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| data science for urban planning: Applied Data Analysis for Urban Planning and Management Alasdair Rae, Cecilia Wong, 2021-09-08 This book showcases the different ways in which contemporary forms of data analysis are being used in urban planning and management. It highlights the emerging possibilities that city-regional governance, technology and data have for better planning and urban management - and discusses how you can apply them to your research. Including perspectives from across the globe, it’s packed with examples of good practice and helps to demystify the process of using big and open data. Learn about different kinds of emergent data sources and how they are processed, visualised and presented. Understand how spatial analysis and GIS are used in city planning. See examples of how contemporary data analytics methods are being applied in a variety of contexts, such as ‘smart’ city management and megacities. Aimed at upper undergraduate and postgraduate students studying spatial analysis and planning, this timely text is the perfect companion to enable you to apply data analytics approaches in your research. |
| data science for urban planning: Public Policy Analytics Ken Steif, 2021-08-18 Public Policy Analytics: Code & Context for Data Science in Government teaches readers how to address complex public policy problems with data and analytics using reproducible methods in R. Each of the eight chapters provides a detailed case study, showing readers: how to develop exploratory indicators; understand ‘spatial process’ and develop spatial analytics; how to develop ‘useful’ predictive analytics; how to convey these outputs to non-technical decision-makers through the medium of data visualization; and why, ultimately, data science and ‘Planning’ are one and the same. A graduate-level introduction to data science, this book will appeal to researchers and data scientists at the intersection of data analytics and public policy, as well as readers who wish to understand how algorithms will affect the future of government. |
| data science for urban planning: Advances in Urban Planning in Developing Nations Arnab Jana, 2021-05-26 This book studies the increasing use of data analytics and technology in urban planning and development in developing nations. It examines the application of urban science and engineering in different sectors of urban planning and looks at the challenges involved in planning 21st-century cities, especially in India. The volume analyzes various key themes such as auditory/visual sensing, network analysis and spatial planning, and decision-making and management in the planning process. It also studies the application of big data, geographic information systems, and information and communications technology in urban planning. Finally, it provides data-driven approaches toward holistic and optimal urban solutions for challenges in transportation planning, housing, and conservation of vulnerable urban zones like coastal areas and open spaces. Well supplemented with rigorous case studies, the book will be of interest to scholars and researchers of architecture, architectural and urban planning, and urban analytics. It will also be useful for professionals involved in smart city planning, planning authorities, urban scientists, and municipal and local bodies. |
| data science for urban planning: Big Data Science and Analytics for Smart Sustainable Urbanism Simon Elias Bibri, 2019 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. |
| data science for urban planning: Urban Analytics Alex D. Singleton, Seth Spielman, David Folch, 2017-11-27 The economic and political situation of cities has shifted in recent years in light of rapid growth amidst infrastructure decline, the suburbanization of poverty and inner city revitalization. At the same time, the way that data are used to understand urban systems has changed dramatically. Urban Analytics offers a field-defining look at the challenges and opportunities of using new and emerging data to study contemporary and future cities through methods including GIS, Remote Sensing, Big Data and Geodemographics. Written in an accessible style and packed with illustrations and interviews from key urban analysts, this is a groundbreaking new textbook for students of urban planning, urban design, geography, and the information sciences. |
| data science for urban planning: Big Data Support of Urban Planning and Management Zhenjiang Shen, Miaoyi Li, 2017-09-26 In the era of big data, this book explores the new challenges of urban-rural planning and management from a practical perspective based on a multidisciplinary project. Researchers as contributors to this book have accomplished their projects by using big data and relevant data mining technologies for investigating the possibilities of big data, such as that obtained through cell phones, social network systems and smart cards instead of conventional survey data for urban planning support. This book showcases active researchers who share their experiences and ideas on human mobility, accessibility and recognition of places, connectivity of transportation and urban structure in order to provide effective analytic and forecasting tools for smart city planning and design solutions in China. |
