1.

Record Nr.

UNINA9910483345903321

Autore

Long Ying

Titolo

Data Augmented Design : Embracing New Data for Sustainable Urban Planning and Design / / by Ying Long, Enjia Zhang

Pubbl/distr/stampa

Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021

ISBN

3-030-49618-X

Edizione

[1st ed. 2021.]

Descrizione fisica

1 online resource (XXIII, 242 p. 149 illus., 136 illus. in color.)

Collana

Spatial Planning and Sustainable Development, , 2522-8471

Disciplina

307.12160285

Soggetti

Big data

Sociology, Urban

Computer-aided engineering

Sustainability

Big Data

Urban Sociology

Computer-Aided Engineering (CAD, CAE) and Design

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Sommario/riassunto

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.