Big Data Science and Analytics for Smart Sustainable Urbanism

Opening the book as a scene-setting chapter, this chapter covers introduction and background as well as the aim, structure and content, and organization and design purposes of the book. The main topics, concepts and theories, research issues, knowledge gaps, opportunities, and prospects pointing to a need for elaboration or investigation in relevance to the focus and scope of the book are introduced in this chapter and then will be developed further or addressed and discussed in more details in the subsequent chapters as part of the systematic exploration of the field of smart sustainable/sustainable smart urbanism and the examination of the unprecedented paradigmatic shifts and practical advances it is undergoing in light of big data science and analytics and the underlying advanced technologies.

The big data revolution is set to erupt in both smart cities and sustainable cities throughout the world. This is manifested in bits meeting bricks on a vast scale as instrumentation, datafication, and computation are routinely pervading urban environments. As a result, smart sustainable urbanism is becoming more and more data-driven. Explicitly, big data computing and the underpinning technologies are drastically changing the way both smart cities and sustainable cities are understood, operated, managed, planned, designed, developed, and governed in relation to sustainability in the face of urbanization. This implies that urban systems are becoming much more tightly integrated and urban domains much more highly coordinated while more holistic views and synoptic city intelligence can now be provided thanks to the possibility of drawing together and interlinking urban big data as well as reducing urban life to a form of logic and calculative procedures on the basis of powerful computational algorithms. These data-driven transformations are in turn being directed for improving, advancing, and maintaining the contribution of smart sustainable/sustainable smart cities to the goals of sustainable development. This chapter provides a comprehensive, state-of-the-art review of smart sustainable/sustainable smart cities as a leading paradigm of urbanism in terms of the underlying foundational components and assumptions, research status, issues and debates, research opportunities and challenges, future practices and horizons, and technological trends and developments. As to the findings, this chapter shows that smart sustainable urbanism involves numerous issues that are unsolved, largely ignored, or underexplored from an applied theoretical perspective. And, a large part of research in this area focuses on exploiting the potentials of big data technologies and their novel applications as an effective way to mitigate or overcome the issue of sustainable cities and smart cities being extremely fragmented as landscapes and weakly connected as approaches. The comprehensive overview of and critique on existing work on smart sustainable urbanism provides a valuable reference for researchers and practitioners in related research communities and the necessary material to inform these communities of the latest developments in the area of smart sustainable urban planning and development. The outcome of this topical review will help strategic city stakeholders to understand what they can do more to advance sustainability based on big data technology and its novel applications, and also give policymakers an opportunity to identify areas for further improvement while leveraging areas of strength with regard to the future form of sustainable smart urbanism in the era of big data.

Interdisciplinarity and transdisciplinarity have become a widespread mantra for research within diverse fields, accompanied by a growing body of academic and scientific publications. The research field of smart sustainable/sustainable smart urbanism is profoundly interdisciplinary and transdisciplinary in nature. It operates out of the understanding that advances in knowledge necessitate pursuing multifaceted questions that can only be resolved from the vantage point of interdisciplinarity and transdisciplinarity. Indeed, related research problems are inherently too complex and dynamic to be addressed by single disciplines. In addition, this field does not have a unitary approach in terms of a uniform set of concepts, theories, and disciplines, as it does not represent a specific direction of research but rather multiple directions. These are analytically quite diverse. Regardless, interdisciplinarity and transdisciplinarity as scholarly perspectives apply, by extension, to any conceptual, theoretical, and/or disciplinary foundations underpinning this field. Such perspectives in this chapter represent a rather topical and organizational approach as justified and determined by the interdisciplinary aid transdisciplinary nature of the research field of smart sustainable urbanism. In this subject, additionally, theories from academic and scientific disciplines constitute a foundation for action—data–driven smart sustainable urbanism and related urban big data development as informed by data science practiced within the fields of urban science and urban informatics, as well as by sustainability science and sustainable development. In light of this, it is of relevance and importance to develop a foundational approach consisting of the relevant concepts, theories, discourses, and academic and scientific disciplines that underpin smart sustainable urbanism as a field for research and practice. With that in regard, this chapter endeavors to systematize this complex field by identifying, distilling, mixing, fusing, and thematically analytically organizing the core dimensions of this foundational approach. The primary intention of setting such approach is to conceptually and analytically relate urban planning and development, sustainable development, and urban science while emphasizing why and the extent to which sustainability and big data computing have particularly become influential in urbanism in modern society. Being interdisciplinary and transdisciplinary in nature, such approach is meant to further highlight that this scholarly character epitomizes the orientation and essence of the research field of smart sustainable urbanism in terms of its pursuit and practice. Moreover, its value lies in fulfilling one primary purpose: to explain the nature, meaning, implications, and challenges pertaining to the multifaceted phenomenon of smart sustainable urbanism. This chapter provides an important lens through which to understand a set of theories that is of high integration, fusion, applicability, and influence potential in relation to smart sustainable urbanism.