| data science for urban planning: Open Source Geospatial Science for Urban Studies Amin Mobasheri, 2020-09-07 This book is mainly focused on two themes: transportation and smart city applications. Open geospatial science and technology is an increasingly important paradigm that offers the opportunity to promote the democratization of geographical information, the transparency of governments and institutions, as well as social, economic and urban opportunities. During the past decade, developments in the area of open geospatial data have greatly increased. The open source GIS research community believes that combining free and open software, open data, as well as open standards, leads to the creation of a sustainable ecosystem for accelerating new discoveries to help solve global cross-disciplinary urban challenges. The vision of this book is to enrich the existing literature on this topic, and act one step towards more sustainable cities through employment of open source GIS solutions that are reproducible. Various contributions are provided and practically implemented in several urban use cases. Therefore, apart from researchers, lecturers and students in the geography/urbanism domain, crowdsourcing and VGI domain, as well as open source GIS domain, it is believed the specialists and mentors in municipalities and urban planning departments as well as professionals in private companies would be interested to read this book. |
| data science for urban planning: Urban Systems Design Yoshiki Yamagata, Perry P. J. Yang, 2020-02-11 Urban Systems Design: Creating Sustainable Smart Cities in the Internet of Things Era shows how to design, model and monitor smart communities using a distinctive IoT-based urban systems approach. Focusing on the essential dimensions that constitute smart communities energy, transport, urban form, and human comfort, this helpful guide explores how IoT-based sharing platforms can achieve greater community health and well-being based on relationship building, trust, and resilience. Uncovering the achievements of the most recent research on the potential of IoT and big data, this book shows how to identify, structure, measure and monitor multi-dimensional urban sustainability standards and progress. This thorough book demonstrates how to select a project, which technologies are most cost-effective, and their cost-benefit considerations. The book also illustrates the financial, institutional, policy and technological needs for the successful transition to smart cities, and concludes by discussing both the conventional and innovative regulatory instruments needed for a fast and smooth transition to smart, sustainable communities. - Provides operational case studies and best practices from cities throughout Europe, North America, Latin America, Asia, Australia, and Africa, providing instructive examples of the social, environmental, and economic aspects of smartification - Reviews assessment and urban sustainability certification systems such as LEED, BREEAM, and CASBEE, examining how each addresses smart technologies criteria - Examines existing technologies for efficient energy management, including HEMS, BEMS, energy harvesting, electric vehicles, smart grids, and more |
| data science for urban planning: Spatial Planning in the Big Data Revolution Voghera, Angioletta, La Riccia, Luigi, 2019-03-15 Through interaction with other databases such as social media, geographic information systems have the ability to build and obtain not only statistics defined on the flows of people, things, and information but also on perceptions, impressions, and opinions about specific places, territories, and landscapes. It is thus necessary to systematize, integrate, and coordinate the various sources of data (especially open data) to allow more appropriate and complete analysis, descriptions, and elaborations. Spatial Planning in the Big Data Revolution is a critical scholarly resource that aims to bring together different methodologies that combine the potential of large data analysis with GIS applications in dedicated tools specifically for territorial, social, economic, environmental, transport, energy, real estate, and landscape evaluation. Additionally, the book addresses a number of fundamental objectives including the application of big data analysis in supporting territorial analysis, validating crowdsourcing and crowdmapping techniques, and disseminating information and community involvement. Urban planners, architects, researchers, academicians, professionals, and practitioners in such fields as computer science, data science, and business intelligence will benefit most from the research contained within this publication. |
| data science for urban planning: Urban Informatics Wenzhong Shi, Michael F. Goodchild, Michael Batty, Mei-Po Kwan, Anshu Zhang, 2021-04-06 This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity. |
| data science for urban planning: Data Augmented Design Ying Long, Enjia Zhang, 2020-08-13 This book offers an essential introduction to a new urban planning and design methodology called Data Augmented Design (DAD) and its evolution and progresses, highlighting data driven methods, urban planning and design applications and related theories. The authors draw on many kinds of data, including big, open, and conventional data, and discuss cutting-edge technologies that illustrate DAD as a future oriented design framework in terms of its focus on multi-data, multi-method, multi-stage and multi-scale sustainable urban planning. In four sections and ten chapters, the book presents case studies to address the core concepts of DAD, the first type of applications of DAD that emerged in redevelopment-oriented planning and design, the second type committed to the planning and design for urban expansion, and the future-oriented applications of DAD to advance sustainable technologies and the future structural form of the built environment. The book is geared towards a broad readership, ranging from researchers and students of urban planning, urban design, urban geography, urban economics, and urban sociology, to practitioners in the areas of urban planning and design. |
