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| Author | : Steven M. Manson |
| Publisher | : Cambridge University Press |
| Total Pages | : 271 |
| Release | : 2023-01-31 |
| Genre | : Business & Economics |
| ISBN | : 1108486282 |
The first comprehensive treatment of data science as a new and powerful way to understand and manage human-environment interactions.
| Author | : |
| Publisher | : Elsevier |
| Total Pages | : 3134 |
| Release | : 2017-11-08 |
| Genre | : Science |
| ISBN | : 0128032219 |
Comprehensive Remote Sensing covers all aspects of the topic, with each volume edited by well-known scientists and contributed to by frontier researchers. It is a comprehensive resource that will benefit both students and researchers who want to further their understanding in this discipline. The field of remote sensing has quadrupled in size in the past two decades, and increasingly draws in individuals working in a diverse set of disciplines ranging from geographers, oceanographers, and meteorologists, to physicists and computer scientists. Researchers from a variety of backgrounds are now accessing remote sensing data, creating an urgent need for a one-stop reference work that can comprehensively document the development of remote sensing, from the basic principles, modeling and practical algorithms, to various applications. Fully comprehensive coverage of this rapidly growing discipline, giving readers a detailed overview of all aspects of Remote Sensing principles and applications Contains ‘Layered content’, with each article beginning with the basics and then moving on to more complex concepts Ideal for advanced undergraduates and academic researchers Includes case studies that illustrate the practical application of remote sensing principles, further enhancing understanding
| Author | : Stephen Jia Wang |
| Publisher | : Springer |
| Total Pages | : 160 |
| Release | : 2018-03-22 |
| Genre | : Technology & Engineering |
| ISBN | : 3319736108 |
This book presents a practical framework for the application of big data, cloud, and pervasive and complex systems to sustainable solutions for urban environmental challenges. It covers the technologies, potential, and possible and impact of big data on energy efficiency and the urban environment. The book first introduces key aspects of big data, cloud services, pervasive computing, and mobile technologies from a pragmatic design perspective, including sample open source firmware. Cloud services, mobile and embedded platforms, interfaces, operating system design methods, networking, and middleware are all considered. The authors then explore in detail the framework, design principles, architecture and key components of developing energy systems to support sustainable urban environments. The included case study provides a pathway to improve the eco-efficiency of urban transport, demonstrating how to design an energy efficient next generation urban navigation system by leveraging vast cloud data sets on user-behavior. Ultimately, this resource maps big data’s pivotal intersection with rapid global urbanization along the path to a sustainable future.
| Author | : Jim Thatcher |
| Publisher | : U of Nebraska Press |
| Total Pages | : 318 |
| Release | : 2018-04 |
| Genre | : Science |
| ISBN | : 1496205375 |
Thinking Big Data in Geography offers a practical state-of-the-field overview of big data as both a means and an object of research, with essays from prominent and emerging scholars such as Rob Kitchin, Renee Sieber, and Mark Graham. Part 1 explores how the advent of geoweb technologies and big data sets has influenced some of geography’s major subdisciplines: urban politics and political economy, human-environment interactions, and geographic information sciences. Part 2 addresses how the geographic study of big data has implications for other disciplinary fields, notably the digital humanities and the study of social justice. The volume concludes with theoretical applications of the geoweb and big data as they pertain to society as a whole, examining the ways in which user-generated data come into the world and are complicit in its unfolding. The contributors raise caution regarding the use of spatial big data, citing issues of accuracy, surveillance, and privacy.
| Author | : Geetam S. Tomar |
| Publisher | : CRC Press |
| Total Pages | : 364 |
| Release | : 2016-10-26 |
| Genre | : Business & Economics |
| ISBN | : 149875418X |
The proposed book talks about the participation of human in Big Data.How human as a component of system can help in making the decision process easier and vibrant.It studies the basic build structure for big data and also includes advanced research topics.In the field of Biological sciences, it comprises genomic and proteomic data also. The book swaps traditional data management techniques with more robust and vibrant methodologies that focus on current requirement and demand through human computer interfacing in order to cope up with present business demand. Overall, the book is divided in to five parts where each part contains 4-5 chapters on versatile domain with human side of Big Data.