Smart sustainable/sustainable smart cities, a defining context for ICT for sustainability, have recently become the leading global paradigm of urbanism. With this position, they are increasingly gaining traction and prevalence worldwide as a promising response to the mounting challenges of sustainability and the potential effects of urbanization. In the meantime, the research in this area is garnering growing attention and rapidly burgeoning, and its status is consolidating as one of the most enticing areas of investigation today. A large part of research in this area focuses on exploiting the potentials and opportunities of advanced technologies and their novel applications, especially big data computing, as an effective way to mitigate or overcome the issue of sustainable cities and smart cities being extremely fragmented as landscapes and weakly connected as approaches. In this context, one of the most appealing strands of research in the domain of smart sustainable urbanism is that which is concerned with futures studies related to the planning and development of new models for smart sustainable cities. Not only in the futures studies using a backcasting approach to strategic planning and development, but also in those using other approaches, is trend analysis a necessary step to perform and a critical input to the scenario analysis as part of such studies. With that in regard, this chapter aims to provide a detailed qualitative analysis of the key forms of trends shaping and driving the emergence, materialization, and evolvement of the phenomenon of smart sustainable cities as a leading paradigm of urbanism, as well as to identify the relevant expected developments related to smart sustainable urbanism. It is more likely that these forms of trends reflect a congeries of long-lasting forces behind the continuation of smart sustainable cities as a set of multiple approaches to, and multiple pathways to achieving, smart sustainable urban development. As part of the futures studies related to smart sustainable city planning and development using a backcasting methodology, both the trends and expected developments are key ingredients of, and crucial inputs for, analyzing different alternative scenarios for the future or long-term visions pertaining to desirable sustainable futures in terms of their opportunities, potentials, environmental and social benefits, and other effects. This study serves to provide a necessary material for scholars, researchers, and academics, as well as other futurists, who are in the process of conducting, or planning to carry out, futures research projects or scholarly backcasting endeavors related to the field of smart sustainable urbanism.

We are moving into an era where instrumentation, datafication, and computation are routinely pervading the very fabric of cities, coupled with the interlinking, integration, and coordination of their systems and domains. As a result, vast troves of contextual and actionable data are being produced and used to operate, regulate, manage, and organize urban life. This data-driven approach to urbanism has recently become the mode of production for smart sustainable cities, which are accordingly becoming knowable, tractable, and controllable in new dynamic ways, responsive to the data generated about them by reacting to the analytical outcome of many domains of urban life in terms of enhancing and optimizing operational functioning, planning, design, development, and governance in line with the goals of sustainable development. However, topical studies tend to deal mostly with data-driven smart urbanism while barely exploring how this approach can improve and advance sustainable urbanism under what is labeled ‘data-driven smart sustainable cities’ as a leading paradigm of urbanism. Having a threefold aim, this chapter first examines how data-driven smart sustainable cities are being instrumented, datafied, and computerized so as to improve, advance, and maintain their contribution to the goals of sustainable development through enhanced practices. Secondly, it highlights and substantiates the real potential of big data technology for enabling such contribution by identifying, synthesizing, distilling, and enumerating the key practical and analytical applications of this advanced technology in relation to multiple urban systems and domains with respect to operations, functions, services, designs, strategies, and policies. Thirdly, it proposes, illustrates, and describes a novel architecture and typology of data-driven smart sustainable cities. This chapter intervenes in the existing scholarly conversation by calling attention to a relevant object of study that previous scholarship has neglected and whose significance for the field of urbanism is well elucidated, as well as by bringing new insights to and informing the ongoing debate on smart sustainable urbanism in light of big data science and analytics. This work serves to bring data-analytic thinking and practice to smart sustainable urbanism, and seeks to promote and mainstream its adoption, in addition to drawing special attention to the crucial role and enormous benefits of big data technology and its novel applications as to transforming the future form of such urbanism.