| data science for urban planning: Applied Remote Sensing for Urban Planning, Governance and Sustainability Maik Netzband, William L. Stefanov, Charles Redman, 2007-12-10 This evaluation of the potential of remote sensing of urban areas helps to close a gap between the research-focused results offered by the urban remote sensing community, and the application of these data and products by the governing bodies of cities and urban regions. The authors present data from six urban regions worldwide. They explain what the important questions are, and how data and scientific skills can help answer them. |
| data science for urban planning: Artificial Intelligence in Urban Planning and Design Imdat As, Prithwish Basu, Pratap Talwar, 2022-05-14 Artificial Intelligence in Urban Planning and Design: Technologies, Implementation, and Impacts is the most comprehensive resource available on the state of Artificial Intelligence (AI) as it relates to smart city planning and urban design. The book explains nascent applications of AI technologies in urban design and city planning, providing a thorough overview of AI-based solutions. It offers a framework for discussion of theoretical foundations of AI, AI applications in the urban design, AI-based research and information systems, and AI-based generative design systems. The concept of AI generates unprecedented city planning solutions without defined rules in advance, a development raising important questions issues for urban design and city planning. This book articulates current theoretical and practical methods, offering critical views on tools and techniques and suggests future directions for the meaningful use of AI technology. - Includes a cutting-edge catalogue of AI tools applied to smart city design and planning - Provides case studies from around the globe at various scales - Includes diagrams and graphics for course instruction |
| data science for urban planning: Handbook of Research on Developing Smart Cities Based on Digital Twins Del Giudice, Matteo, Osello, Anna, 2021-01-15 The advent of connected, smart technologies for the built environment may promise a significant value that has to be reached to develop digital city models. At the international level, the role of digital twin is strictly related to massive amounts of data that need to be processed, which proposes several challenges in terms of digital technologies capability, computing, interoperability, simulation, calibration, and representation. In these terms, the development of 3D parametric models as digital twins to evaluate energy assessment of private and public buildings is considered one of the main challenges of the last years. The ability to gather, manage, and communicate contents related to energy saving in buildings for the development of smart cities must be considered a specificity in the age of connection to increase citizen awareness of these fields. The Handbook of Research on Developing Smart Cities Based on Digital Twins contains in-depth research focused on the description of methods, processes, and tools that can be adopted to achieve smart city goals. The book presents a valid medium for disseminating innovative data management methods related to smart city topics. While highlighting topics such as data visualization, a web-based ICT platform, and data-sharing methods, this book is ideally intended for researchers in the building industry, energy, and computer science fields; public administrators; building managers; and energy professionals along with practitioners, stakeholders, researchers, academicians, and students interested in the implementation of smart technologies for the built environment. |
| data science for urban planning: Smart Sustainable Cities of the Future Simon Elias Bibri, 2018-02-24 This book is intended to help explore the field of smart sustainable cities in its complexity, heterogeneity, and breadth, the many faces of a topical subject of major importance for the future that encompasses so much of modern urban life in an increasingly computerized and urbanized world. Indeed, sustainable urban development is currently at the center of debate in light of several ICT visions becoming achievable and deployable computing paradigms, and shaping the way cities will evolve in the future and thus tackle complex challenges. This book integrates computer science, data science, complexity science, sustainability science, system thinking, and urban planning and design. As such, it contains innovative computer–based and data–analytic research on smart sustainable cities as complex and dynamic systems. It provides applied theoretical contributions fostering a better understanding of such systems and the synergistic relationships between the underlying physical and informational landscapes. It offers contributions pertaining to the ongoing development of computer–based and data science technologies for the processing, analysis, management, modeling, and simulation of big and context data and the associated applicability to urban systems that will advance different aspects of sustainability. This book seeks to explicitly bring together the smart city and sustainable city endeavors, and to focus on big data analytics and context-aware computing specifically. In doing so, it amalgamates the design concepts