Data Science Applied to Sustainability Analysis

Data Science Applied to Sustainability Analysis

Author: Jennifer Dunn

Publisher: Elsevier

Published: 2021-05-11

Total Pages: 312

ISBN-13: 0128179775

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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


Book Synopsis Data Science Applied to Sustainability Analysis by : Jennifer Dunn

Download or read book Data Science Applied to Sustainability Analysis written by Jennifer Dunn and published by Elsevier. This book was released on 2021-05-11 with total page 312 pages. Available in PDF, EPUB and Kindle. Book 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


Sustainable Development Through Data Analytics and Innovation

Sustainable Development Through Data Analytics and Innovation

Author: Jorge Marx Gómez

Publisher: Springer Nature

Published: 2022-09-26

Total Pages: 195

ISBN-13: 3031125274

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Sustainable development is based on the idea that societies should advance without compromising their future development requirements. This book explores how the application of data analytics and digital technologies can ensure that development changes are executed on the basis of factual data and information. It addresses how innovations that rely on digital technologies can support sustainable development across all sectors and all social, economic, and environmental aspects and help us achieve the Sustainable Development Goals (SDGs). The book also highlights techniques, processes, models, tools, and practices used to achieve sustainable development through data analysis. The various topics covered in this book are critically evaluated, not only theoretically, but also from an application perspective. It will be of interest to researchers and students, especially those in the fields of applied data analytics, business intelligence and knowledge management.


Book Synopsis Sustainable Development Through Data Analytics and Innovation by : Jorge Marx Gómez

Download or read book Sustainable Development Through Data Analytics and Innovation written by Jorge Marx Gómez and published by Springer Nature. This book was released on 2022-09-26 with total page 195 pages. Available in PDF, EPUB and Kindle. Book excerpt: Sustainable development is based on the idea that societies should advance without compromising their future development requirements. This book explores how the application of data analytics and digital technologies can ensure that development changes are executed on the basis of factual data and information. It addresses how innovations that rely on digital technologies can support sustainable development across all sectors and all social, economic, and environmental aspects and help us achieve the Sustainable Development Goals (SDGs). The book also highlights techniques, processes, models, tools, and practices used to achieve sustainable development through data analysis. The various topics covered in this book are critically evaluated, not only theoretically, but also from an application perspective. It will be of interest to researchers and students, especially those in the fields of applied data analytics, business intelligence and knowledge management.


Computational Intelligent Data Analysis for Sustainable Development

Computational Intelligent Data Analysis for Sustainable Development

Author: Ting Yu

Publisher: CRC Press

Published: 2016-04-19

Total Pages: 443

ISBN-13: 1439895953

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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


Book Synopsis Computational Intelligent Data Analysis for Sustainable Development by : Ting Yu

Download or read book Computational Intelligent Data Analysis for Sustainable Development written by Ting Yu and published by CRC Press. This book was released on 2016-04-19 with total page 443 pages. Available in PDF, EPUB and Kindle. Book 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


Methods in Sustainability Science

Methods in Sustainability Science

Author: Jingzheng Ren

Publisher: Elsevier

Published: 2021-08-05

Total Pages: 446

ISBN-13: 012824240X

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Methods in Sustainability Science: Assessment, Prioritization, Improvement, Design and Optimization presents cutting edge, detailed methodologies needed to create sustainable growth in any field or industry, including life cycle assessments, building design, and energy systems. The book utilized a systematic structured approach to each of the methodologies described in an interdisciplinary way to ensure the methodologies are applicable in the real world, including case studies to demonstrate the methods. The chapters are written by a global team of authors in a variety of sustainability related fields. Methods in Sustainability Science: Assessment, Prioritization, Improvement, Design and Optimization will provide academics, researchers and practitioners in sustainability, especially environmental science and environmental engineering, with the most recent methodologies needed to maintain a sustainable future. It is also a necessary read for postgraduates in sustainability, as well as academics and researchers in energy and chemical engineering who need to ensure their industrial methodologies are sustainable. Provides a comprehensive overview of the most recent methodologies in sustainability assessment, prioritization, improvement, design and optimization Sections are organized in a systematic and logical way to clearly present the most recent methodologies for sustainability and the chapters utilize an interdisciplinary approach that covers all considerations of sustainability Includes detailed case studies demonstrating the efficacies of the described methods


Book Synopsis Methods in Sustainability Science by : Jingzheng Ren

Download or read book Methods in Sustainability Science written by Jingzheng Ren and published by Elsevier. This book was released on 2021-08-05 with total page 446 pages. Available in PDF, EPUB and Kindle. Book excerpt: Methods in Sustainability Science: Assessment, Prioritization, Improvement, Design and Optimization presents cutting edge, detailed methodologies needed to create sustainable growth in any field or industry, including life cycle assessments, building design, and energy systems. The book utilized a systematic structured approach to each of the methodologies described in an interdisciplinary way to ensure the methodologies are applicable in the real world, including case studies to demonstrate the methods. The chapters are written by a global team of authors in a variety of sustainability related fields. Methods in Sustainability Science: Assessment, Prioritization, Improvement, Design and Optimization will provide academics, researchers and practitioners in sustainability, especially environmental science and environmental engineering, with the most recent methodologies needed to maintain a sustainable future. It is also a necessary read for postgraduates in sustainability, as well as academics and researchers in energy and chemical engineering who need to ensure their industrial methodologies are sustainable. Provides a comprehensive overview of the most recent methodologies in sustainability assessment, prioritization, improvement, design and optimization Sections are organized in a systematic and logical way to clearly present the most recent methodologies for sustainability and the chapters utilize an interdisciplinary approach that covers all considerations of sustainability Includes detailed case studies demonstrating the efficacies of the described methods


Sustainability Analysis

Sustainability Analysis

Author: S. Shmelev

Publisher: Springer

Published: 2012-01-27

Total Pages: 501

ISBN-13: 0230362435

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Sustainability Analysis provides a detailed exploration of current environmental thinking from a variety of perspectives, including institutional and psychological angles. Primarily focusing on macroeconomic policies and green national accounting, this book provides a strong basis for further study in sustainable development.