As a new area of science and technology (S&T), big data science and analytics embodies an unprecedentedly transformative 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 which is based on a computational understanding of city systems that reduces urban life to logical and algorithmic rules and procedures and that employs new scientific methods and principles, while also harnessing urban big data to provide a more holistic and integrated view or synoptic intelligence of the city. This is underpinned by epistemological realism and instrumental rationality, which sustain and are shaped by urban science. However, all knowledge is socially constructed and historically situated, so too are research methods and applied research as related to S&T and as historically produced social formations and practices that circumscribe and produce culturally specific forms of knowledge and reality. This chapter examines the unprecedented paradigmatic, scientific, scholarly, epistemic, and discursive shifts the field of smart sustainable urbanism is undergoing in light of big data science and analytics and the underlying advanced technologies, as well as discusses how these shifts intertwine with and affect one another, and their sociocultural specificity and historical situatedness. I argue that data-intensive science as a new paradigmatic shift is fundamentally changing the scientific and practical foundations of urban sustainability. In specific terms, the new urban science—as underpinned by sustainability science—is increasingly making cities more sustainable, resilient, efficient, livable, and equitable by rendering them more measurable, knowable, and tractable in terms of their operational functioning, management, planning, design, and development.

There has recently been a conscious push for cities across the globe to be smart and even smarter and thus more sustainable by developing and implementing big data technologies and their applications across various urban domains in the hopes of reaching the required level of sustainability and improving the living standard of citizens. Having gained momentum and traction as a promising response to the needed transition toward sustainability and to the challenges of urbanization, smart and smarter cities as urban planning and development strategies (or urbanism approaches) are increasingly adopting the advanced forms of ICT to improve their performance in line with the goals of sustainable development and the requirements of urban growth. One of such forms that has tremendous potential to enhance urban operations, functions, services, designs, strategies, and policies in this direction is big data computing and its application. It was not until recently that the realization grew about the benefits of exploiting the big data deluge and its extensive sources to better monitor, understand, analyze, and plan smart and smarter cities to improve their contribution to sustainability. However, topical studies on big data applications in the context of smart and smarter cities tend to deal largely with economic growth and the quality of life in terms of service efficiency and betterment, while overlooking and barely exploring the untapped potential of such applications for advancing sustainability. In fact, smart and smarter cities raise several issues and involve significant challenges when it comes to their development and implementation in the context of sustainability. This chapter provides a comprehensive, state-of-the-art review and synthesis of the field of smart and smarter cities in regard to sustainability and related big data analytics and its application in terms of the underlying foundations and assumptions, research issues and debates, opportunities and benefits, technological developments, emerging trends, future practices, and challenges and open issues. This study shows that smart and smarter cities are associated with misunderstanding and deficiencies as regards their incorporation of, and contribution to, sustainability, respectively. Nevertheless, as also revealed by this study, tremendous opportunities are available for utilizing big data applications in smart cities of the future or smarter cities to improve their contribution to the goals of sustainable development through optimizing and enhancing urban operations, functions, services, designs, strategies, and policies, as well as finding answers to challenging analytical questions and advancing knowledge forms. However, just as there are immense opportunities ahead to embrace and exploit, there are enormous challenges ahead to address and overcome in order to achieve a successful implementation of big data technology and its novel applications in such cities. These findings will help strategic city stakeholders understand what they can do more to advance sustainability based on big data applications, and also give policymakers an opportunity to identify areas for further improvement while leveraging areas of strength with regard to the future form of sustainable smart urbanism.