and planning principles of sustainable urban forms with the novel applications of ICT of ubiquitous computing to primarily advance sustainability. Its strength lies in combining big data and context–aware technologies and their novel applications for the sheer purpose of harnessing and leveraging the disruptive and synergetic effects of ICT on forms of city planning that are required for future forms of sustainable development. This is because the effects of such technologies reinforce one another as to their efforts for transforming urban life in a sustainable way by integrating data–centric and context–aware solutions for enhancing urban systems and facilitating coordination among urban domains. This timely and comprehensive book is aimed at a wide audience across science, academia industry, and policymaking. It provides the necessary material to inform relevant research communities of the state–of–the–art research and the latest development in the area of smart sustainable urban development, as well as a valuable reference for planners, designers, strategists, and ICT experts who are working towards the development and implementation of smart sustainable cities based on big data analytics and context–aware computing. |
| data science for urban planning: Online Research Methods in Urban and Planning Studies: Design and Outcomes Silva, Carlos Nunes, 2012-01-31 This book provides an overview of online research methods in urban and planning studies, exploring and discussing new digital tools and Web-based research methods, as well as the scholarly, legal, and ethical challenges associated with their use--Provided by publisher. |
| data science for urban planning: Urban Planning For Dummies Jordan Yin, 2012-02-21 How to create the world's new urban future With the majority of the world's population shifting to urban centres, urban planning—the practice of land-use and transportation planning to help shape cities structurally, economically, and socially—has become an increasingly vital profession. In Urban Planning For Dummies, readers will get a practical overview of this fascinating field, including studying community demographics, determining the best uses for land, planning economic and transportation development, and implementing plans. Following an introductory course on urban planning, this book is key reading for any urban planning student or anyone involved in urban development. With new studies conclusively demonstrating the dramatic impact of urban design on public psychological and physical health, the impact of the urban planner on a community is immense. And with a wide range of positions for urban planners in the public, nonprofit, and private sectors—including law firms, utility companies, and real estate development firms—having a fundamental understanding of urban planning is key to anyone even considering entry into this field. This book provides a useful introduction and lays the groundwork for serious study. Helps readers understand the essentials of this complex profession Written by a certified practicing urban planner, with extensive practical and community-outreach experience For anyone interested in being in the vanguard of building, designing, and shaping tomorrow's sustainable city, Urban Planning For Dummies offers an informative, entirely accessible introduction on learning how. |
| data science for urban planning: Basic Quantitative Research Methods for Urban Planners Reid Ewing, Keunhyun Park, 2020-02-24 In most planning practice and research, planners work with quantitative data. By summarizing, analyzing, and presenting data, planners create stories and narratives that explain various planning issues. Particularly, in the era of big data and data mining, there is a stronger demand in planning practice and research to increase capacity for data-driven storytelling. Basic Quantitative Research Methods for Urban Planners provides readers with comprehensive knowledge and hands-on techniques for a variety of quantitative research studies, from descriptive statistics to commonly used inferential statistics. It covers statistical methods from chi-square through logistic regression and also quasi-experimental studies. At the same time, the book provides fundamental knowledge about research in general, such as planning data sources and uses, conceptual frameworks, and technical writing. The book presents relatively complex material in the simplest and clearest way possible, and through the use of real world planning examples, makes the theoretical and abstract content of each chapter as tangible as possible. It will be invaluable to students and novice researchers from planning programs, intermediate researchers who want to branch out methodologically, practicing planners who need to conduct basic analyses with planning data, and anyone who consumes the research of others and needs to judge its validity and reliability. |
