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This book aims to promote the synergistic usage of advanced computational methodologies in close relationship to geospatial information across cities of different scales. A rich collection of chapters subsumes current research frontiers originating from disciplines such as geography, urban planning, computer science, statistics, geographic information science and remote sensing. The topics covered in the book are of interest to researchers, postgraduates, practitioners and professionals. The editors hope that the scientific outcome of this book will stimulate future urban-related international and interdisciplinary research, bringing us closer to the vision of a “new science of cities.”
The classic work on the evaluation of city form. What does the city's form actually mean to the people who live there? What can the city planner do to make the city's image more vivid and memorable to the city dweller? To answer these questions, Mr. Lynch, supported by studies of Los Angeles, Boston, and Jersey City, formulates a new criterion—imageability—and shows its potential value as a guide for the building and rebuilding of cities. The wide scope of this study leads to an original and vital method for the evaluation of city form. The architect, the planner, and certainly the city dweller will all want to read this book.
Papers presented at the CMEM 2017 conference form this book, which includes research from scientists, researchers and specialists who perform experiments, develop computer codes and carry out measurements on prototypes. A wide variety of topics related to new experimental and computational methods are explored.
Data, Matter, Design presents a comprehensive overview of current design processes that rely on the input of data and use of computational design strategies, and their relationship to an array of outputs. Technological changes, through the use of computational tools and processes, have radically altered and influenced our relationship to cities and the methods by which we design architecture, urban, and landscape systems. This book presents a wide range of curated projects and contributed texts by leading architects, urbanists, and designers that transform data as an abstraction, into spatial, experiential, and performative configurations within urban ecologies, emerging materials, robotic agents, adaptive fields, and virtual constructs. Richly illustrated with over 200 images, Data, Matter, Design is an essential read for students, academics, and professionals to evaluate and discuss how data in design methodologies and theoretical discourses have evolved in the last two decades and why processes of data collection, measurement, quantification, simulation, algorithmic control, and their integration into methods of reading and producing spatial conditions, are becoming vital in academic and industry practices.
This textbook integrates GIS, spatial analysis, and computational methods for solving real-world problems in various policy-relevant social science applications. Thoroughly updated, the third edition showcases the best practices of computational spatial social science and includes numerous case studies with step-by-step instructions in ArcGIS Pro and open-source platform KNIME. Readers sharpen their GIS skills by applying GIS techniques in detecting crime hotspots, measuring accessibility of primary care physicians, forecasting the impact of hospital closures on local community, or siting the best locations for business. FEATURES Fully updated using the latest version of ArcGIS Pro and open-source platform KNIME Features two brand-new chapters on agent-based modeling and big data analytics Provides newly automated tools for regionalization, functional region delineation, accessibility measures, planning for maximum equality in accessibility, and agent-based crime simulation Includes many compelling examples and real-world case studies related to social science, urban planning, and public policy Provides a website for downloading data and programs for implementing all case studies included in the book and the KNIME lab manual Intended for students taking upper-level undergraduate and graduate-level courses in quantitative geography, spatial analysis, and GIS applications, as well as researchers and professionals in fields such as geography, city and regional planning, crime analysis, public health, and public administration.
This book explains why the earliest cities had grid-form street systems, what conditions led to their being overwhelmingly preferred for 5000 years throughout the world, why the Founding Fathers wanted gridform cities and how they affect economic transactions. Real property has been instrumental in forming urban settlements for 5000 years, but virtually all urban form commentary, theory and research has ignored this reality. The result is an incomplete and flawed understanding of cities. Real property became a means of arranging spatial patterns caused by millennia of human evolutionary and historical developments with respect to access and movement. As a result, access to resources of all types became a regulatory mechanism controlled, at least in part, by real property ownership. The effects of real property on urban spatial patterns are currently best seen by examining American urban space, which has changed significantly over the past 200 years. This change, which began in the 1840s and established path dependence through a combination of design thought, sentimental pastoralism and financial prowess resulted in an urban regime shift that diminished economic resilience. This book offers a rethinking of how real property relates to real space, examines the thought of form promoters, links space, property, neurological evolution and settlement form, shows access is measurable and describes the plusses and minuses of functionalism, rent seeking, general purpose technology, grid-form street systems and what the American Founding Fathers thought about urban form.
This volume contains the best papers presented at the 2nd ECCOMAS International Conference on Multiscale Computations for Solids and Fluids, held June 10-12, 2015. Topics dealt with include multiscale strategy for efficient development of scientific software for large-scale computations, coupled probability-nonlinear-mechanics problems and solution methods, and modern mathematical and computational setting for multi-phase flows and fluid-structure interaction. The papers consist of contributions by six experts who taught short courses prior to the conference, along with several selected articles from other participants dealing with complementary issues, covering both solid mechanics and applied mathematics.
This book contains the proceedings of the 4TH International Conference on Computational Methods in Science and Technology (ICCMST 2024). The proceedings explores research and innovation in the field of Internet of things, Cloud Computing, Machine Learning, Networks, System Design and Methodologies, Big Data Analytics and Applications, ICT for Sustainable Environment, Artificial Intelligence and it provides real time assistance and security for advanced stage learners, researchers and academicians has been presented. This will be a valuable read to researchers, academicians, undergraduate students, postgraduate students, and professionals within the fields of Computer Science, Sustainability and Artificial Intelligence.
Machine Learning and the City Explore the applications of machine learning and artificial intelligence to the built environment Machine Learning and the City: Applications in Architecture and Urban Design delivers a robust exploration of machine learning (ML) and artificial intelligence (AI) in the context of the built environment. Relevant contributions from leading scholars in their respective fields describe the ideas and techniques that underpin ML and AI, how to begin using ML and AI in urban design, and the likely impact of ML and AI on the future of city design and planning. Each section couples theoretical and technical chapters, authoritative references, and concrete examples and projects that illustrate the efficacy and power of machine learning in urban design. The book also includes: An introduction to the probabilistic logic that underpins machine learning Comprehensive explorations of the applications of machine learning and artificial intelligence to urban environments Practical discussions of the consequences of applied machine learning and the future of urban design Perfect for designers approaching machine learning and AI for the first time, Machine Learning and the City: Applications in Architecture and Urban Design will also earn a place in the libraries of urban planners and engineers involved in urban design.
This volume focuses on practical aspects of sustainable water management in urban areas and presents a discussion of key concepts, methodologies, and case studies of innovative and evolving technologies. Topics include: (1) challenges in urban water resiliency; (2) water and energy nexus; (3) integrated urban water management; and (4) water reuse options (black water, gray water, rainwater). This volume serves as a useful reference for students and researchers involved in holistic approaches to water management, and as a valuable guide to experts in governmental agencies as well as planners and engineers concerned with sustainable water management systems in urban environments.