Sustainable cities have been the leading global paradigm of urbanism. Undoubtedly, sustainable development has significantly positively influenced city planning and development since the early 1990s. This pertains to the immense opportunities that have been explored and, thus, the enormous benefits that have been realized from the planning and development of sustainable urban forms as an instance of sustainable cities. However, the existing models of such forms, especially compact cities and eco-cities, are associated with a number of problems, issues, and challenges. This mainly involves the question of how such forms should be monitored, understood, and analyzed to improve, advance, and maintain their contribution to sustainability and hence to overcome the kind of wicked problems, intractable issues, and complex challenges they embody. This in turn brings us to the current question related to the weak connection between and the extreme fragmentation of sustainable cities and smart cities as approaches and landscapes, respectively, despite the great potential of advanced ICT for, and also its proven role in, supporting sustainable cities in improving their performance under what is labeled ‘smart sustainable cities.’ This integrated approach to urbanism takes multiple forms of combining the strengths of sustainable cities and smart cities based on how the concept of smart sustainable cities can be conceptualized and operationalized. In this respect, there has recently been a conscious push for cities across the globe to be smarter and thus more sustainable by particularly utilizing big data technology and its applications in the hopes of reaching the optimal level of sustainability. Having a twofold aim, this chapter firstly provides a comprehensive, state-of-the-art review of the domain of sustainable urbanism, with a focus on compact cities and eco-cities as models of sustainable urban forms and thus instances of sustainable cities, in terms of research issues and debates, knowledge gaps, challenges, opportunities, benefits, and emerging practices. It secondly highlights and substantiates the real, yet untapped, potential of big data technology and its novel applications for advancing sustainable cities. In so doing, it identifies, synthesizes, distills, and enumerates the key practical and analytical applications of big data technology for multiple urban domains. This study shows that sustainable urban forms involve limitations, inadequacies, difficulties, fallacies, and uncertainties in the context of sustainability, in spite of what has been realized over the past three decades or so within sustainable urbanism. Nevertheless, as also revealed by this study, tremendous opportunities are available for exploiting big data technology and its novel applications to smarten up sustainable urban forms in ways that can improve, advance, and sustain their contribution to the goals of sustainable development by optimizing and enhancing their operations, functions, services, designs, strategies, and policies across multiple urban domains, as well as by finding answers to challenging analytical questions and transforming the way knowledge can be developed and applied.

There has recently been much enthusiasm about the immense opportunities and fascinating possibilities created by the unfolding and soaring deluge of exhaustive, fast, indexical data and its new and extensive sources as to understanding, analyzing, and planning smart sustainable/sustainable smart cities in ways that improve, advance, and maintain their contribution to the goals of sustainable development. This is owing to the underlying power of thinking data-analytically about sustainability in terms of finding answers to challenging questions for addressing the wicked problems and disentangling the intractable issues related to the practice of urbanism: operational functioning, planning, design, and development. In the meantime, as widely acknowledged within the field of smart and sustainable urbanism as regards academic and scientific research, ‘small data’ studies are associated with high cost, infrequent periodicity, quick obsolescence, incompleteness, inaccuracy, as well as inherent subjectivity and biases. In addition, such studies capture a relatively limited sample of data that is tightly focused, less representative, restricted in scope and scale, time and space specific, and relatively expensive to generate and analyze. Indeed, much of our knowledge of urbanism has been gleaned from scholarly studies characterized by data scarcity and involving the use of traditional data collection and analysis methods with inherent limitations and constraints. Therefore, this chapter endeavors to develop, illustrate, and discuss a systematic framework for city analytics and ‘big data’ studies in relation to the domain of smart sustainable/sustainable smart urbanism based on cross-industry standard process for data mining. This endeavor is in response to the emerging paradigm of big data computing and the increasing role of underpinning technologies in operating, organizing, planning, and designing smart sustainable cities as a leading paradigm of urbanism. The intention is to utilize and apply well-informed, knowledge-driven decision-making and enhanced insights to improve and optimize urban operations, functions, services, designs, strategies, and policies in line with the long-term goals of sustainability. I argue that there is tremendous potential for advancing smart sustainable urbanism or transforming the knowledge of smart sustainable cities through creating a data deluge that can, through analytics, provide much more sophisticated, finer-grained, wider-scale, real-time understanding and control of various aspects of urbanity in the undoubtedly upcoming Exabyte/Zettabyte Age.