| data science for urban planning: Data Mining and Predictive Analytics Daniel T. Larose, 2015-02-19 Learn methods of data analysis and their application to real-world data sets This updated second edition serves as an introduction to data mining methods and models, including association rules, clustering, neural networks, logistic regression, and multivariate analysis. The authors apply a unified “white box” approach to data mining methods and models. This approach is designed to walk readers through the operations and nuances of the various methods, using small data sets, so readers can gain an insight into the inner workings of the method under review. Chapters provide readers with hands-on analysis problems, representing an opportunity for readers to apply their newly-acquired data mining expertise to solving real problems using large, real-world data sets. Data Mining and Predictive Analytics: Offers comprehensive coverage of association rules, clustering, neural networks, logistic regression, multivariate analysis, and R statistical programming language Features over 750 chapter exercises, allowing readers to assess their understanding of the new material Provides a detailed case study that brings together the lessons learned in the book Includes access to the companion website, www.dataminingconsultant, with exclusive password-protected instructor content Data Mining and Predictive Analytics will appeal to computer science and statistic students, as well as students in MBA programs, and chief executives. |
| data science for urban planning: Big Data Science and Analytics for Smart Sustainable Urbanism Simon Elias Bibri, 2019-05-30 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. |
| data science for urban planning: Big Data for Regional Science Laurie A Schintler, Zhenhua Chen, 2017-08-07 Recent technological advancements and other related factors and trends are contributing to the production of an astoundingly large and rapidly accelerating collection of data, or ‘Big Data’. This data now allows us to examine urban and regional phenomena in ways that were previously not possible. Despite the tremendous potential of big data for regional science, its use and application in this context is fraught with issues and challenges. This book brings together leading contributors to present an interdisciplinary, agenda-setting and action-oriented platform for research and practice in the urban and regional community. This book provides a comprehensive, multidisciplinary and cutting-edge perspective on big data for regional science. Chapters contain a collection of research notes contributed by experts from all over the world with a wide array of disciplinary backgrounds. The content is organized along four themes: sources of big data; integration, processing and management of big data; analytics for big data; and, higher level policy and programmatic considerations. As well as concisely and comprehensively synthesising work done to date, the book also considers future challenges and prospects for the use of big data in regional science. Big Data for Regional Science provides a seminal contribution to the field of regional science and will appeal to a broad audience, including those at all levels of academia, industry, and government. |
| data science for urban planning: Urban Climate Science for Planning Healthy Cities Chao Ren, Glenn McGregor, 2022-01-01 This volume demonstrates how urban climate science can provide valuable information for planning healthy cities. The book illustrates the idea of Science in Time, Science in Place by providing worldwide case-based urban climatic planning applications for a variety of regions and countries, utilizing relevant climatic-spatial planning experiences to address local climatic and environmental health issues. Comprised of three major sections entitled The Rise of Mega-cities and the Concept of Climate Resilience and Healthy Living, Urban Climate Science in Action, and Future Challenges and the Way Forward, the book argues for the recognition of climate as a key element of healthy cities. Topics covered include: urban resilience in a climate context, climate responsive planning and urban climate interventions to achieve healthy cities, climate extremes, public health impact, urban climate-related health risk information, urban design and planning, and governance and management of sustainable urban development. The book will appeal to an international audience of practicing planners and designers, public health and built environment professionals, social scientists, researchers in epidemiology, climatology and biometeorology, and international to city scale policy makers. Chapter “Manchester: The Role of Urban Domestic Gardens in Climate Adaptation and Resilience” is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com. |
| data science for urban planning: Encyclopedia of Urban Studies Ray Hutchison, 2010 An encyclopedia about various topics relating to urban studies. |
| data science for urban planning: Data-driven Analytics for Sustainable Buildings and Cities Xingxing Zhang, 2021-09-11 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. |
| data science for urban planning: Leveraging Data Science for Global Health Leo Anthony Celi, Maimuna S. Majumder, Patricia Ordóñez, Juan Sebastian Osorio, Kenneth E. Paik, Melek Somai, 2020-07-31 This open access book explores ways to leverage information technology and machine learning to combat disease and promote health, especially in resource-constrained settings. It focuses on digital disease surveillance through the application of machine learning to non-traditional data sources. Developing countries are uniquely prone to large-scale emerging infectious disease outbreaks due to disruption of ecosystems, civil unrest, and poor healthcare infrastructure – and without comprehensive surveillance, delays in outbreak identification, resource deployment, and case management can be catastrophic. In combination with context-informed analytics, students will learn how non-traditional digital disease data sources – including news media, social media, Google Trends, and Google Street View – can fill critical knowledge gaps and help inform on-the-ground decision-making when formal surveillance systems are insufficient. |