Book Synopsis Sustainability Analysis by : S. Shmelev

Download or read book Sustainability Analysis written by S. Shmelev and published by Springer. This book was released on 2012-01-27 with total page 501 pages. Available in PDF, EPUB and Kindle. Book excerpt: Sustainability Analysis provides a detailed exploration of current environmental thinking from a variety of perspectives, including institutional and psychological angles. Primarily focusing on macroeconomic policies and green national accounting, this book provides a strong basis for further study in sustainable development.


Data Science and SDGs

Data Science and SDGs

Author: Bikas Kumar Sinha

Publisher:

Published: 2021

Total Pages: 0

ISBN-13: 9789811619205

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The book presents contributions on statistical models and methods applied, for both data science and SDGs, in one place. Measuring and controlling data of SDGs, data driven measurement of progress needs to be distributed to stakeholders. In this situation, the techniques used in data science, specially, in the big data analytics, play an important role rather than the traditional data gathering and manipulation techniques. This book fills this space through its twenty contributions. The contributions have been selected from those presented during the 7th International Conference on Data Science and Sustainable Development Goals organized by the Department of Statistics, University of Rajshahi, Bangladesh; and cover topics mainly on SDGs, bioinformatics, public health, medical informatics, environmental statistics, data science and machine learning. The contents of the volume would be useful to policymakers, researchers, government entities, civil society, and nonprofit organizations for monitoring and accelerating the progress of SDGs.


Book Synopsis Data Science and SDGs by : Bikas Kumar Sinha

Download or read book Data Science and SDGs written by Bikas Kumar Sinha and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book presents contributions on statistical models and methods applied, for both data science and SDGs, in one place. Measuring and controlling data of SDGs, data driven measurement of progress needs to be distributed to stakeholders. In this situation, the techniques used in data science, specially, in the big data analytics, play an important role rather than the traditional data gathering and manipulation techniques. This book fills this space through its twenty contributions. The contributions have been selected from those presented during the 7th International Conference on Data Science and Sustainable Development Goals organized by the Department of Statistics, University of Rajshahi, Bangladesh; and cover topics mainly on SDGs, bioinformatics, public health, medical informatics, environmental statistics, data science and machine learning. The contents of the volume would be useful to policymakers, researchers, government entities, civil society, and nonprofit organizations for monitoring and accelerating the progress of SDGs.


Handbook on Life Cycle Sustainability Assessment

Handbook on Life Cycle Sustainability Assessment

Author: Guido Sonnemann

Publisher: Edward Elgar Publishing

Published: 2024-04-12

Total Pages: 461

ISBN-13: 1800378653

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This Handbook presents the state-of-the-art of Life Cycle Sustainability Assessment (LCSA) practice and provides guidance for its implementation and outlook for future work. Spotlighting sustainability analysts, managers and overall decision-makers from private and public sectors as well as experts in academia, it covers the historical background and current global context for life cycle sustainability assessment, methods and data management advancements.


Book Synopsis Handbook on Life Cycle Sustainability Assessment by : Guido Sonnemann

Download or read book Handbook on Life Cycle Sustainability Assessment written by Guido Sonnemann and published by Edward Elgar Publishing. This book was released on 2024-04-12 with total page 461 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Handbook presents the state-of-the-art of Life Cycle Sustainability Assessment (LCSA) practice and provides guidance for its implementation and outlook for future work. Spotlighting sustainability analysts, managers and overall decision-makers from private and public sectors as well as experts in academia, it covers the historical background and current global context for life cycle sustainability assessment, methods and data management advancements.


CIGOS 2021, Emerging Technologies and Applications for Green Infrastructure

CIGOS 2021, Emerging Technologies and Applications for Green Infrastructure

Author: Cuong Ha-Minh

Publisher: Springer Nature

Published: 2021-10-28

Total Pages: 1861

ISBN-13: 9811671605

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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.


Book Synopsis CIGOS 2021, Emerging Technologies and Applications for Green Infrastructure by : Cuong Ha-Minh

Download or read book CIGOS 2021, Emerging Technologies and Applications for Green Infrastructure written by Cuong Ha-Minh and published by Springer Nature. This book was released on 2021-10-28 with total page 1861 pages. Available in PDF, EPUB and Kindle. Book 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.


Metabolomics, Proteomics and Gene Editing Approaches in Biofertilizer Industry

Metabolomics, Proteomics and Gene Editing Approaches in Biofertilizer Industry

Author: Sukhminderjit Kaur

Publisher: Springer Nature

Published:

Total Pages: 372

ISBN-13: 9819729106

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Book Synopsis Metabolomics, Proteomics and Gene Editing Approaches in Biofertilizer Industry by : Sukhminderjit Kaur

Download or read book Metabolomics, Proteomics and Gene Editing Approaches in Biofertilizer Industry written by Sukhminderjit Kaur and published by Springer Nature. This book was released on with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt:


Introduction to Environmental Data Science

Introduction to Environmental Data Science

Author: Jerry Davis

Publisher: CRC Press

Published: 2023-03-13

Total Pages: 492

ISBN-13: 100084241X

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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.


Book Synopsis Introduction to Environmental Data Science by : Jerry Davis

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.