We are moving into an era where instrumentation, datafication, and computation are routinely pervading the very fabric of the city as a complex system and dynamically changing environment, and vast troves of contextual and actionable data are being generated and used to control, manage, regulate, and organize the urban life. At the heart of this emerging era of data-driven urbanism is a computational understanding of urban systems and processes that reduces urban life to a set of logic, calculative, and algorithmic rules and procedures. Such understanding entails drawing together, interlinking, and analyzing urban big data to provide a more holistic and integrated view and synoptic intelligence of the city. This is being increasingly directed for improving, advancing, and maintaining the contribution of both sustainable cities and smart cities to the goals of sustainable development. Indeed, a new era is presently unfolding wherein smart sustainable urbanism is increasingly becoming data-driven. In light of this, smart sustainable urbanism has become even more complex with the very technologies being used to make sense of and deal with it as involving special conundrums, wicked problems, intractable issues, and complex challenges associated mainly with sustainability and urbanization. Consequently, to tackle smart sustainable cities requires, I contend, innovative solutions and sophisticated approaches as to the way they can be monitored, understood, and analyzed so as to be effectively operated, managed, planned, designed, developed, and governed in line with the long-term goals of sustainability. Therefore, this chapter examines and discusses the approach to data-driven smart sustainable urbanism in terms of computerized decision support and making, intelligence functions, simulation models, and optimization and prediction methods. It also documents and highlights the potential of the integration of these advanced technologies for facilitating the synergy between the operational functioning, planning, design, and development of smart sustainable cities. I argue that data-driven urbanism is the mode of production for smart sustainable cities, which are accordingly becoming knowable, tractable, and controllable in new dynamic ways thanks to urban science and complexity science. I conclude that the upcoming developments and innovations in big data computing and the underpinning technologies, coupled with the evolving deluge of urban data, hold great potential for enhancing and advancing the different practices of smart sustainable urbanism. This work contributes to bringing data-analytic thinking and practice to smart sustainable urbanism, in addition to drawing special attention to the crucial role and enormous benefits of the emerging paradigm of big data computing as to transforming the future form of such urbanism.

At the beginning of a new decade, we have the opportunity to look forward and consider what we could achieve in the coming years in the era of big data revolution. Again, we have the chance to consider the desired future of the data-driven smart sustainable city as we are in the midst of an expansion of time horizons in city planning and development. Sustainable cities look further into the future when forming scenarios. The movement toward a long-term vision arises from three major megatrends or macro-shifts that shape our societies at a growing pace: sustainability, disruptive technology, and urbanization. Recognizing a link between these trends or shifts, sustainable cities have adopted ambitious goals that extend far into the future, which relate to the way they should be monitored, understood, and analyzed to improve, advance, and maintain their contribution to sustainability, and hence to overcome the kind of wicked problems, intractable issues, and complex challenges they embody. Indeed, sustainable cities and smart cities as landscapes and approaches are extremely fragmented and weakly connected, respectively. Moreover, there are multiple visions of, and pathways to achieving, smart sustainable cities based on how they can be conceptualized and operationalized. As a corollary of this, there is a host of opportunities to explore toward new approaches to smart sustainable urbanism. The aim of this futures study is to analyze, investigate, and develop a novel model for smart sustainable city of the future using backcasting as a scholarly and planning methodology. In doing so, it endeavors to integrate the physical landscape of sustainable cities with the informational landscape of smart cities at the technical level, as well as to merge the two strategies on several scales, all in the context of sustainability. This chapter is concerned with Step 3 of the backcasting approach being used to achieve the overall aim of the futures study. In this respect, it aims to report the outcome of Step 3 by answering 6 guiding questions. Visionary images of a long-term future can stimulate an accelerated movement toward achieving the long-term goals of sustainability. The proposed model is believed to be the first of its kind and thus has not been, to the best of one’s knowledge, produced, nor is it being currently investigated, elsewhere.