| data science for urban planning: Education, Space and Urban Planning Angela Million, Anna Juliane Heinrich, Thomas Coelen, 2016-07-26 This book examines a range of practical developments that are happening in education as conducted in urban settings across different scales. It contains insights that draw upon the fields of urban planning/urbanism, geography, architecture, education and pedagogy. It brings together current thinking and practical experience from German and international perspectives. This discussion is organised in four segments: schools and the neighbourhood; education and the neighbourhood; education and the city and finally, education and the region. Contributors cover a wide range of contemporary and significant socio-political aspects of education over the last decade. They reinforce emergent thinking that space and its urban context are important dimensions of education. This book also underscores the need for more research in the relationships between education and urban development itself. Current urban planning does not fully connect our understanding in education with what we know in the spatial and planning sciences. Accordingly, this release is an early attempt to bring together a growing body of integrated and interdisciplinary reflection on education theory and practice. |
| data science for urban planning: Research Design in Urban Planning Stuart Farthing, 2015-11-09 This excellent book fills a significant gap in the literature supporting planning education by providing clear, succinct advice on the design and implementation of small-scale student research projects. - Chris Couch, Professor of Geography and Planning, University of Liverpool A perfect text for supervisors to give students so that they plan their research projects carefully rather than leap headlong into data collection. - Jean Hillier, Emeritus Professor of Sustainability and Urban Planning, RMIT University, Melbourne Highly recommended... Ranging across topics such as planning a research programme and data management and the handling of ethical issues, the book will be very helpful to those embarking on a thesis or dissertation in the field. - Peter Fidler, President of the University of Sunderland Research Design in Urban Planning: A Student’s Guide is a brilliantly accessible guide to designing research for that all-important dissertation. Aimed at both undergraduate and postgraduate levels, this text will: · discuss research design, outlining the stages of the research process in clear detail and the key decisions which need to be taken at each stage · explain to students how to re-interpret policy issues as researchable questions, appropriate for investigation · look in detail at how researchers make their choice of methods, helping students to justify their own decisions · reveal the ethical dimension to such decisions in the context of a growing requirement for the ethical approval of student projects · review the issues for comparative studies – important not least because of student involvement in Erasmus programs and AESOP workshops Packed with case studies, exercises, illustrations and summaries, Research Design in Urban Planning is an invaluable resource for students undertaking their first substantial, individual investigations. |
| data science for urban planning: The Urban Climatic Map Edward Ng, Chao Ren, 2015-09-07 Rapid urbanization, higher density and more compact cities have brought about a new science of urban climatology. An understanding of the mapping of this phenomenon is crucial for urban planners. The book brings together experts in the field of Urban Climatic Mapping to provide the state of the art understanding on how urban climatic knowledge can be made available and utilized by urban planners. The book contains the technology, methodology, and various focuses and approaches of urban climatic map making. It illustrates this understanding with examples and case studies from around the world, and it explains how urban climatic information can be analysed, interpreted and applied in urban planning. The book attempts to bridge the gap between the science of urban climatology and the practice of urban planning. It provides a useful one-stop reference for postgraduates, academics and urban climatologists wishing to better understand the needs for urban climatic knowledge in city planning; and urban planners and policy makers interested in applying the knowledge to design future sustainable cities and quality urban spaces. |
| data science for urban planning: Introduction to Urban Science Luis M. A. Bettencourt, 2021-08-17 A novel, integrative approach to cities as complex adaptive systems, applicable to issues ranging from innovation to economic prosperity to settlement patterns. Human beings around the world increasingly live in urban environments. In Introduction to Urban Science, Luis Bettencourt takes a novel, integrative approach to understanding cities as complex adaptive systems, claiming that they require us to frame the field of urban science in a way that goes beyond existing theory in such traditional disciplines as sociology, geography, and economics. He explores the processes facilitated by and, in many cases, unleashed for the first time by urban life through the lenses of social heterogeneity, complex networks, scaling, circular causality, and information. Though the idea that cities are complex adaptive systems has become mainstream, until now those who study cities have lacked a comprehensive theoretical framework for understanding cities and urbanization, for generating useful and falsifiable predictions, and for constructing a solid body of empirical evidence so that the discipline of urban science can continue to develop. Bettencourt applies his framework to such issues as innovation and development across scales, human reasoning and strategic decision-making, patterns of settlement and mobility and their influence on socioeconomic life and resource use, inequality and inequity, biodiversity, and the challenges of sustainable development in both high- and low-income nations. It is crucial, says Bettencourt, to realize that cities are not zero-sum games and that knowledge, human cooperation, and collective action can build a better future. |
