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Data Augmented Design

Data Augmented Design: Embracing New Data for Sustainable Urban Planning and Design

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Data Augmented Design: Embracing New Data for Sustainable Urban Planning and Design

Long, Ying; Zhang, Enjia

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 isgeared 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.​

    

Details

Published by: Springer

Publication Date: 2021-08-15

Format: Paperback

ISBN-13: 9783030496203

DOI: 10.1007/978-3-030-49618-0

Dimensions: 235.0cm x155.0cm

Pages: 242.0

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