientists and Engineers


  • Author : Ralph R.B. Von Frese
  • Publisher : CRC Press
  • Release Date : 2019-11-22
  • Genre: Mathematics
  • Pages : 223
  • ISBN 10 : 9781000725759

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Basic Environmental Data Analysis for Scientists and Engineers 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

Environmental Systems Science Book

Environmental Systems Science


  • Author : Daniel Vallero
  • Publisher : Elsevier
  • Release Date : 2021-05-27
  • Genre: Medical
  • Pages : 704
  • ISBN 10 : 9780128219447

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Environmental Systems Science Excerpt :

Environmental Systems Science: Theory and Practical Applications looks at pollution and environmental quality from a systems perspective. Credible human and ecological risk estimation and prediction methods are described, including life cycle assessment, feasibility studies, pollution control decision tools, and approaches to determine adverse outcome pathways, fate and transport, sampling and analysis, and cost-effectiveness. The book brings translational science to environmental quality, applying groundbreaking methodologies like informatics, data mining, and applications of secondary data systems. Multiple human and ecological variables are introduced and integrated to support calculations that aid environmental and public health decision making. The book bridges the perspectives of scientists, engineers, and other professionals working in numerous environmental and public health fields addressing problems like toxic substances, deforestation, climate change, and loss of biological diversity, recommending sustainable solutions to these and other seemingly intractable environmental problems. The causal agents discussed include physical, chemical, and biological agents, such as per- and polyfluoroalkyl substances (PFAS), SARS-CoV-2 (the COVID-19 virus), and other emerging contaminants. Provides an optimistic and interdisciplinary approach, underpinned by scientific first principles and theory to evaluate pollutant sources and sinks, applying biochemodynamic methods, measurements and models Deconstructs prior initiatives in environmental assessment and management using an interdisciplinary approach to evaluate what has worked and why Lays out a holistic understanding of the real impact of human activities on the current state of pollution, linking the physical sciences and engineering with socioeconomic, cultural perspectives, and environmental justice Takes a life cycle view of human and ecological systems, from the molecular to the planetary scale, integrating the

Applied Statistics for Environmental Science with R Book

Applied Statistics for Environmental Science with R


  • Author : Abbas F. M. Al-Karkhi
  • Publisher : Elsevier
  • Release Date : 2019-09-13
  • Genre: Computers
  • Pages : 240
  • ISBN 10 : 9780128186237

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Applied Statistics for Environmental Science with R Excerpt :

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. Includes step-by-step tutorials to aid in understanding the process and implementation of unique data Presents statistical theory in a simple way without complex mathematical proofs Shows how to analyze data using R software and provides R scripts for all examples and figures

CIGOS 2021  Emerging Technologies and Applications for Green Infrastructure Book

CIGOS 2021 Emerging Technologies and Applications for Green Infrastructure


  • Author : Cuong Ha-Minh
  • Publisher : Springer Nature
  • Release Date : 2021-10-28
  • Genre: Science
  • Pages : 1958
  • ISBN 10 : 9789811671609

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CIGOS 2021 Emerging Technologies and Applications for Green Infrastructure Excerpt :

This book highlights the key role of green infrastructure (GI) in providing natural and ecosystem solutions, helping alleviate many of the environmental, social, and economic problems caused by rapid urbanization. The book gathers the emerging technologies and applications in various disciplines involving geotechnics, civil engineering, and structures, which are presented in numerous high-quality papers by worldwide researchers, practitioners, policymakers, and entrepreneurs at the 6th CIGOS event, 2021. Moreover, by sharing knowledge and experiences around emerging GI technologies and policy issues, the book aims at encouraging adoption of GI technologies as well as building capacity for implementing GI practices at all scales. This book is useful for researchers and professionals in designing, building, and managing sustainable buildings and infrastructure.