| data science for urban planning: Research Methods in Urban and Regional Planning Xinhao Wang, Rainer Hofe, 2008-09-02 This book provides an up-to-date introduction to the fundamental methods related to planning and human services delivery. These methods aid planners in answering crucial questions about human activities within a given community. This book brings the pillars of planning methods together in an introductory text targeted towards senior level undergraduate and graduate students. Planning professionals will also find this book an invaluable reference. |
| data science for urban planning: Technologies for Urban and Spatial Planning: Virtual Cities and Territories Pinto, Nuno Norte, 2013-07-31 This book covers a multitude of newly developed hardware and software technology advancements in urban and spatial planning and architecture, drawing on the most current research and studies of field practitioners who offer solutions and recommendations for further growth, specifically in urban and spatial developments-- |
| data science for urban planning: Analysis of Urban Growth and Sprawl from Remote Sensing Data Basudeb Bhatta, 2010-03-03 This book provides a comprehensive discussion on urban growth and sprawl, and how they can be analyzed using remote sensing imageries. It compiles views of numerous researchers that help in understanding the urban growth and sprawl; their patterns, process, causes, consequences, and countermeasures; how remote sensing data and geographic information system techniques can be used in mapping, monitoring, measuring, analyzing, and simulating the urban growth and sprawl and what are the merits and demerits of available methods and models. This book will be of value for the scientists and researchers engaged in urban geographic research, especially using remote sensing imageries. This book will serve as a rigours literature review for them. Post graduate students of urban geography or urban/regional planning may refer this book as additional studies. This book may help the academicians for preparing lecture notes and delivering lectures. Industry professionals may also be benefited from the discussed methods and models along with numerous citations. |
| data science for urban planning: The Oxford Handbook of Urban Planning Randall Crane, Rachel Weber, 2015 Why plan? How and what do we plan? Who plans for whom? These three questions are then applied across three major topics in planning: States, Markets, and the Provision of Social Goods; The Methods and Substance of Planning; and Agency, Implementation, and Decision Making. |
| data science for urban planning: Complexity, Cognition, Urban Planning and Design Juval Portugali, Egbert Stolk, 2016-05-19 This book, which resulted from an intensive discourse between experts from several disciplines – complexity theorists, cognitive scientists, philosophers, urban planners and urban designers, as well as a zoologist and a physiologist – addresses various issues regarding cities. It is a first step in responding to the challenge of generating just such a discourse, based on a dilemma identified in the CTC (Complexity Theories of Cities) domain. The latter has demonstrated that cities exhibit the properties of natural, organic complex systems: they are open, complex and bottom-up, have fractal structures and are often chaotic. CTC have further shown that many of the mathematical formalisms and models developed to study material and organic complex systems also apply to cities. The dilemma in the current state of CTC is that cities differ from natural complex systems in that they are hybrid complex systems composed, on the one hand, of artifacts such as buildings, roads and bridges, and of natural human agents on the other. This raises a plethora of new questions on the difference between the natural and the artificial, the cognitive origin of human action and behavior, and the role of planning and designing cities. The answers to these questions cannot come from a single discipline; they must instead emerge from a discourse between experts from several disciplines engaged in CTC. |
| data science for urban planning: Green and Ecological Technologies for Urban Planning: Creating Smart Cities Ercoskun, Ozge Yalciner, 2011-12-31 Ecological and technological (eco-tech) planning provides a possible response to the essential issues of sustainability and rehabilitation in rapidly growing urban spaces. Green and Ecological Technologies for Urban Planning: Creating Smart Cities addresses the ecological, technological, and social challenges faced in the smart urban planning and design of settlements when using eco-technologies – from sustainable land use to transportation, and from green areas to municipal applications – with a focus on resilience. Containing research from leading international experts, this book provides comprehensive coverage and definitions of the most important issues, concepts, trends, and technologies within the planning field. |