| Author | : National Academy of Engineering |
| Publisher | : National Academies Press |
| Total Pages | : 225 |
| Release | : 1997-03-03 |
| Genre | : Science |
| ISBN | : 0309051339 |
Technological Trajectories and the Human Environment provides a surprising projection of a much greener planet, based on long-range analysis of trends in the efficient use of energy, materials, and land. The authors argue that we will decarbonize the global energy system and drastically reduce greenhouse gas emissions. We will dematerialize the economy by leaner manufacturing, better product design, and smart use of materials. We will significantly increase land areas reserved for nature by conducting highly productive and environmentally friendly agriculture on less land than is used today, even as global population doubles. The book concludes that the technological opportunities before us offer the possibility of a vastly superior industrial ecology. Rich in both data and theory, the book offers fresh analyses essential for everyone in the environmental arena concerned with global change, sustainable development, and profitable investments in technology.
| Author | : Stephen Jia Wang |
| Publisher | : |
| Total Pages | : |
| Release | : 2018 |
| Genre | : Big data |
| ISBN | : 9783319736099 |
This book presents a practical framework for the application of big data, cloud, and pervasive and complex systems to sustainable solutions for urban environmental challenges. It covers the technologies, potential, and possible and impact of big data on energy efficiency and the urban environment. The book first introduces key aspects of big data, cloud services, pervasive computing, and mobile technologies from a pragmatic design perspective, including sample open source firmware. Cloud services, mobile and embedded platforms, interfaces, operating system design methods, networking, and middleware are all considered. The authors then explore in detail the framework, design principles, architecture and key components of developing energy systems to support sustainable urban environments. The included case study provides a pathway to improve the eco-efficiency of urban transport, demonstrating how to design an energy efficient next generation urban navigation system by leveraging vast cloud data sets on user-behavior. Ultimately, this resource maps big data's pivotal intersection with rapid global urbanization along the path to a sustainable future.
| Author | : Simon Elias Bibri |
| Publisher | : Springer |
| Total Pages | : 337 |
| Release | : 2019-05-30 |
| Genre | : Political Science |
| ISBN | : 3030173127 |
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 integrated view or synoptic intelligence of the city. This is increasingly being directed towards improving, advancing, and maintaining the contribution of both sustainable cities and smart cities to the goals of sustainable development. This timely and multifaceted book is aimed at a broad readership. As such, it will appeal to urban scientists, data scientists, urbanists, planners, engineers, designers, policymakers, philosophers of science, and futurists, as well as all readers interested in an overview of the pivotal role of big data science and analytics in advancing every academic discipline and social practice concerned with data–intensive science and its application, particularly in relation to sustainability.
| Author | : Piyushimita (Vonu) Thakuriah |
| Publisher | : Springer |
| Total Pages | : 559 |
| Release | : 2016-10-07 |
| Genre | : Science |
| ISBN | : 3319409026 |
This book introduces the latest thinking on the use of Big Data in the context of urban systems, including research and insights on human behavior, urban dynamics, resource use, sustainability and spatial disparities, where it promises improved planning, management and governance in the urban sectors (e.g., transportation, energy, smart cities, crime, housing, urban and regional economies, public health, public engagement, urban governance and political systems), as well as Big Data’s utility in decision-making, and development of indicators to monitor economic and social activity, and for urban sustainability, transparency, livability, social inclusion, place-making, accessibility and resilience.
| Author | : W.H. Inmon |
| Publisher | : Academic Press |
| Total Pages | : 431 |
| Release | : 2019-04-30 |
| Genre | : Computers |
| ISBN | : 0128169176 |
Over the past 5 years, the concept of big data has matured, data science has grown exponentially, and data architecture has become a standard part of organizational decision-making. Throughout all this change, the basic principles that shape the architecture of data have remained the same. There remains a need for people to take a look at the "bigger picture" and to understand where their data fit into the grand scheme of things. Data Architecture: A Primer for the Data Scientist, Second Edition addresses the larger architectural picture of how big data fits within the existing information infrastructure or data warehousing systems. This is an essential topic not only for data scientists, analysts, and managers but also for researchers and engineers who increasingly need to deal with large and complex sets of data. Until data are gathered and can be placed into an existing framework or architecture, they cannot be used to their full potential. Drawing upon years of practical experience and using numerous examples and case studies from across various industries, the authors seek to explain this larger picture into which big data fits, giving data scientists the necessary context for how pieces of the puzzle should fit together. New case studies include expanded coverage of textual management and analytics New chapters on visualization and big data Discussion of new visualizations of the end-state architecture