Big Data Analytics for Sustainable Computing Book

Big Data Analytics for Sustainable Computing


  • Author : Haldorai, Anandakumar
  • Publisher : IGI Global
  • Release Date : 2019-09-20
  • Genre: Computers
  • Pages : 263
  • ISBN 10 : 9781522597520

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Big Data Analytics for Sustainable Computing Excerpt :

Big data consists of data sets that are too large and complex for traditional data processing and data management applications. Therefore, to obtain the valuable information within the data, one must use a variety of innovative analytical methods, such as web analytics, machine learning, and network analytics. As the study of big data becomes more popular, there is an urgent demand for studies on high-level computational intelligence and computing services for analyzing this significant area of information science. Big Data Analytics for Sustainable Computing is a collection of innovative research that focuses on new computing and system development issues in emerging sustainable applications. Featuring coverage on a wide range of topics such as data filtering, knowledge engineering, and cognitive analytics, this publication is ideally designed for data scientists, IT specialists, computer science practitioners, computer engineers, academicians, professionals, and students seeking current research on emerging analytical techniques and data processing software.

Research Handbook on Big Data Law Book

Research Handbook on Big Data Law


  • Author : Roland Vogl
  • Publisher : Edward Elgar Publishing
  • Release Date : 2021-05-28
  • Genre: Law
  • Pages : 544
  • ISBN 10 : 9781788972826

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Research Handbook on Big Data Law Excerpt :

This state-of-the-art Research Handbook provides an overview of research into, and the scope of current thinking in, the field of big data analytics and the law. It contains a wealth of information to survey the issues surrounding big data analytics in legal settings, as well as legal issues concerning the application of big data techniques in different domains.

Data Treatment in Environmental Sciences Book

Data Treatment in Environmental Sciences


  • Author : Valérie David
  • Publisher : Elsevier
  • Release Date : 2017-05-25
  • Genre: Science
  • Pages : 194
  • ISBN 10 : 9780081023464

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Data Treatment in Environmental Sciences Excerpt :

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

Artificial Intelligence and Data Science in Environmental Sensing Book

Artificial Intelligence and Data Science in Environmental Sensing


  • Author : Mohsen Asadnia
  • Publisher : Academic Press
  • Release Date : 2022-02-24
  • Genre: Computers
  • Pages : 324
  • ISBN 10 : 9780323905077

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Artificial Intelligence and Data Science in Environmental Sensing Excerpt :

Artificial Intelligence and Data Science in Environmental Sensing provides state-of-the-art information on the inexpensive mass-produced sensors that are used as inputs to artificial intelligence systems. The book discusses the advances of AI and Machine Learning technologies in material design for environmental areas. It is an excellent resource for researchers and professionals who work in the field of data processing, artificial intelligence sensors and environmental applications. Presents tools, connections and proactive solutions to take sustainability programs to the next level Offers a practical guide for making students proficient in modern electronic data analysis and graphics Provides knowledge and background to develop specific platforms related to environmental sensing, including control water, air and soil quality, water and wastewater treatment, desalination, pollution mitigation/control, and resource management and recovery

Statistical Data Analysis Explained Book

Statistical Data Analysis Explained


  • Author : Clemens Reimann
  • Publisher : John Wiley & Sons
  • Release Date : 2011-08-31
  • Genre: Science
  • Pages : 362
  • ISBN 10 : 9781119965282

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Statistical Data Analysis Explained Excerpt :

Few books on statistical data analysis in the natural sciences are written at a level that a non-statistician will easily understand. This is a book written in colloquial language, avoiding mathematical formulae as much as possible, trying to explain statistical methods using examples and graphics instead. To use the book efficiently, readers should have some computer experience. The book starts with the simplest of statistical concepts and carries readers forward to a deeper and more extensive understanding of the use of statistics in environmental sciences. The book concerns the application of statistical and other computer methods to the management, analysis and display of spatial data. These data are characterised by including locations (geographic coordinates), which leads to the necessity of using maps to display the data and the results of the statistical methods. Although the book uses examples from applied geochemistry, and a large geochemical survey in particular, the principles and ideas equally well apply to other natural sciences, e.g., environmental sciences, pedology, hydrology, geography, forestry, ecology, and health sciences/epidemiology. The book is unique because it supplies direct access to software solutions (based on R, the Open Source version of the S-language for statistics) for applied environmental statistics. For all graphics and tables presented in the book, the R-scripts are provided in the form of executable R-scripts. In addition, a graphical user interface for R, called DAS+R, was developed for convenient, fast and interactive data analysis. Statistical Data Analysis Explained: Applied Environmental Statistics with R provides, on an accompanying website, the software to undertake all the procedures discussed, and the data employed for their description in the book.