| data science for urban planning: Urban Planning in the Digital Age Nicolas Douay, 2018-09-05 Technological changes have often produced important social changes that translate into spatial and planning practice. Whereas the intelligent city is one of the unavoidable and even dominant concepts, digital uses can influence urban planning in four different directions. These scenarios are represented by a compass composed of a horizontal axis opposing institutional and non-institutional actors, and a second axis with open and closed opposition. |
| data science for urban planning: City Science Jeremy Burke, Ramon Gras, 2024-03 This book showcases cutting-edge research on city form revealing that urban design features such as topology, morphology, entropy and scale have massive implications to the quality of life for a city's residents. The Aretian team, a spin off company from the Harvard Innovation Lab, has developed a city science methodology to evaluate the relationship between city form and urban performance. By measuring innovation economies to design Innovation Districts, social networks, city topology, morphology, entropy and scale to create 15 Minute Cities are some of the frameworks presented in this volume. Therefore, urban designers, architects and engineers will be able to successfully tackle complex urban design challenges by using the authors' frameworks and findings in their own work. This book give readers a new set of tools to learn from, expand, and develop for the healthy growth of cities and regions around the world. With Contributions by Jordan Kruguer and Fernando Yu. |
| data science for urban planning: Order without Design Alain Bertaud, 2024-08-06 An argument that operational urban planning can be improved by the application of the tools of urban economics to the design of regulations and infrastructure. Urban planning is a craft learned through practice. Planners make rapid decisions that have an immediate impact on the ground—the width of streets, the minimum size of land parcels, the heights of buildings. The language they use to describe their objectives is qualitative—“sustainable,” “livable,” “resilient”—often with no link to measurable outcomes. Urban economics, on the other hand, is a quantitative science, based on theories, models, and empirical evidence largely developed in academic settings. In this book, the eminent urban planner Alain Bertaud argues that applying the theories of urban economics to the practice of urban planning would greatly improve both the productivity of cities and the welfare of urban citizens. Bertaud explains that markets provide the indispensable mechanism for cities’ development. He cites the experience of cities without markets for land or labor in pre-reform China and Russia; this “urban planners’ dream” created inefficiencies and waste. Drawing on five decades of urban planning experience in forty cities around the world, Bertaud links cities’ productivity to the size of their labor markets; argues that the design of infrastructure and markets can complement each other; examines the spatial distribution of land prices and densities; stresses the importance of mobility and affordability; and critiques the land use regulations in a number of cities that aim at redesigning existing cities instead of just trying to alleviate clear negative externalities. Bertaud concludes by describing the new role that joint teams of urban planners and economists could play to improve the way cities are managed. |
| data science for urban planning: Security, Privacy, and Forensics Issues in Big Data Joshi, Ramesh C., Gupta, Brij B., 2019-08-30 With the proliferation of devices connected to the internet and connected to each other, the volume of data collected, stored, and processed is increasing every day, which brings new challenges in terms of information security. As big data expands with the help of public clouds, traditional security solutions tailored to private computing infrastructures and confined to a well-defined security perimeter, such as firewalls and demilitarized zones (DMZs), are no longer effective. New security functions are required to work over the heterogenous composition of diverse hardware, operating systems, and network domains. Security, Privacy, and Forensics Issues in Big Data is an essential research book that examines recent advancements in big data and the impact that these advancements have on information security and privacy measures needed for these networks. Highlighting a range of topics including cryptography, data analytics, and threat detection, this is an excellent reference source for students, software developers and engineers, security analysts, IT consultants, academicians, researchers, and professionals. |
| data science for urban planning: Urban Informatics and Future Cities S. C. M. Geertman, Christopher Pettit, Robert Goodspeed, Aija Staffans, 2021-07-15 This book forms a selection of chapters submitted for the CUPUM (Computational Urban Planning and Urban Management) conference, held in the second week of June 2021 at Aalto University in Helsinki, Finland. Chapters were selected from a double-blind review process by the conference's scientific committee. The chapters in the book cover developments and applications with big data and urban analytics, collaborative urban planning, applications of geodesign and innovations, and planning support science. |
Data and Digital Outputs Management Plan (DDOMP)
Data and Digital Outputs Management Plan (DDOMP)
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